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Wieringa TH, León-García M, Espinoza Suárez NR, Hernández-Leal MJ, Jacome CS, Zisman-Ilani Y, Otten RHJ, Montori VM, Pieterse AH. The role of time in involving patients with cancer in treatment decision making: A scoping review. Patient Educ Couns 2024; 125:108285. [PMID: 38701622 DOI: 10.1016/j.pec.2024.108285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Revised: 03/28/2024] [Accepted: 04/01/2024] [Indexed: 05/05/2024]
Abstract
BACKGROUND Time is often perceived as a barrier to shared decision making in cancer care. It remains unclear how time functions as a barrier and how it could be most effectively utilized. OBJECTIVE This scoping review aimed to describe the role of time in patient involvement, and identify strategies to overcome time-related barriers. METHODS Seven databases were searched for any publications on patient involvement in cancer treatment decisions, focusing on how time is used to involve patients, the association between time and patient involvement, and/or strategies to overcome time-related barriers. Reviewers worked independently and in duplicate to select publications and extract data. One coder thematically analyzed data, a second coder checked these analyses. RESULTS The analysis of 26 eligible publications revealed four themes. Time was a resource 1) to process the diagnosis, 2) to obtain/process/consider information, 3) for patients and clinicians to spend together, and 4) for patient involvement in making decisions. DISCUSSION Time is a resource throughout the treatment decision-making process, and generic strategies have been proposed to overcome time constraints. PRACTICE VALUE Clinicians could co-create decision-making timelines with patients, spread decisions across several consultations, share written information with patients, and support healthcare redesigns that allocate the necessary time.
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Affiliation(s)
- Thomas H Wieringa
- Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands; Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Montserrat León-García
- Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain; Knowledge and Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA; Department of Pediatrics, Obstetrics, Gynecology and Preventive Medicine, Universidad Autónoma de Barcelona, Barcelona, Spain
| | - Nataly R Espinoza Suárez
- Knowledge and Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA; VITAM - Center for Sustainable Health Research, Integrated University Health and Social Services Center of Capitale-Nationale, Quebec City, QC, Canada; Faculty of Nursing, Laval University, Quebec City, QC, Canada
| | - María José Hernández-Leal
- Knowledge and Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA; Department of Economics, Rovira i Virgili University, Tarragona, Spain; University of Navarra, School of Nursing, Department of Community, Maternity and Pediatric Nursing, Campus Universitario, 31008 Pamplona, Spain; Millennium Nucleus on Sociomedicine, 750908 Santiago, Chile
| | - Cristian Soto Jacome
- Knowledge and Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA; Division of Internal Medicine, Department of Medicine, Norwalk Hospital, Norwalk, CT, USA
| | - Yaara Zisman-Ilani
- Department of Social and Behavioral Sciences, College of Public Health, Temple University, Philadelphia, PA, USA; Department of Clinical, Educational and Health Psychology, Division of Psychology and Language Sciences, University College London, London, UK
| | - René H J Otten
- Walaeus Library, Leiden University Medical Center, Leiden, the Netherlands
| | - Victor M Montori
- Knowledge and Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA
| | - Arwen H Pieterse
- Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands.
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Mandhana DM, Jacome CS, Ballard DI, Tesfai Y, Johnson SB, Gionfriddo MR, Espinoza Suarez NR, Perneth SA, Su L, Montori VM. Developing and validating the Unhurried Conversations Assessment Tool (UCAT). Patient Educ Couns 2024; 123:108237. [PMID: 38461793 DOI: 10.1016/j.pec.2024.108237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 01/29/2024] [Accepted: 02/29/2024] [Indexed: 03/12/2024]
Abstract
OBJECTIVE Given the importance of unhurried conversations for providing careful and kind care, we sought to create, test, and validate the Unhurried Conversations Assessment Tool (UCAT) for assessing the unhurriedness of patient-clinician consultations. METHODS In the first two phases, the unhurried conversation dimensions were identified and transformed into an assessment tool. In the third phase, two independent raters used UCAT to evaluate the unhurriedness of 100 randomly selected consultations from 184 videos recorded for a large research trial. UCAT's psychometric properties were evaluated using this data. RESULTS UCAT demonstrates content validity based on the literature and expert review. EFA and reliability analyses confirm its construct validity and internal consistency. The seven formative dimensions account for 89.93% of the variance in unhurriedness, each displaying excellent internal consistency (α > 0.90). Inter-rater agreement for the overall assessment item was fair (ICC = 0.59), with individual dimension ICCs ranging from 0.26 (poor) to 0.95 (excellent). CONCLUSION UCAT components comprehensively assess the unhurriedness of consultations. The tool exhibits content and construct validity and can be used reliably. PRACTICE IMPLICATIONS UCAT's design and psychometric properties make it a practical and efficient tool. Clinicians can use it for self-evaluations and training to foster unhurried conversations.
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Affiliation(s)
- Dron M Mandhana
- Department of Communication, Villanova University, Villanova, PA, USA; Knowledge & Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA
| | - Cristian Soto Jacome
- Knowledge & Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA; Norwalk Hospital, Department of Internal Medicine, Nuvance Health, Norwalk, CT, USA
| | - Dawna I Ballard
- Knowledge & Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA; Department of Communication Studies, The University of Texas at Austin, Austin, TX, USA
| | - Yohanna Tesfai
- Department of Communication Studies, The University of Texas at Austin, Austin, TX, USA
| | - Sarah B Johnson
- Knowledge & Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA
| | - Michael R Gionfriddo
- Division of Pharmaceutical, Administrative, and Social Sciences, School of Pharmacy, Duquesne University, Pittsburgh, PA, USA
| | - Nataly R Espinoza Suarez
- Knowledge & Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA; VITAM - Centre for Sustainable Health Research, Integrated University Health and Social Services Center of Capitale-Nationale, Quebec City, QC, Canada; Faculty of Nursing, Laval University, Quebec City, QC, Canada
| | - Sandra Algarin Perneth
- Knowledge & Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, USA
| | - Lillian Su
- Division of Cardiovascular Intensive Care Medicine, Phoenix Children's Hospital, Phoenix, AZ, USA
| | - Victor M Montori
- Knowledge & Evaluation Research (KER) Unit, Mayo Clinic, Rochester, MN, USA.
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Tabatabaei Yeganeh HS, Kiliaki SA, Gnanapandithan K, Loor-Torres R, Duran M, Yousufuddin M, Prokop LJ, Vella A, Montori VM, Dugani SB. Inclusion of Rurality and Social Determinants of Health in Documents for the Primary Prevention of Type 2 Diabetes: A Systematic Review. Metab Syndr Relat Disord 2024. [PMID: 38708695 DOI: 10.1089/met.2023.0124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/07/2024] Open
Abstract
Purpose: The type 2 diabetes (T2D) burden is disproportionately concentrated in low- and middle-income economies, particularly among rural populations. The purpose of the systematic review was to evaluate the inclusion of rurality and social determinants of health (SDOH) in documents for T2D primary prevention. Methods: This systematic review is reported following Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines. We searched 19 databases, from 2017-2023, for documents on rurality and T2D primary prevention. Furthermore, we searched online for documents from the 216 World Bank economies, categorized by high, upper-middle, lower-middle, and low income status. We extracted data on rurality and the ten World Health Organization SDOH. Two authors independently screened documents and extracted data. Findings: Based on 3318 documents (19 databases and online search), we selected 15 documents for data extraction. The 15 documents applied to 32 economies; 12 of 15 documents were from nongovernment sources, none was from low-income economies, and 10 of 15 documents did not define or describe rurality. Among the SDOH, income and social protection (SDOH 1) and social inclusion and nondiscrimination (SDOH 8) were mentioned in documents for 25 of 29 high-income economies, while food insecurity (SDOH 5) and housing, basic amenities, and the environment (SDOH 6) were mentioned in documents for 1 of 2 lower-middle-income economies. For U.S. documents, none of the authors was from institutions in noncore (most rural) counties. Conclusions: Overall, documents on T2D primary prevention had sparse inclusion of rurality and SDOH, with additional disparity based on economic status. Inclusion of rurality and/or SDOH may improve T2D primary prevention in rural populations.
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Affiliation(s)
| | - Shangwe A Kiliaki
- Division of Hospital Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Ricardo Loor-Torres
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, Minnesota, USA
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Mayra Duran
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, Minnesota, USA
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Mohammed Yousufuddin
- Division of Hospital Medicine, Mayo Clinic Health System, Austin, Minnesota, USA
| | | | - Adrian Vella
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, Minnesota, USA
| | - Victor M Montori
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, Minnesota, USA
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Sagar B Dugani
- Division of Hospital Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA
- Division of Health Care Delivery Research, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA
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Muganzi DJ, Namara CM, Kintu TM, Atulinda L, Kihumuro RB, Ahaisibwe B, Montori VM. Paving the Path to Patient-Centered Healthcare in Africa: Insights From a Student Led Initiative. Ann Glob Health 2024; 90:27. [PMID: 38618271 PMCID: PMC11012222 DOI: 10.5334/aogh.4250] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 01/23/2024] [Indexed: 04/16/2024] Open
Abstract
Patient-centered care (PCC) is a key domain of healthcare quality. Its importance is driven by evidence-based medicine, the predominance of chronic conditions requiring self-care, and the recognition of the priority of patient goals, values, priorities, and preferences in determining care plans. This article emphasizes the urgent need for Africa to develop PCC and a workforce committed to its implementation, as well as highlights an initiative by African medical students to champion PCC continent-wide. Embracing this transformative approach presents Africa with an unprecedented opportunity to improve care for each person. Through a comprehensive exploration of unique strategies and considerations in African health professions education, this viewpoint seeks to spark dialogue and inspire action towards a future where patient-centered care is the foundation of healthcare delivery in Africa.
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Affiliation(s)
- David Jolly Muganzi
- Patient Centered Care movement Africa (PaCeM-Afro), Kampala, Uganda
- The Patient Revolution, Inc, United States
| | | | - Timothy Mwanje Kintu
- Patient Centered Care movement Africa (PaCeM-Afro), Kampala, Uganda
- African Center of Excellence in Bioinformatics and Data Intensive Sciences, Makerere, University, Kampala, Uganda
| | - Linda Atulinda
- Patient Centered Care movement Africa (PaCeM-Afro), Kampala, Uganda
| | | | | | - Victor M. Montori
- The Patient Revolution, Inc, United States
- Knowledge and Evaluation Research Unit, Mayo Clinic (Rochester, Minnesota), United States
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Keij SM, Branda ME, Montori VM, Brito JP, Kunneman M, Pieterse AH. Patient Characteristics and the Extent to Which Clinicians Involve Patients in Decision Making: Secondary Analyses of Pooled Data. Med Decis Making 2024; 44:346-356. [PMID: 38563311 PMCID: PMC10988989 DOI: 10.1177/0272989x241231721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 01/22/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND The occurrence of shared decision making (SDM) in daily practice remains limited. Various patient characteristics have been suggested to potentially influence the extent to which clinicians involve patients in SDM. OBJECTIVE To assess associations between patient characteristics and the extent to which clinicians involve patients in SDM. METHODS We conducted a secondary analysis of data pooled from 10 studies comparing the care of adult patients with (intervention) or without (control) a within-encounter SDM conversation tool. We included studies with audio(-visual) recordings of clinical encounters in which decisions about starting or reconsidering treatment were discussed. MAIN MEASURES In the original studies, the Observing Patient Involvement in Decision Making 12-items (OPTION12 item) scale was used to code the extent to which clinicians involved patients in SDM in clinical encounters. We conducted multivariable analyses with patient characteristics (age, gender, race, education, marital status, number of daily medications, general health status, health literacy) as independent variables and OPTION12 as a dependent variable. RESULTS We included data from 1,614 patients. The between-arm difference in OPTION12 scores was 7.7 of 100 points (P < 0.001). We found no association between any patient characteristics and the OPTION12 score except for education level (p = 0.030), an association that was very small (2.8 points between the least and most educated), contributed mostly by, and only significant in, control arms (6.5 points). Subanalyses of a stroke prevention trial showed a positive association between age and OPTION12 score (P = 0.033). CONCLUSIONS Most characteristics showed no association with the extent to which clinicians involved patients in SDM. Without an SDM conversation tool, clinicians devoted more efforts to involve patients with higher education, a difference not observed when the tool was used. HIGHLIGHTS Most sociodemographic patient characteristics show no association with the extent to which clinicians involve patients in shared decision making.Clinicians devoted less effort to involve patients with lower education, a difference that was not observed when a shared decision-making conversation tool was used.SDM conversation tools can be useful for clinicians to better involve patients and ensure patients get involved equally regardless of educational background.
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Affiliation(s)
- Sascha M. Keij
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, The Netherlands
| | - Megan E. Branda
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester MN, USA
| | - Victor M. Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester MN, USA
| | - Juan P. Brito
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester MN, USA
| | - Marleen Kunneman
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, The Netherlands
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester MN, USA
| | - Arwen H. Pieterse
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, The Netherlands
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Garcia SI, Finch AS, Ridgeway JL, Beckman TJ, Montori VM, Rivera M, Gajic O, Kennedy CC, Kelm DJ. Understanding Team Dynamics and Culture of Safety using Video Reflexive Ethnography during Real-Time Emergent Intubation. Ann Am Thorac Soc 2024. [PMID: 38470228 DOI: 10.1513/annalsats.202310-901oc] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 03/08/2024] [Indexed: 03/13/2024] Open
Abstract
RATIONALE Endotracheal intubation is the third most common bedside procedure in U.S. hospitals. In over 40% of intubations preventable complications attributable to human factors occur. A better understanding of team dynamics during intubation may improve patient safety. OBJECTIVE To explore team dynamics and safety-related actions during emergent endotracheal intubations in the emergency department (ED) and intensive care unit (ICU), and to engage members of the care team in reflection for process improvement through a novel video-based team debriefing technique. METHODS Video-reflexive ethnography involves in-situ video-recording and reflexive discussions with practitioners to scrutinize behaviors and to identify opportunities for improvement. In this study, real-time intubations were recorded in the ED and ICU at Mayo Clinic Rochester and facilitated video-reflexive sessions were conducted with the multidisciplinary procedural teams. Themes about team dynamics and safety-related action were identified inductively from transcriptions of recorded sessions. RESULTS Between December 2022 and January 2023, eight video-reflexive sessions were conducted with a total of 78 participants. Multidisciplinary members included nurses (n=23), respiratory therapists (n=16), pharmacists (n=7), advanced practitioners (n=5), and physicians (n=26). Video-reflexive discussions identified major safety gaps and proposed several solutions related to the use of a multidisciplinary intubation checklist, standardized communication and team positioning, developing a culture of safety, and routinely debriefing after the procedure. CONCLUSION The findings of this study may inform the development of a team supervision model for emergent endotracheal intubations. This approach could integrate key components such as a multidisciplinary intubation checklist, standardized communication and team positioning, a culture of safety, and debriefing as part of the procedure itself.
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Affiliation(s)
- Samuel I Garcia
- Mayo Clinic, 6915, Division of Pulmonary, Critical Care and Sleep Medicine, Rochester, Minnesota, United States
| | - Alexander S Finch
- Mayo Clinic, 6915, Department of Emergency Medicine, Rochester, Minnesota, United States
| | - Jennifer L Ridgeway
- Mayo Clinic Rochester, 384842, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, Minnesota, United States
| | - Thomas J Beckman
- Mayo Clinic, 6915, Division of General Internal Medicine, Rochester, Minnesota, United States
| | - Victor M Montori
- Mayo Clinic, 6915, Division of Endocrinology, Rochester, Minnesota, United States
| | - Mariela Rivera
- Mayo Clinic, 6915, Department of Surgery, Rochester, Minnesota, United States
| | - Ognjen Gajic
- Mayo Clinic College of Medicine, Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, Rochester, Minnesota, United States
| | - Cassie C Kennedy
- Mayo Clinic, Division of Pulmonary and Critical Care Medicine, Rochester, Minnesota, United States
| | - Diana J Kelm
- Mayo Clinic, Division of Pulmonary and Critical Care Medicine, Rochester, Minnesota, United States;
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Singh Ospina N, Patel Chavez C, Godinez Leiva E, Bagautdinova D, Hidalgo J, Hartasanchez S, Algarin Perneth S, Barb D, Danan D, Dziegielewski P, Hughley B, Srihari A, Subbarayan S, Castro MR, Dean D, Morris J, Ryder M, Stan MN, Hargraves I, Bylund CL, Treise D, Montori VM, Brito JP. Clinician feedback using a shared decision-making tool for the evaluation of patients with thyroid nodules-an observational study. Endocrine 2024; 83:449-458. [PMID: 37695453 PMCID: PMC10999160 DOI: 10.1007/s12020-023-03519-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 08/30/2023] [Indexed: 09/12/2023]
Abstract
BACKGROUND We pilot-tested an encounter conversation aid to support shared decision making (SDM) between patients with thyroid nodules and their clinicians. OBJECTIVE Characterize the clinician feedback after providing care to patients with thyroid nodules using a tool to promote SDM conversations during the clinical encounter, and evaluate how clinicians used the tool during the visit. METHODS Mixed method study in two academic centers in the U.S., including adult patients presenting for evaluation of thyroid nodules and their clinicians. We thematically analyzed interviews with clinicians after they used the SDM tool in at least three visits to characterize their feedback. Additionally, investigators evaluated visits recordings to determine the extent to which clinicians engaged patients in the decision-making process (OPTION score, scale 0 to 100, higher levels indicating higher involvement), the tool's components used (fidelity), and encounter duration. Using a post-visit survey, we evaluated the extent to which clinicians felt the tool was easy to use, helpful, and supportive of the patient-clinician collaboration. RESULTS Thirteen clinicians participated in the study and used the SDM tool in the care of 53 patients. Clinicians thought the tool was well-organized and beneficial to patients and clinicians. Clinicians noticed a change in their routine with the use of the conversation aid and suggested it needed to be more flexible to better support varying conversations. The median OPTION score was 34, the fidelity of use 75%, and the median visit duration 17 min. In most encounters, clinicians agreed or strongly agreed the tool was easy to use (86%), helpful (65%), and supported collaboration (62%). CONCLUSION Clinicians were able to use a SDM tool in the care of patients with thyroid nodules. Although they wished it were more flexible, they found on the whole that its use in the clinical encounter was beneficial to patients and clinicians.
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Affiliation(s)
- Naykky Singh Ospina
- Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, FL, USA.
| | - Chandani Patel Chavez
- Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, FL, USA
| | - Eddison Godinez Leiva
- Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, FL, USA
| | - Diliara Bagautdinova
- College of Journalism and Communications, University of Florida, Gainesville, FL, USA
| | - Jessica Hidalgo
- Knowledge and Evaluation Research Unit in Endocrinology (KER_Endo), Mayo Clinic, Rochester, MN, USA
| | - Sandra Hartasanchez
- Knowledge and Evaluation Research Unit in Endocrinology (KER_Endo), Mayo Clinic, Rochester, MN, USA
| | - Sandra Algarin Perneth
- Knowledge and Evaluation Research Unit in Endocrinology (KER_Endo), Mayo Clinic, Rochester, MN, USA
| | - Diana Barb
- Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, FL, USA
| | - Deepa Danan
- Department of Otolaryngology, University of Florida, Gainesville, FL, USA
| | | | - Brian Hughley
- Department of Otolaryngology, University of Florida, Gainesville, FL, USA
| | - Ashok Srihari
- Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, FL, USA
| | - Sreevidya Subbarayan
- Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, FL, USA
| | | | - Diana Dean
- Division of Endocrinology, Mayo Clinic, Rochester, MN, USA
| | - John Morris
- Division of Endocrinology, Mayo Clinic, Rochester, MN, USA
| | - Mabel Ryder
- Division of Endocrinology, Mayo Clinic, Rochester, MN, USA
| | - Marius N Stan
- Division of Endocrinology, Mayo Clinic, Rochester, MN, USA
| | - Ian Hargraves
- Knowledge and Evaluation Research Unit in Endocrinology (KER_Endo), Mayo Clinic, Rochester, MN, USA
| | - Carma L Bylund
- Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA
| | - Debbie Treise
- College of Journalism and Communications, University of Florida, Gainesville, FL, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit in Endocrinology (KER_Endo), Mayo Clinic, Rochester, MN, USA
- Division of Endocrinology, Mayo Clinic, Rochester, MN, USA
| | - Juan P Brito
- Knowledge and Evaluation Research Unit in Endocrinology (KER_Endo), Mayo Clinic, Rochester, MN, USA
- Division of Endocrinology, Mayo Clinic, Rochester, MN, USA
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Martinez KA, Montori VM, Rodriguez F, Tereshchenko LG, Kovach JD, Hurwitz HM, Rothberg MB. Clinician use of the Statin Choice Shared Decision-making Encounter Tool in a Major Health System. J Gen Intern Med 2024:10.1007/s11606-023-08597-3. [PMID: 38191974 DOI: 10.1007/s11606-023-08597-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 12/28/2023] [Indexed: 01/10/2024]
Abstract
BACKGROUND Effective shared decision-making (SDM) tools for use during clinical encounters are available, but, outside of study settings, little is known about clinician use of these tools in practice. OBJECTIVE To describe real-world use of an SDM encounter tool for statin prescribing, Statin Choice, embedded into the workflow of an electronic health record. DESIGN Cross-sectional study. PARTICIPANTS Clinicians and their statin-eligible patients who had outpatient encounters between January 2020 and June 2021 in Cleveland Clinic Health System. MAIN MEASURES Clinician use of Statin Choice was recorded within the Epic record system. We categorized each patient's 10-year atherosclerotic cardiovascular disease risk into low (< 5%), borderline (5-7.5%), intermediate (7.5-20%), and high (≥ 20%). Other patient factors included age, sex, insurance, and race. We used mixed effects logistic regression to assess the odds of using Statin Choice for statin-eligible patients, accounting for clustering by clinician and site. We generated a residual intraclass correlation coefficient (ICC) to characterize the impact of the clinician on Statin Choice use. KEY RESULTS Statin Choice was used in 7% of 68,505 eligible patients. Of 1047 clinicians, 48% used Statin Choice with ≥ 1 patient, and these clinicians used it with a median 9% of their patients (interquartile range: 3-22%). In the mixed effects logistic regression model, patient age (adjusted OR per year: 1.04; 95%CI 1.03-1.04) and 10-year ASVCD risk (aOR for 5-7.5% versus < 5% risk: 1.28; 95%CI: 1.14-1.44) were associated with use of Statin Choice. Black versus White race was associated with a lower odds of Statin Choice use (aOR: 0.83; 95%CI: 0.73-0.95), as was female versus male sex (aOR: 0.83; 95%CI: 0.76-0.90). The model ICC demonstrated that 53% of the variation in use of Statin Choice was clinician-driven. CONCLUSIONS Patient factors, including race and sex, were associated with clinician use of Statin Choice; half the variation in use was attributable to individual clinicians.
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Affiliation(s)
- Kathryn A Martinez
- Cleveland Clinic Center for Value-Based Care Research, Cleveland, OH, USA.
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | - Fatima Rodriguez
- Division of Cardiovascular Medicine and the Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Larisa G Tereshchenko
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
- Department of Cardiovascular Medicine, Heart, Vascular & Thoracic Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jeffrey D Kovach
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA
| | | | - Michael B Rothberg
- Cleveland Clinic Center for Value-Based Care Research, Cleveland, OH, USA
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Lenfant T, Ravaud P, Montori VM, Berntsen GR, Tran VT. Five principles for the development of minimally disruptive digital medicine. BMJ 2023; 383:2960. [PMID: 38114257 DOI: 10.1136/bmj.p2960] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Affiliation(s)
- Tiphaine Lenfant
- Université Paris Cité, METHODS Team, CRESS, INSERM, INRAE, Paris, France
- Assistance Publique-Hôpitaux de Paris, Médecine Interne, Hôpital Européen Georges Pompidou, Paris, France
| | - Philippe Ravaud
- Université Paris Cité, METHODS Team, CRESS, INSERM, INRAE, Paris, France
- Assistance Publique-Hôpitaux de Paris, Centre d'Épidémiologie Clinique, Hôpital Hôtel-Dieu, Paris, France
- Columbia University Mailman School of Public Health, Department of Epidemiology, New York, USA2 AP HEGP
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, 55905, USA
| | - Gro R Berntsen
- Norwegian Center for e-healthresearch, University hospital of North Norway, Unit for Primary Care, Institute of Community Medicine, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Viet-Thi Tran
- Université Paris Cité, METHODS Team, CRESS, INSERM, INRAE, Paris, France
- Assistance Publique-Hôpitaux de Paris, Centre d'Épidémiologie Clinique, Hôpital Hôtel-Dieu, Paris, France
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Kidholm K, Jensen LK, Johansson M, Montori VM. Telemedicine and the assessment of clinician time: a scoping review. Int J Technol Assess Health Care 2023; 40:e3. [PMID: 38099431 PMCID: PMC10859839 DOI: 10.1017/s0266462323002830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2024]
Abstract
OBJECTIVES Telemedicine may improve healthcare access and efficiency if it demands less clinician time than usual care. We sought to describe the degree to which telemedicine trials assess the effect of telemedicine on clinicians' time and to discuss how including the time needed to treat (TNT) in health technology assessment (HTA) could affect the design of telemedicine services and studies. METHODS We conducted a scoping review by searching clinicaltrials.gov using the search term "telemedicine" and limiting results to randomized trials or observational studies registered between January 2012 and October 2023. We then reviewed trial registration data to determine if any of the outcomes assessed in the trials measured effect on clinicians' time. RESULTS We found 113 studies and of these 78 studies of telemedicine met the inclusion criteria and were included. Nine (12 percent) of the 78 studies had some measure of clinician time as a primary outcome, and 11 (14 percent) as a secondary outcome. Four studies compared direct measures of TNT with telemedicine versus usual care, but no statistically significant difference was found. Of the sixteen studies including indirect measures of clinician time, thirteen found no significant effects, two found a statistically significant reduction, and one found a statistically significant increase. CONCLUSIONS This scoping review found that clinician time is not commonly measured in studies of telemedicine interventions. Attention to telemedicine's TNT in clinical studies and HTAs of telemedicine in practice may bring attention to the organization of clinical workflows and increase the value of telemedicine.
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Affiliation(s)
- Kristian Kidholm
- Center for Innovative Medical Technology, Odense University Hospital and University of Southern Denmark, Denmark
| | - Lise Kvistgaard Jensen
- Center for Innovative Medical Technology, Odense University Hospital and University of Southern Denmark, Denmark
| | - Minna Johansson
- Global Center for Sustainable Healthcare, School of Public Health and Community Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Victor M Montori
- Department of Medicine, Mayo Clinic, Knowledge and Evaluation Research Unit, Rochester, MN, USA
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León-García M, Wieringa TH, Espinoza Suárez NR, Hernández-Leal MJ, Villanueva G, Singh Ospina N, Hidalgo J, Prokop LJ, Rocha Calderón C, LeBlanc A, Zeballos-Palacios C, Brito JP, Montori VM. Does the duration of ambulatory consultations affect the quality of healthcare? A systematic review. BMJ Open Qual 2023; 12:e002311. [PMID: 37875307 PMCID: PMC10603464 DOI: 10.1136/bmjoq-2023-002311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 09/23/2023] [Indexed: 10/26/2023] Open
Abstract
BACKGROUND The objective is to examine and synthesise the best available experimental evidence about the effect of ambulatory consultation duration on quality of healthcare. METHODS We included experimental studies manipulating the length of outpatient clinical encounters between adult patients and clinicians (ie, therapists, pharmacists, nurses, physicians) to determine their effect on quality of care (ie, effectiveness, efficiency, timeliness, safety, equity, patient-centredness and patient satisfaction). INFORMATION SOURCES Using controlled vocabulary and keywords, without restriction by language or year of publication, we searched MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials and Database of Systematic Reviews and Scopus from inception until 15 May 2023. RISK OF BIAS Cochrane Risk of Bias instrument. DATA SYNTHESIS Narrative synthesis. RESULTS 11 publications of 10 studies explored the relationship between encounter duration and quality. Most took place in the UK's general practice over two decades ago. Study findings based on very sparse and outdated evidence-which suggested that longer consultations improved indicators of patient-centred care, education about prevention and clinical referrals; and that consultation duration was inconsistently related to patient satisfaction and clinical outcomes-warrant low confidence due to limited protections against bias and indirect applicability to current practice. CONCLUSION Experimental evidence for a minimal or optimal duration of an outpatient consultation is sparse and outdated. To develop evidence-based policies and practices about encounter length, randomised trials of different consultation lengths-in person and virtually, and with electronic health records-are needed. TRIAL REGISTRATION NUMBER OSF Registration DOI:10.17605/OSF.IO/EUDK8.
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Affiliation(s)
- Montserrat León-García
- Biomedical Research Institute Sant Pau (IIB Sant Pau), Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya, Spain
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
- Department of Pediatrics, Obstetrics, Gynaecology and Preventive Medicine, Universidad Autónoma de Barcelona, Barcelona, Spain
| | - Thomas H Wieringa
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University, Leiden, Netherlands
| | - Nataly R Espinoza Suárez
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
- VITAM Research Center for Sustainable Health, Quebec Integrated University Health and Social Services; Faculty of Medicine, Université Laval, Quebec, Quebec, Canada
| | - María José Hernández-Leal
- Department of Economics. Research Centre on Economics and Sustainability (ECO-SOS). Research Group on Statistics, Economic Evaluation and Health (GRAEES), Faculty of Business and Economics. Rovira i Virgili University, Reus, Spain
| | - Gemma Villanueva
- Department of Pediatrics, Obstetrics, Gynaecology and Preventive Medicine, Universidad Autónoma de Barcelona, Barcelona, Spain
- Cochrane Response, London, UK
| | - Naykky Singh Ospina
- Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, Florida, USA
| | - Jessica Hidalgo
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Larry J Prokop
- Mayo Clinic Libraries, Mayo Clinic, Mayo Clinic, Rochester, Minnesota, USA
| | - Claudio Rocha Calderón
- Department of Preventive Medicine, University Hospital of Bellvitge, IDIBELL, Barcelona, Catalunya, Spain
| | - Annie LeBlanc
- VITAM Research Center for Sustainable Health, Quebec Integrated University Health and Social Services; Faculty of Medicine, Université Laval, Quebec, Quebec, Canada
| | - Claudia Zeballos-Palacios
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Juan Pablo Brito
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, Minnesota, USA
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12
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Vickery KD, Ford BR, Gelberg L, Bonilla Z, Strother E, Gust S, Adair E, Montori VM, Linzer M, Evans MD, Connett J, Heisler M, O'Connor PJ, Busch AM. The development and initial feasibility testing of D-HOMES: a behavioral activation-based intervention for diabetes medication adherence and psychological wellness among people experiencing homelessness. Front Psychol 2023; 14:1225777. [PMID: 37794913 PMCID: PMC10546874 DOI: 10.3389/fpsyg.2023.1225777] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 08/08/2023] [Indexed: 10/06/2023] Open
Abstract
Introduction Compared to stably housed peers, people experiencing homelessness (PEH) have lower rates of ideal glycemic control, and experience premature morbidity and mortality. High rates of behavioral health comorbidities and trauma add to access barriers driving poor outcomes. Limited evidence guides behavioral approaches to support the needs of PEH with diabetes. Lay coaching models can improve care for low-resource populations with diabetes, yet we found no evidence of programs specifically tailored to the needs of PEH. Methods We used a multistep, iterative process following the ORBIT model to develop the Diabetes Homeless Medication Support (D-HOMES) program, a new lifestyle intervention for PEH with type 2 diabetes. We built a community-engaged research team who participated in all of the following steps of treatment development: (1) initial treatment conceptualization drawing from evidence-based programs, (2) qualitative interviews with affected people and multi-disciplinary housing and healthcare providers, and (3) an open trial of D-HOMES to evaluate acceptability (Client Satisfaction Questionnaire, exit interview) and treatment engagement (completion rate of up to 10 offered coaching sessions). Results In step (1), the D-HOMES treatment manual drew from existing behavioral activation and lay health coach programs for diabetes as well as clinical resources from Health Care for the Homeless. Step (2) qualitative interviews (n = 26 patients, n = 21 providers) shaped counseling approaches, language and choices regarding interventionists, tools, and resources. PTSD symptoms were reported in 69% of patients. Step (3) trial participants (N = 10) overall found the program acceptable, however, we saw better program satisfaction and treatment engagement among more stably housed people. We developed adapted treatment materials for the target population and refined recruitment/retention strategies and trial procedures sensitive to prevalent discrimination and racism to better retain people of color and those with less stable housing. Discussion The research team has used these findings to inform an NIH-funded randomized control pilot trial. We found synergy between community-engaged research and the ORBIT model of behavioral treatment development to develop a new intervention designed for PEH with type 2 diabetes and address health equity gaps in people who have experienced trauma. We conclude that more work and different approaches are needed to address the needs of participants with the least stable housing.
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Affiliation(s)
- Katherine Diaz Vickery
- The Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN, United States
- Department of Medicine, Hennepin Healthcare, Minneapolis, MN, United States
- The Quorum for Community Engaged Wellness Research, Minneapolis, MN, United States
| | - Becky R. Ford
- The Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN, United States
- Department of Medicine, Hennepin Healthcare, Minneapolis, MN, United States
| | - Lillian Gelberg
- Department of Family Medicine, David Geffen School of Medicine at UCLA and UCLA Fielding School of Public Health, Los Angeles, CA, United States
| | - Zobeida Bonilla
- School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - Ella Strother
- The Health, Homelessness, and Criminal Justice Lab, Hennepin Healthcare Research Institute, Minneapolis, MN, United States
- Department of Medicine, Hennepin Healthcare, Minneapolis, MN, United States
| | - Susan Gust
- The Quorum for Community Engaged Wellness Research, Minneapolis, MN, United States
| | - Edward Adair
- The Quorum for Community Engaged Wellness Research, Minneapolis, MN, United States
| | - Victor M. Montori
- Division of Endocrinology, Diabetes, Metabolism, Nutrition, Department of Internal Medicine and the Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, United States
| | - Mark Linzer
- Department of Medicine, Hennepin Healthcare, Minneapolis, MN, United States
| | - Michael D. Evans
- Clinical and Translational Science Institute, University of Minnesota, Minneapolis, MN, United States
| | - John Connett
- School of Public Health, University of Minnesota, Minneapolis, MN, United States
| | - Michele Heisler
- Division of General Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Patrick J. O'Connor
- Center for Chronic Care Innovation, HealthPartners Institute, Bloomington, MN, United States
| | - Andrew M. Busch
- Department of Medicine, Hennepin Healthcare, Minneapolis, MN, United States
- The Behavioral Health Equity Research Group, Hennepin Healthcare Research Institute, Minneapolis, MN, United States
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Affiliation(s)
- Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Merel M Ruissen
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
- Department of Biomedical Data Sciences, Section of Medical Decision Making, Leiden University Medical Center, Leiden, Netherlands
- Department of Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden, Netherlands
| | - Ian G Hargraves
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Juan P Brito
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Marleen Kunneman
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
- Department of Biomedical Data Sciences, Section of Medical Decision Making, Leiden University Medical Center, Leiden, Netherlands
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Mendoza-Quispe D, Perez-Leon S, Alarcon-Ruiz CA, Gaspar A, Cuba-Fuentes MS, Zunt JR, Montori VM, Bazo-Alvarez JC, Miranda JJ. Scoping review of measures of treatment burden in patients with multimorbidity: advancements and current gaps. J Clin Epidemiol 2023; 159:92-105. [PMID: 37217106 PMCID: PMC10529536 DOI: 10.1016/j.jclinepi.2023.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 05/03/2023] [Accepted: 05/16/2023] [Indexed: 05/24/2023]
Abstract
OBJECTIVES To identify, assess, and summarize the measures to assess burden of treatment in patients with multimorbidity (BoT-MMs) and their measurement properties. STUDY DESIGN AND SETTING MEDLINE via PubMed was searched from inception until May 2021. Independent reviewers extracted data from studies in which BoT-MMs were developed, validated, or reported as used, including an assessment of their measurement properties (e.g., validity and reliability) using the COnsensus-based Standards for the selection of health Measurement INstruments. RESULTS Eight BoT-MMs were identified across 72 studies. Most studies were performed in English (68%), in high-income countries (90%), without noting urban-rural settings (90%). No BoT-MMs had both sufficient content validity and internal consistency; some measurement properties were either insufficient or uncertain (e.g., responsiveness). Other frequent limitations of BoT-MMs included absent recall time, presence of floor effects, and unclear rationale for categorizing and interpreting raw scores. CONCLUSION The evidence needed for use of extant BoT-MMs in patients with multimorbidity remains insufficiently developed, including that of suitability for their development, measurement properties, interpretability of scores, and use in low-resource settings. This review summarizes this evidence and identifies issues needing attention for using BoT-MMs in research and clinical practice.
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Affiliation(s)
- Daniel Mendoza-Quispe
- CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru.
| | - Silvana Perez-Leon
- CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru
| | - Christoper A Alarcon-Ruiz
- Unidad de Investigación para la Generación y Síntesis de Evidencias en Salud, Universidad San Ignacio de Loyola, Lima, Peru
| | - Andrea Gaspar
- School of Medicine, University of Washington, Washington, DC, USA
| | | | - Joseph R Zunt
- Departments of Neurology, Global Health, Medicine (Infectious Diseases), and Epidemiology, University of Washington, Seattle, WA, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN 55905, USA
| | - Juan Carlos Bazo-Alvarez
- Research Department of Primary Care and Population Health, University College London, London, UK
| | - J Jaime Miranda
- CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru; School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru; The George Institute for Global Health, UNSW, Sydney, Australia
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Tabatabaei Yeganeh HS, Prokop LJ, Kiliaki SA, Gnanapandithan K, Yousufuddin M, Vella A, Montori VM, Dugani SB. Guidelines, position statements, and advisories for the primary prevention of type 2 diabetes, hypertension, and cardiovascular disease in rural populations: A systematic review protocol. PLoS One 2023; 18:e0288116. [PMID: 37384783 PMCID: PMC10309979 DOI: 10.1371/journal.pone.0288116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 06/12/2023] [Indexed: 07/01/2023] Open
Abstract
INTRODUCTION Globally, noncommunicable diseases (NCDs), which include type 2 diabetes (T2D), hypertension, and cardiovascular disease (CVD), are associated with a high burden of morbidity and mortality. Health disparities exacerbate the burden of NCDs. Notably, rural, compared with urban, populations face greater disparities in access to preventive care, management, and treatment of NCDs. However, there is sparse information and no known literature synthesis on the inclusion of rural populations in documents (i.e., guidelines, position statements, and advisories) pertaining to the prevention of T2D, hypertension, and CVD. To address this gap, we are conducting a systematic review to assess the inclusion of rural populations in documents on the primary prevention of T2D, hypertension, and CVD. METHODS AND ANALYSIS This protocol follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched 19 databases including EMBASE, MEDLINE, and Scopus, from January 2017 through October 2022, on the primary prevention of T2D, hypertension, and CVD. We conducted separate Google® searches for each of the 216 World Bank economies. For primary screening, titles and/or abstracts were screened independently by two authors (databases) or one author (Google®). Documents meeting selection criteria will undergo full-text review (secondary screening) using predetermined criteria, and data extraction using a standardized form. The definition of rurality varies, and we will report the description provided in each document. We will also describe the social determinants of health (based on the World Health Organization) that may be associated with rurality. ETHICS AND DISSEMINATION To our knowledge, this will be the first systematic review on the inclusion of rurality in documents on the primary prevention of T2D, hypertension, and CVD. Ethics approval is not required since we are not using patient-level data. Patients are not involved in the study design or analysis. We will present the results at conferences and in peer-reviewed publication(s). TRIAL REGISTRATION PROSPERO Registration Number: CRD42022369815.
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Affiliation(s)
| | - Larry J. Prokop
- Mayo Clinic Libraries, Rochester, MN, United States of America
| | - Shangwe A. Kiliaki
- Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, United States of America
| | - Karthik Gnanapandithan
- Division of Hospital Internal Medicine, Mayo Clinic, Jacksonville, FL, United States of America
| | - Mohammed Yousufuddin
- Division of Hospital Medicine, Mayo Clinic Health System, Austin, MN, United States of America
| | - Adrian Vella
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN, United States of America
| | - Victor M. Montori
- Division of Endocrinology, Diabetes & Metabolism, Mayo Clinic College of Medicine, Rochester, MN, United States of America
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, United States of America
| | - Sagar B. Dugani
- Division of Hospital Internal Medicine, Mayo Clinic, Rochester, MN, United States of America
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, United States of America
- Division of Health Care Delivery Research, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, United States of America
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Shickh S, Leventakos K, Lewis MA, Bombard Y, Montori VM. Shared Decision Making in the Care of Patients With Cancer. Am Soc Clin Oncol Educ Book 2023; 43:e389516. [PMID: 37339391 DOI: 10.1200/edbk_389516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/22/2023]
Abstract
Shared decision making (SDM) is a method of care that is suitable for the care of patients with cancer. It involves a collaborative conversation seeking to respond sensibly to the problematic situation of the patient, cocreating a plan of care that makes sense intellectually, practically, and emotionally. Genetic testing to identify whether a patient has a hereditary cancer syndrome represents a prime example of the importance for SDM in oncology. SDM is important for genetic testing because not only results affect current cancer treatment, cancer surveillance, and care of relatives but also these tests generate both complex results and psychological concerns. SDM conversations should take place without interruptions, disruptions, or hurry and be supported, where available, by tools that assist in conveying the relevant evidence and in supporting plan development. Examples of these tools include treatment SDM encounter aids and the Genetics Adviser. Patients are expected to play a key role in making decisions and implementing plans of care, but several evolving challenges related to the unfettered access to information and expertise of varying trustworthiness and complexity in between interactions with clinicians can both support and complicate this role. SDM should result in a plan of care that is maximally responsive to the biology and biography of each patient, maximally supportive of each patient's goals and priorities, and minimally disruptive of their lives and loves.
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Affiliation(s)
- Salma Shickh
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
| | - Konstantinos Leventakos
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN
- Department of Medical Oncology, Mayo Clinic, Rochester, MN
| | - Mark A Lewis
- Division of Gastrointestinal Oncology, Intermountain Healthcare, Salt Lake City, UT
| | - Yvonne Bombard
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Genomics Health Services Research Program, Li Ka Shing Knowledge Institute, St Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada
- Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN
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Joyce DD, Tilburt JC, Pacyna JE, Cina K, Petereit DG, Koller KR, Flanagan CA, Stillwater B, Miller M, Kaur JS, Peil E, Zahrieh D, Dueck AC, Montori VM, Frosch DL, Volk RJ, Kim SP. The Impact of Within-Consultation and Preconsultation Decision Aids for Localized Prostate Cancer on Patient Knowledge: Results of a Patient-Level Randomized Trial. Urology 2023; 175:90-95. [PMID: 36898587 PMCID: PMC10239323 DOI: 10.1016/j.urology.2023.02.029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 02/09/2023] [Accepted: 02/19/2023] [Indexed: 03/11/2023]
Abstract
OBJECTIVE To evaluate the role of timing (either before or during initial consultation) on the effectiveness of decision aids (DAs) to support shared-decision-making in a minority-enriched sample of patients with localized prostate cancer using a patient-level randomized controlled trial design. METHODS We conducted a 3-arm, patient-level-randomized trial in urology and radiation oncology practices in Ohio, South Dakota, and Alaska, testing the effect of preconsultation and within-consultation DAs on patient knowledge elements deemed essential to make treatment decisions about localized prostate cancer, all measured immediately following the initial urology consultation using a 12-item Prostate Cancer Treatment Questionnaire (score range 0 [no questions correct] to 1 [all questions correct]), compared to usual care (no DAs). RESULTS Between 2017 and 2018, 103 patients-including 16 Black/African American and 17 American Indian or Alaska Native men-were enrolled and randomly assigned to receive usual care (n = 33) or usual care and a DA before (n = 37) or during (n = 33) the consultation. After adjusting for baseline characteristics, there were no statistically significant proportional score differences in patient knowledge between the preconsultation DA arm (0.06 knowledge change, 95% CI -0.02 to 0.12, P = .1) or the within-consultation DA arm (0.04 knowledge change, 95% CI -0.03 to 0.11, P = .3) and usual care. CONCLUSION In this trial oversampling minority men with localized prostate cancer, DAs presented at different times relative to the specialist consultation showed no improvement in patient knowledge above usual care.
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Affiliation(s)
| | - Jon C Tilburt
- Division of General Internal Medicine, Mayo Clinic, Scottsdale, AZ; Division of Health Care Policy and Research, Mayo Clinic, Rochester, MN; Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN.
| | - Joel E Pacyna
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, MN
| | - Kristin Cina
- Walking Forward Avera Health, Division of Research, Rapid City, SD
| | - Daniel G Petereit
- Cancer Care Institute at Monument Health, Rapid City, SD; Walking Forward Avera Health, Division of Research, Rapid City, SD
| | - Kathryn R Koller
- Alaska Native Tribal Health Consortium Research Services, Anchorage, AK
| | - Christie A Flanagan
- Alaska Native Tribal Health Consortium Research Services, Anchorage, AK; Alaska Native Epidemiology Center, Alaska Native Tribal Health Consortium, Anchorage, AK
| | | | - Mariam Miller
- Department of Urology, Alaska Native Medical Center, Anchorage, AK
| | - Judith S Kaur
- Department of Hematology and Oncology, Mayo Clinic, Jacksonville, FL
| | - Elizabeth Peil
- Clinical Trials and Biostatistics, Mayo Clinic, Rochester, MN
| | - David Zahrieh
- Clinical Trials and Biostatistics, Mayo Clinic, Rochester, MN
| | - Amylou C Dueck
- Clinical Trials and Biostatistics, Mayo Clinic, Scottsdale, AZ
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN
| | | | - Robert J Volk
- Division of Cancer Prevention and Population Sciences, Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX
| | - Simon P Kim
- Division of Urology, University of Colorado Anschutz Medical Center, University of Colorado, Aurora, CO
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Kunneman M, Gravholt D, Hartasanchez SA, Gionfriddo MR, Paskins Z, Prokop LJ, Stiggelbout AM, Montori VM. Assessing collaborative efforts of making care fit for each patient - A systematic review. Health Expect 2023. [PMID: 36973176 DOI: 10.1111/hex.13759] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 12/14/2022] [Accepted: 03/26/2023] [Indexed: 03/29/2023] Open
Abstract
INTRODUCTION For too many people, their care plans are designed without fully accounting for who they are, the lives they live, what matters to them, or what they aspire to achieve. We aimed to summarize instruments capable of measuring dimensions of patient-clinician collaboration to make care fit. METHODS We systematically searched several databases (Medline, Embase, Cochrane, Scopus, and Web of Science) from inception to September 2021 for studies using quantitative measures to assess, evaluate or rate the work of making care fit by any participant in real-life clinical encounters. Eligibility was assessed in duplicate. After extracting all items from relevant instruments, we coded them deductively on dimensions relevant to making care fit (as presented in a recent Making Care Fit Manifesto), and inductively on main action described. RESULTS We included 189 papers, mostly from North America (N=83, 44%) and in the context of primary care (N=54, 29%). Half of the papers (N=88, 47%) were published in the last five years. We found 1243 relevant items to assess efforts of making care fit, included within 151 instruments. Most items related to the dimensions "Patient-clinician collaboration: content" (N=396, 32%) and "Patient-clinician collaboration: manner" (N=382, 31%), and the least related to "Ongoing and iterative process" (N=22, 2%) and in "Minimally disruptive of patient lives" (N=29, 2%). The items referred to 27 specific actions. Most items referred to "Informing" (N=308, 25%) and "Exploring" (N=93, 8%), the fewest items referred to "Following up", "Comforting", and "Praising" (each N=3, 0.2%). DISCUSSION Measures of the work that patients and clinicians do together to make care fit focus heavily on the content of their collaborations, particularly on exchanging information. Other dimensions and actions previously identified as crucial to making care fit are assessed infrequently or not at all. The breadth of extant measures of making care fit and the lack of appropriate measures of this key construct limit both the assessment and the successful implementation of efforts to improve patient care. PATIENT CONTRIBUTION Patients and caregivers from the 'Making care fit Collaborative' were involved in drafting the dimensions relevant to patient-clinician collaboration. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Marleen Kunneman
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | | | | | - Michael R Gionfriddo
- School of Pharmacy, Division of Pharmaceutical, Social and Administrative Sciences, Duquesne University, Pittsburgh, PA, USA
| | - Zoe Paskins
- School of Medicine, Keele University, Newcastle-under-Lyme, UK
- Haywood Academic Rheumatology Centre, Midlands Partnership NHS Foundation Trust, Stoke-on-Trent, UK
| | | | - Anne M Stiggelbout
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, the Netherlands
- Erasmus School of Health Policy and Management, Erasmus University Rotterdam, the Netherlands
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
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Steiger KG, Boehmer KR, Klanderman MC, Mookadam A, Koneru SS, Montori VM, Mookadam M. Who Is Most Burdened in Health Care? An Analysis of Responses to the ICAN Discussion Aid. J Am Board Fam Med 2023; 36:277-288. [PMID: 36948538 DOI: 10.3122/jabfm.2022.220251r1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 10/27/2022] [Accepted: 11/01/2022] [Indexed: 03/24/2023] Open
Abstract
OBJECTIVE To create a model based on patients' characteristics that can predict the number of burdens reported using the ICAN Discussion Aid, to target use of this tool to patients likeliest to benefit. PATIENTS AND METHODS Six hundred thirty-five patients (aged ≥18 years) completed the ICAN Discussion Aid at a Scottsdale, Arizona, family medicine clinic. Patient characteristics were gathered from their health records. Regression trees with Poisson splitting criteria were used to model the data. RESULTS Our model suggests the patients with the most burdens had major depressive disorder, with twice as many overall burdens (personal plus health care burdens) than patients without depression. Patients with depression who were younger than 38 years had the highest number of personal burdens. A body mass index (BMI) of 26 or greater was associated with increased health care burden versus a BMI below 26. CONCLUSION The number of burdens a patient will report on the ICAN Discussion Aid can be approximated based on certain patient characteristics. Adults with major depression, a BMI of 26 or greater, and younger age may have greater reported burdens on ICAN, but this finding needs to be validated in independent samples.
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Affiliation(s)
- Kyle G Steiger
- From the Mayo Clinic Alix School of Medicine, Mayo Clinic College of Medicine and Science, Scottsdale (KGS); Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota (KRB, VMM); Division of Health Care Delivery Research, Mayo Clinic, Rochester, Minnesota (KRB); Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona (MCK); Mayo Clinic, Scottsdale, Arizona (AM, SSK); Department of Family Medicine, Mayo Clinic, Scottsdale, Arizona (MM); Arizona State University, Tempe (AM)
| | - Kasey R Boehmer
- From the Mayo Clinic Alix School of Medicine, Mayo Clinic College of Medicine and Science, Scottsdale (KGS); Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota (KRB, VMM); Division of Health Care Delivery Research, Mayo Clinic, Rochester, Minnesota (KRB); Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona (MCK); Mayo Clinic, Scottsdale, Arizona (AM, SSK); Department of Family Medicine, Mayo Clinic, Scottsdale, Arizona (MM); Arizona State University, Tempe (AM)
| | - Molly C Klanderman
- From the Mayo Clinic Alix School of Medicine, Mayo Clinic College of Medicine and Science, Scottsdale (KGS); Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota (KRB, VMM); Division of Health Care Delivery Research, Mayo Clinic, Rochester, Minnesota (KRB); Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona (MCK); Mayo Clinic, Scottsdale, Arizona (AM, SSK); Department of Family Medicine, Mayo Clinic, Scottsdale, Arizona (MM); Arizona State University, Tempe (AM)
| | - Aamena Mookadam
- From the Mayo Clinic Alix School of Medicine, Mayo Clinic College of Medicine and Science, Scottsdale (KGS); Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota (KRB, VMM); Division of Health Care Delivery Research, Mayo Clinic, Rochester, Minnesota (KRB); Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona (MCK); Mayo Clinic, Scottsdale, Arizona (AM, SSK); Department of Family Medicine, Mayo Clinic, Scottsdale, Arizona (MM); Arizona State University, Tempe (AM)
| | - Sethu Sandeep Koneru
- From the Mayo Clinic Alix School of Medicine, Mayo Clinic College of Medicine and Science, Scottsdale (KGS); Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota (KRB, VMM); Division of Health Care Delivery Research, Mayo Clinic, Rochester, Minnesota (KRB); Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona (MCK); Mayo Clinic, Scottsdale, Arizona (AM, SSK); Department of Family Medicine, Mayo Clinic, Scottsdale, Arizona (MM); Arizona State University, Tempe (AM)
| | - Victor M Montori
- From the Mayo Clinic Alix School of Medicine, Mayo Clinic College of Medicine and Science, Scottsdale (KGS); Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota (KRB, VMM); Division of Health Care Delivery Research, Mayo Clinic, Rochester, Minnesota (KRB); Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona (MCK); Mayo Clinic, Scottsdale, Arizona (AM, SSK); Department of Family Medicine, Mayo Clinic, Scottsdale, Arizona (MM); Arizona State University, Tempe (AM)
| | - Martina Mookadam
- From the Mayo Clinic Alix School of Medicine, Mayo Clinic College of Medicine and Science, Scottsdale (KGS); Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota (KRB, VMM); Division of Health Care Delivery Research, Mayo Clinic, Rochester, Minnesota (KRB); Department of Quantitative Health Sciences, Mayo Clinic, Scottsdale, Arizona (MCK); Mayo Clinic, Scottsdale, Arizona (AM, SSK); Department of Family Medicine, Mayo Clinic, Scottsdale, Arizona (MM); Arizona State University, Tempe (AM).
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Ruissen MM, Montori VM, Hargraves IG, Branda ME, León García M, de Koning EJ, Kunneman M. Problem-based shared decision-making in diabetes care: a secondary analysis of video-recorded encounters. BMJ Evid Based Med 2023; 28:157-163. [PMID: 36868578 DOI: 10.1136/bmjebm-2022-112067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/12/2023] [Indexed: 03/05/2023]
Abstract
OBJECTIVES To describe the range of collaborative approaches to shared decision-making (SDM) observed in clinical encounters of patients with diabetes and their clinicians. DESIGN A secondary analysis of videorecordings obtained in a randomised trial comparing usual diabetes primary care with or without using a within-encounter conversation SDM tool. SETTING Using the purposeful SDM framework, we classified the forms of SDM observed in a random sample of 100 video-recorded clinical encounters of patients with type 2 diabetes in primary care. MAIN OUTCOME MEASURES We assessed the correlation between the extent to which each form of SDM was used and patient involvement (OPTION12-scale). RESULTS We observed at least one instance of SDM in 86 of 100 encounters. In 31 (36%) of these 86 encounters, we found only one form of SDM, in 25 (29%) two forms, and in 30 (35%), we found ≥3 forms of SDM. In these encounters, 196 instances of SDM were identified, with weighing alternatives (n=64 of 196, 33%), negotiating conflicting desires (n=59, 30%) and problemsolving (n=70, 36%) being similarly prevalent and developing existential insight accounting for only 1% (n=3) of instances. Only the form of SDM focused on weighing alternatives was correlated with a higher OPTION12-score. More forms of SDM were used when medications were changed (2.4 SDM forms (SD 1.48) vs 1.8 (SD 1.46); p=0.050). CONCLUSIONS After considering forms of SDM beyond weighing alternatives, SDM was present in most encounters. Clinicians and patients often used different forms of SDM within the same encounter. Recognising a range of SDM forms that clinicians and patients use to respond to problematic situations, as demonstrated in this study, opens new lines of research, education and practice that may advance patient-centred, evidence-based care.
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Affiliation(s)
- Merel M Ruissen
- Department of Medicine, Leiden University Medical Center, Leiden, The Netherlands
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Ian G Hargraves
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Megan E Branda
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA
| | - Montserrat León García
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
- Biomedical Research Institute Sant Pau (IIB Sant Pau), Barcelona, Spain
| | - Eelco Jp de Koning
- Department of Medicine, Leiden University Medical Center, Leiden, The Netherlands
| | - Marleen Kunneman
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
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21
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Meza-Contreras A, Wenczenovicz C, Ruiz-Arellanos K, Vesely EAK, Mogollon R, Montori VM. Statin intolerance management: a systematic review. Endocrine 2023; 79:430-436. [PMID: 36459335 DOI: 10.1007/s12020-022-03263-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 11/14/2022] [Indexed: 12/04/2022]
Abstract
BACKGROUND Statin intolerance is a key barrier to the effective prevention of atherosclerotic cardiovascular disease (ASCVD). Experts do not agree on what it is and how to respond to this problem clinically. OBJECTIVE To characterize the range of expert recommendations about the care of patients with statin intolerance. METHODS Systematic review registered in PROSPERO that searched on April 1 2022 in PubMed, EMBASE, Scopus, Cochrane, online textbooks, and specialty textbooks for expert reviews (e.g., review articles and book chapters), systematic reviews, or clinical practice guidelines published in the past 5 years without language restriction. Authors working in duplicate extracted definitions, management recommendations, and supportive evidence cited. RESULTS We identified 26 eligible articles, none of which described a systematic method to summarize the evidence or to develop and grade recommendations. Of these, 14 (54%) offered a definition of statin intolerance. A sequenced approach to management of statin intolerance was suggested in 24 (92%) articles describing 12 different approaches without supporting evidence of efficacy. Investigating for other causes was the most common first step. All authors suggested rechallenging after a washout period with either the same or other statin. Few considered nonlipid approaches to reducing ASCVD risk and none recommended involving patients in shared decision making. CONCLUSION We found substantial variability in the definition and management of statin intolerance among experts. Few focused on ASCVD risk reduction and none promoted the participation of patients in shared decision making about how to address the threat of ASCVD with or without statins.
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Affiliation(s)
| | - Camila Wenczenovicz
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | | | | | - Renzo Mogollon
- University of Nevada Reno, Internal Medicine Program, Reno, NV, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
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22
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Affiliation(s)
- Iona Heath
- London
- Mayo Clinic, Rochester, Minnesota, USA
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23
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Zisman-Ilani Y, Khaikin S, Savoy ML, Paranjape A, Rubin DJ, Jacob R, Wieringa TH, Suarez J, Liu J, Gardiner H, Bass SB, Montori VM, Siminoff LA. Disparities in Shared Decision-Making Research and Practice: The Case for Black American Patients. Ann Fam Med 2023; 21:112-118. [PMID: 36750357 PMCID: PMC10042565 DOI: 10.1370/afm.2943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 10/12/2022] [Accepted: 10/19/2022] [Indexed: 02/09/2023] Open
Abstract
OBJECTIVE The extent of shared decision making (SDM) use in the care of Black patients is limited. We explored preferences, needs, and challenges of Black patients to enhance SDM offerings. METHODS We performed interviews with 32 Black patients receiving type 2 diabetes care in safety-net primary care practices caring predominantly for Black people. RESULTS The following 4 themes emerged: preference for humanistic communication, need to account for the role of family in decision making, need for medical information sharing, and mistrust of clinicians. CONCLUSION Given the dearth of research on SDM among ethnic and racial minorities, this study offers patient-perspective recommendations to improve SDM offerings for Black patients in primary care settings. To enhance SDM with Black patients, acknowledgment of the importance of storytelling as a strategy, to place medical information in a context that makes it meaningful and memorable, is recommended. Triadic SDM, in which family members are centrally involved in decision making, is preferred over classical dyadic SDM. There is a need to reconsider the universalism assumption underlying contemporary SDM models and the relevancy of current SDM practices that were developed mostly without the feedback of participants of ethnic, racial, and cultural minorities.
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Affiliation(s)
- Yaara Zisman-Ilani
- College of Public Health, Temple University, Philadelphia, Pennsylvania.,Division of Psychology and Language Sciences, University College London, London, United Kingdom.,Shared Decision Making Laboratory, Temple University, Philadelphia, Pennsylvania
| | - Shely Khaikin
- Shared Decision Making Laboratory, Temple University, Philadelphia, Pennsylvania
| | - Margot L Savoy
- Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania.,American Academy of Family Physicians, Washington, DC
| | - Anuradha Paranjape
- Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania
| | - Daniel J Rubin
- Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania
| | - Regina Jacob
- Lewis Katz School of Medicine, Temple University, Philadelphia, Pennsylvania
| | - Thomas H Wieringa
- Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - John Suarez
- Shared Decision Making Laboratory, Temple University, Philadelphia, Pennsylvania
| | - Jin Liu
- Shared Decision Making Laboratory, Temple University, Philadelphia, Pennsylvania
| | - Heather Gardiner
- College of Public Health, Temple University, Philadelphia, Pennsylvania
| | | | | | - Laura A Siminoff
- College of Public Health, Temple University, Philadelphia, Pennsylvania
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24
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Affiliation(s)
- Marleen Kunneman
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
- Knowledge and Evaluation Research Unit, Mayo Clinic Rochester, Rochester, Minnesota, USA
| | - Ingeborg P M Griffioen
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
- Faculty of Industrial Design Engineering, Delft University of Technology, Delft, Zuid-Holland, The Netherlands
| | - Nanon H M Labrie
- Department of Language, Literature & Communication, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Maria Kristiansen
- Department of Public Health & Center for Healthy Aging, University of Copenhagen, Kobenhavn, Denmark
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic Rochester, Rochester, Minnesota, USA
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25
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Kunneman M, Branda ME, Ridgeway JL, Tiedje K, May CR, Linzer M, Inselman J, Buffington ALH, Coffey J, Boehm D, Deming J, Dick S, van Houten H, LeBlanc A, Liesinger J, Lima J, Nordeen J, Pencille L, Poplau S, Reed S, Vannelli A, Yost KJ, Ziegenfuss JY, Smith SA, Montori VM, Shah ND. Correction to: Making sense of diabetes medication decisions: a mixed methods cluster randomized trial using a conversation aid intervention. Endocrine 2023; 79:221-222. [PMID: 36357824 PMCID: PMC9813200 DOI: 10.1007/s12020-022-03240-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Affiliation(s)
- Marleen Kunneman
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Megan E Branda
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado-Denver Anschutz Medical Campus, Aurora, CO, USA
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Jennifer L Ridgeway
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Kristina Tiedje
- Laboratoire d'anthropologie des enjeux contemporains, Lyon, France
| | - Carl R May
- Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK
| | - Mark Linzer
- Department of Medicine, Hennepin Healthcare and University of Minnesota, Minneapolis, MN, USA
| | - Jonathan Inselman
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, MN, USA
| | - Angela L H Buffington
- Department of Psychiatry and Psychology, Mayo Clinic Health System, Mankato, MN, USA
- Department of Family Medicine and Community Health, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Jordan Coffey
- Practice-Based Research Network, Mayo Clinic, Rochester, MN, USA
- Center for Translational Science Activities, Mayo Clinic, Rochester, MN, USA
| | - Deborah Boehm
- Center for Patient and Provider Experience, Hennepin County Medical Center, Minneapolis, MN, USA
- School of Nursing, University of Minnesota, Minneapolis, MN, USA
- Decision Partners for Health, Richfield, MN, USA
| | - James Deming
- Mayo Clinic Health System Northwest Wisconsin, (dept) Home Health and Hospice, Eau Claire, WI, USA
| | - Sara Dick
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
| | - Holly van Houten
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Annie LeBlanc
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
- Department of Family and Emergency Medicine, Faculty of Medicine, Laval University, Quebec, QC, Canada
| | - Juliette Liesinger
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, MN, USA
| | - Janet Lima
- Park Nicollet International Diabetes Center, St. Louis Park, MN, USA
| | | | - Laurie Pencille
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
- Kern Center for the Science of Health Care Deliver, Mayo Clinic, Rochester, MN, USA
| | - Sara Poplau
- Office of Professional Worklife, Hennepin Healthcare, Minneapolis, MN, USA
| | - Steven Reed
- Department of Internal Medicine, Park Nicollet Clinic, Brooklyn Center, MN, USA
| | - Anna Vannelli
- Park Nicollet International Diabetes Center, St. Louis Park, MN, USA
| | - Kathleen J Yost
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Jeanette Y Ziegenfuss
- Division of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Center for Evaluation and Survey Research, HealthPartners Institute, Bloomington, IN, USA
| | - Steven A Smith
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
| | - Nilay D Shah
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
- Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, MN, USA.
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Golembiewski EH, Espinoza Suarez NR, Maraboto Escarria AP, Yang AX, Kunneman M, Hassett LC, Montori VM. Video-based observation research: A systematic review of studies in outpatient health care settings. Patient Educ Couns 2023; 106:42-67. [PMID: 36207219 DOI: 10.1016/j.pec.2022.09.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Revised: 09/13/2022] [Accepted: 09/30/2022] [Indexed: 06/16/2023]
Abstract
OBJECTIVE To examine the use of video-based observation research in outpatient health care encounter research. METHODS We conducted a systematic search of MEDLINE, Scopus, Cochrane and other databases from database inception to October 2020 for reports of studies that used video recording to investigate ambulatory patient-clinician interactions. Two authors independently reviewed all studies for eligibility and extracted information related to study setting and purpose, participant recruitment and consent processes, data collection procedures, method of analysis, and participant sample characteristics. RESULTS 175 articles were included. Most studies (65%) took place in a primary care or family practice setting. Study objectives were overwhelmingly focused on patient-clinician communication (81%). Reporting of key study elements was inconsistent across included studies. CONCLUSION Video recording has been used as a research method in outpatient health care in a limited number and scope of clinical contexts and research domains. In addition, reporting of study design, methodological characteristics, and ethical considerations needs improvement. PRACTICE IMPLICATIONS Video recording as a method has been relatively underutilized within many clinical and research contexts. This review will serve as a practical resource for health care researchers as they plan and execute future video-based studies.
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Affiliation(s)
| | - Nataly R Espinoza Suarez
- Knowledge and Evaluation Research (KER) Unit Mayo Clinic Rochester, MN, USA; Department of Family Medicine and Emergency Medicine Laval University Quebec, Canada.
| | - Andrea P Maraboto Escarria
- Knowledge and Evaluation Research (KER) Unit Mayo Clinic Rochester, MN, USA; Department of Obstetrics and Gynecology Hospital Angeles Lomas Mexico City, Mexico.
| | - Andrew X Yang
- Mayo Clinic Alix School of Medicine Rochester, MN, USA.
| | - Marleen Kunneman
- Knowledge and Evaluation Research (KER) Unit Mayo Clinic Rochester, MN, USA; Medical Decision Making, Department of Biomedical Data Sciences Leiden University Medical Center Leiden, the Netherlands.
| | - Leslie C Hassett
- Division of Endocrinology, Diabetes, Metabolism and Nutrition Department of Medicine Mayo Clinic, Rochester, MN, USA.
| | - Victor M Montori
- Knowledge and Evaluation Research (KER) Unit Mayo Clinic Rochester, MN, USA; Mayo Clinic Libraries Mayo Clinic, Rochester, MN, USA.
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Jones AE, McCarty MM, Cameron KA, Cavanaugh KL, Steinberg BA, Passman R, Kansal P, Guzman A, Chen E, Zhong L, Fagerlin A, Hargraves I, Montori VM, Brito JP, Noseworthy PA, Ozanne EM. Development of Complementary Encounter and Patient Decision Aids for Shared Decision Making about Stroke Prevention in Atrial Fibrillation. MDM Policy Pract 2023; 8:23814683231178033. [PMID: 38178866 PMCID: PMC10765759 DOI: 10.1177/23814683231178033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 04/06/2023] [Indexed: 01/06/2024] Open
Abstract
Introduction Decision aids (DAs) are helpful instruments used to support shared decision making (SDM). Patients with atrial fibrillation (AF) face complex decisions regarding stroke prevention strategies. While a few DAs have been made for AF stroke prevention, an encounter DA (EDA) and patient DA (PDA) have not been created to be used in conjunction with each other before. Design Using iterative user-centered design, we developed 2 DAs for anticoagulation choice and stroke prevention in AF. Prototypes were created, and we elicited feedback from patients and experts via observations of encounters, usability testing, and semistructured interviews. Results User testing was done with 33 experts (in AF and SDM) and 51 patients from 6 institutions. The EDA and PDA underwent 1 and 4 major iterations, respectively. Major differences between the DAs included AF pathophysiology and a preparation to meet with the clinician in the PDA as well as different language throughout. Content areas included personalized stroke risk, differences between anticoagulants, and risks of bleeding. Based on user feedback, developers 1) addressed feelings of isolation with AF, 2) improved navigation options, 3) modified content and flow for users new to AF and those experienced with AF, 4) updated stroke risk pictographs, and 5) added structure to the preparation for decision making in the PDA. Limitations These DAs focus only on anticoagulation for stroke prevention and are online, which may limit participation for those less comfortable with technology. Conclusions Designing complementary DAs for use in tandem or separately is a new method to support SDM between patients and clinicians. Extensive user testing is essential to creating high-quality tools that best meet the needs of those using them. Highlights First-time complementary encounter and patient decision aids have been designed to work together or separately.User feedback led to greater structure and different experiences for patients naïve or experienced with anticoagulants in patient decision aids.Online tools allow for easier dissemination, use in telehealth visits, and updating as new evidence comes out.
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Affiliation(s)
- Aubrey E. Jones
- College of Pharmacy, Department of Pharmacotherapy, University of Utah, Salt Lake City, UT, USA
| | - Madeleine M. McCarty
- School of Medicine, Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Kenzie A. Cameron
- Feinberg School of Medicine, Department of Medicine, Division of General Internal Medicine and Geriatrics, Northwestern University, Chicago, IL, USA
| | - Kerri L. Cavanaugh
- Department of Medicine, Division of Nephrology and Hypertension, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Benjamin A. Steinberg
- School of Medicine, Division of Cardiovascular Medicine, University of Utah, Salt Lake City, UT, USA
| | - Rod Passman
- Feinberg School of Medicine, Department of Medicine, Division of Cardiology, Northwestern University, Chicago, IL, USA
| | - Preeti Kansal
- Feinberg School of Medicine, Department of Medicine, Division of Cardiology, Northwestern University, Chicago, IL, USA
| | - Adriana Guzman
- Feinberg School of Medicine, Department of Medicine, Division of General Internal Medicine and Geriatrics, Northwestern University, Chicago, IL, USA
| | - Emily Chen
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Lingzi Zhong
- School of Medicine, Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Angela Fagerlin
- School of Medicine, Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
- Salt Lake City VA Informatics Decision-Enhancement and Analytic Sciences (IDEAS) Center for Innovation, Salt Lake City, UT, USA
| | - Ian Hargraves
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Victor M. Montori
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Juan P. Brito
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | | | - Elissa M. Ozanne
- School of Medicine, Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
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Spencer-Bonilla G, Branda ME, Kunneman M, Bellolio F, Burnett B, Guyatt G, Montori VM. Encounter-based randomization did not result in contamination in a shared decision-making trial: a secondary analysis. J Clin Epidemiol 2022; 152:185-192. [PMID: 36220625 DOI: 10.1016/j.jclinepi.2022.09.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 09/07/2022] [Accepted: 09/30/2022] [Indexed: 11/18/2022]
Abstract
OBJECTIVES To estimate the level of contamination in an encounter-randomized trial evaluating a shared decision-making (SDM) tool. STUDY DESIGN AND SETTING We assessed contamination at three levels: (1) tool contamination (whether the tool was physically present in the usual care encounter), (2) functional contamination (whether components of the SDM tool were recreated in the usual care encounters without directly accessing the tool), and (3) learned contamination (whether clinicians "got better at SDM" in the usual care encounters as assessed by the OPTION-12 score). For functional and learned contamination, the interaction with the number of exposures to the tool was assessed. RESULTS We recorded and analyzed 830 of 922 randomized encounters. Of the 411 recorded encounters randomized to usual care, the SDM tool was used in nine (2.2%) encounters. Clinicians discussed at least one patient-important issue in 377 usual care encounters (92%) and the risk of stroke in 214 encounters (52%). We found no significant interaction between number of times the SDM tool was used and subsequent functional or learned contamination. CONCLUSION Despite randomly assigning clinicians to use an SDM tool in some and not other encounters, we found no evidence of contamination in usual care encounters.
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Affiliation(s)
- Gabriela Spencer-Bonilla
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA; Department of Medicine, Stanford University, Stanford, CA, USA
| | - Megan E Branda
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA; Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Marleen Kunneman
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA; Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Fernanda Bellolio
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA; Department of Emergency Medicine, Mayo Clinic, Rochester, MN, USA
| | - Bruce Burnett
- Thrombosis Clinic and Anticoagulation Services, Park Nicollet Health Services, St Louis Park, MN, USA
| | - Gordon Guyatt
- Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA.
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Montori VM, Ruissen MM, Branda ME, Hargraves IG, Kunneman M. Problem-based shared decision making: The role of canonical SDM steps. Health Expect 2022; 26:282-289. [PMID: 36448245 PMCID: PMC9854321 DOI: 10.1111/hex.13654] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 10/07/2022] [Accepted: 10/25/2022] [Indexed: 12/03/2022] Open
Abstract
OBJECTIVE To evaluate the extent to which the canonical steps of shared decision making (SDM) take place in clinical encounters in practice and across SDM forms. METHODS We assessed 100 randomly selected video-recorded primary care encounters, obtained as part of a randomized trial of an SDM intervention in patients with type 2 diabetes. Two coders, working independently, noted each instance of SDM, classified it as one of four problem-based forms to SDM (weighing alternatives, negotiating conflicting issues, solving problems, or developing existential insight), and noted the occurrence and timing of each of the four canonical SDM steps: fostering choice awareness, providing information, stating preferences, and deciding. Descriptive analyses sought to determine the relative frequency of these steps across each of the four SDM forms within each encounter. RESULTS There were 485 SDM steps noted (mean 4.85 steps per encounter), of which providing information and stating preferences were the most common. There were 2.7 (38 steps in 14 encounters) steps per encounter observed in encounters with no discernible SDM form, 3.4 (105 steps in 31 encounters) with one SDM form, 5.2 (129 steps in 25 encounters) with two SDM forms, and 7.1 (213 steps in 30 encounters) when ≥3 SDM forms were observed within the encounter. The prescribed order of the four SDM steps was observed in, at best, 16 of the 100 encounters. Stating preferences was a common step when weighing alternatives (38%) or negotiating conflicts (59.3%) but less common when solving problems (29.2%). The distribution of SDM steps was similar to usual care with or without the SDM intervention. CONCLUSION The normative steps of SDM are infrequently observed in their prescribed order regardless of whether an SDM intervention was used. Some steps are more likely in some SDM forms but no pattern of steps appears to distinguish among SDM forms. CLINICAL TRIAL REGISTRATION ClinicalTrial.gov: NCT01293578.
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Affiliation(s)
- Victor M. Montori
- Knowledge and Evaluation Research UnitMayo Clinic RochesterRochesterMinnesotaUSA
| | - Merel M. Ruissen
- Knowledge and Evaluation Research UnitMayo Clinic RochesterRochesterMinnesotaUSA,Department of Medicine, Division of EndocrinologyLeiden University Medical CenterLeidenZuid‐HollandThe Netherlands,Department of Biomedical Data Sciences, Section of Medical Decision MakingLeiden University Medical CenterLeidenThe Netherlands
| | - Megan E. Branda
- Knowledge and Evaluation Research UnitMayo Clinic RochesterRochesterMinnesotaUSA,Department of Quantitative Health Sciences, Division of Clinical Trials and BiostatisticsMayo ClinicRochesterMinnesotaUSA
| | - Ian G. Hargraves
- Knowledge and Evaluation Research UnitMayo Clinic RochesterRochesterMinnesotaUSA
| | - Marleen Kunneman
- Knowledge and Evaluation Research UnitMayo Clinic RochesterRochesterMinnesotaUSA,Department of Biomedical Data Sciences, Section of Medical Decision MakingLeiden University Medical CenterLeidenThe Netherlands
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Hartasanchez SA, Hargraves IG, Clark JE, Gravholt D, Brito JP, Branda ME, Gomez YL, Nautiyal V, Khurana CS, Thomas RJ, Montori VM, Ridgeway JL. The design and development of an encounter tool to support shared decision making about preventing cardiovascular events. Prev Med Rep 2022; 30:101994. [PMID: 36203943 PMCID: PMC9530931 DOI: 10.1016/j.pmedr.2022.101994] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 08/08/2022] [Accepted: 09/17/2022] [Indexed: 12/31/2022] Open
Abstract
Patients at high risk for cardiovascular disease (CVD) tend to receive less intensive preventive care. Clinical practice guidelines recommend shared decision making (SDM) to improve the quality of primary CVD prevention. There are tools for use during the clinical encounter that promote SDM, but, to our knowledge, there are no SDM encounter tools that support conversations about available lifestyle and pharmacological options that can lead to preventive care that is congruent with patient goals and CVD risk. Using the best available evidence and human-centered design (iterative design in the context of ultimate use with users), our team developed a SDM encounter tool, CV Prevention Choice. Each subsequent version during the iterative development process was evaluated in terms of content, usefulness, and usability by testing it in real preventive encounters. The final version of the tool includes a calculator that estimates the patient's risk of a major atherosclerotic CVD event in the next 10 years. Lifestyle and medication options are presented, alongside their pros, cons, costs, and other burdens. The risk reduction achieved by the selected prevention program is then displayed to support collaborative deliberation and decision making. A U.S. multicenter trial is estimating the effectiveness of CV Prevention Choice in achieving risk-concordant CV prevention while identifying the best strategies for increasing the adoption of the SDM encounter tool and its routine use in practice.
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Affiliation(s)
- Sandra A. Hartasanchez
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Ian G. Hargraves
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Jennifer E. Clark
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Derek Gravholt
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Juan P. Brito
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Megan E. Branda
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA,Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Yvonne L. Gomez
- Altru Health System, 1380 S. Columbia Road, Grand Forks, ND 58206, USA
| | - Vivek Nautiyal
- Wellstar Center for Cardiovascular Care, 55 Whitcher Street, NE, Suite 350, Marietta, GA 30060, USA
| | - Charanjit S. Khurana
- Virginia Hospital Center Physician Group-Cardiology, 1715 North George Mason Drive, Arlington, VA 22205, USA
| | - Randal J. Thomas
- Division of Preventive Cardiology, Department of Cardiovascular Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Victor M. Montori
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Jennifer L. Ridgeway
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA,Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA,Corresponding author at: 200 First Street SW, Rochester, MN 55905, USA.
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Rachmasari K, Montori VM. In type 2 diabetes, SGLT2 inhibitors reduced risk for serious hyperkalemia without increasing hypokalemia. Ann Intern Med 2022; 175:JC104. [PMID: 36063558 DOI: 10.7326/j22-0063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Neuen BL, Oshima M, Agarwal R, et al. Sodium-glucose cotransporter 2 inhibitors and risk of hyperkalemia in people with type 2 diabetes: a meta-analysis of individual participant data from randomized, controlled trials. Circulation. 2022;145:1460-70. 35394821.
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Sohn S, Moon S, Prokop LJ, Montori VM, Fan JW. A scoping review of medical practice variation research within the informatics literature. Int J Med Inform 2022; 165:104833. [PMID: 35868231 PMCID: PMC10103076 DOI: 10.1016/j.ijmedinf.2022.104833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Revised: 04/16/2022] [Accepted: 07/11/2022] [Indexed: 10/17/2022]
Abstract
RATIONALE We performed a scoping review of informatics core literature about medical practice variation (MPV) as an agile summary of the subject in our field. MATERIALS AND METHODS The Ovid integrated database was searched between 1946 and 2022 to identify MPV studies published in major informatics journals and conference proceedings. Two reviewers performed relevance screening, with assistance from another independent reviewer for adjudication. The included articles were then thematically analyzed and summarized through discussion among all three reviewers. RESULTS A total of 43 articles were included and went through the thematic analysis. About half (n = 21) of the included articles were published in conference proceedings. Five articles reported the effect of MPV on patient outcomes. The variation of interest was most frequently in treatment decisions. In terms of the role informatics played (multiple roles allowed), 39 (90.7%) articles pertained to detection of MPV, 5 were about prevention of MPV and 4 about learning from MPV. DISCUSSION MPV remains a critical issue in health care, yet most informatics research has been focused on simple tasks such as automating the detection of MPV and assessing compliance to decision-support systems, and less focused on addressing the causes of variation or supporting learning from variation. CONCLUSION Our scoping review found that informatics studies have focused on detecting of MPV, especially variability in treatments and deviation from practice guidelines. Technological advances should promote more informatics research focused on explaining and learning from MPV.
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Affiliation(s)
- Sunghwan Sohn
- Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States
| | - Sungrim Moon
- Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States
| | - Larry J Prokop
- Mayo Clinic Libraries, Mayo Clinic, Rochester, MN, United States
| | - Victor M Montori
- Department of Internal Medicine, Mayo Clinic, Rochester, MN, United States; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States
| | - J Wilfred Fan
- Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States; Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, United States.
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Sivly A, Gorr HS, Gravholt D, Branda ME, Linzer M, Noseworthy P, Hargraves I, Kunneman M, Doubeni CA, Suzuki T, Brito JP, Jackson EA, Burnett B, Wambua M, Montori VM. Enrolling people of color to evaluate a practice intervention: lessons from the shared decision-making for atrial fibrillation (SDM4AFib) trial. BMC Health Serv Res 2022; 22:1032. [PMID: 35962351 PMCID: PMC9375357 DOI: 10.1186/s12913-022-08399-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 06/29/2022] [Indexed: 11/10/2022] Open
Abstract
Background Trial recruitment of Black, indigenous, and people of color (BIPOC) is key for interventions that interact with socioeconomic factors and cultural norms, preferences, and values. We report on our experience enrolling BIPOC participants into a multicenter trial of a shared decision-making intervention about anticoagulation to prevent strokes, in patients with atrial fibrillation (AF). Methods We enrolled patients with AF and their clinicians in 5 healthcare systems (three academic medical centers, an urban/suburban community medical center, and a safety-net inner-city medical center) located in three states (Minnesota, Alabama, and Mississippi) in the United States. Clinical encounters were randomized to usual care with or without a shared decision-making tool about anticoagulation. Analysis We analyzed BIPOC patient enrollment by site, categorized reasons for non-enrollment, and examined how enrollment of BIPOC patients was promoted across sites. Results Of 2247 patients assessed, 922 were enrolled of which 147 (16%) were BIPOC patients. Eligible Black participants were significantly less likely (p < .001) to enroll (102, 11%) than trial-eligible White participants (185, 15%). The enrollment rate of BIPOC patients varied by site. The inclusion and prioritization of clinical practices that care for more BIPOC patients contributed to a higher enrollment rate into the trial. Specific efforts to reach BIPOC clinic attendees and prioritize their enrollment had lower yield. Conclusions Best practices to optimize the enrollment of BIPOC participants into trials that examined complex and culturally sensitive interventions remain to be developed. This study suggests a high yield from enrolling BIPOC patients from practices that prioritize their care. Trial registration ClinicalTrials.gov (NCT02905032). Supplementary Information The online version contains supplementary material available at 10.1186/s12913-022-08399-z.
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Affiliation(s)
- Angela Sivly
- Knowledge and Evaluation Research Unit, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Haeshik S Gorr
- Hennepin Healthcare, 730 South 8th Street, Minneapolis, MN, 55415, USA
| | - Derek Gravholt
- Knowledge and Evaluation Research Unit, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Megan E Branda
- Knowledge and Evaluation Research Unit, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.,Department of Quantitative Health Sciences, Division of Clinical Trials & Biostatistics, Mayo Clinic, Rochester, MN, 55905, USA
| | - Mark Linzer
- Hennepin Healthcare, 730 South 8th Street, Minneapolis, MN, 55415, USA
| | - Peter Noseworthy
- Knowledge and Evaluation Research Unit, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.,Cardiovascular Diseases, Mayo Clinic, Rochester, MN, 55905, USA
| | - Ian Hargraves
- Knowledge and Evaluation Research Unit, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Marleen Kunneman
- Knowledge and Evaluation Research Unit, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.,Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Chyke A Doubeni
- Mayo Clinic Center for Health Equity and Community Engagement Research, Mayo Clinic, Rochester, MN, 55905, USA
| | - Takeki Suzuki
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | - Juan P Brito
- Knowledge and Evaluation Research Unit, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA
| | - Elizabeth A Jackson
- Division of Cardiovascular Disease, University of Alabama at Birmingham, Birmingham, AL, 32594, USA
| | - Bruce Burnett
- Health Partners, Park Nicollet, 8170 33rd Ave S, Bloomington, MN, 55425, USA
| | - Mike Wambua
- Hennepin Healthcare, 730 South 8th Street, Minneapolis, MN, 55415, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
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Montori VM. Patients surviving COVID-19 had increased risk for incident diabetes vs. persons without COVID-19. Ann Intern Med 2022; 175:JC93. [PMID: 35914265 DOI: 10.7326/j22-0052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Xie Y, Al-Aly Z. Risks and burdens of incident diabetes in long COVID: a cohort study. Lancet Diabetes Endocrinol. 2022;10:311-21. 35325624.
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36
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Hartasanchez SA, Grande SW, Montori VM, Kunneman M, Brito JP, McCarthy S, Hargraves IG. Shared decision making process measures and patient problems. Patient Educ Couns 2022; 105:2457-2465. [PMID: 34802881 PMCID: PMC9079183 DOI: 10.1016/j.pec.2021.11.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 10/26/2021] [Accepted: 11/02/2021] [Indexed: 06/13/2023]
Abstract
OBJECTIVES Purposeful SDM posits four modes of shared decision making (SDM). The use of each mode depends on the type of problem of care that is being addressed. We sought to identify how current observer-based SDM measures apply to each mode of Purposeful SDM. METHODS Four coders, working independently, evaluated 192 items pertaining to 12 observer-based SDM process measures. They classified the items into 6 themes that vary across Purposeful SDM modes and then into one of the four modes (weighing, negotiating, problem-solving, developing insight). Disagreements were resolved by consensus. RESULTS The items were classified as pertaining to the following themes: problem (28), roles/participation (84), options (62), preferences (21), decision (15), and evaluation (6). They were then classified as pertaining particularly to the SDM modes of weighing (54), negotiating (5), problem-solving (0), and developing insight (0) modes, with 191 items applying broadly to all modes of Purposeful SDM. CONCLUSIONS Observer-based SDM measures describe behaviors pertinent to all modes but lack items sensitive to behaviors particular to some modes of SDM. PRACTICE IMPLICATIONS New or revised observer-based measures of the SDM process could help estimate the extent to which the appropriate SDM mode is being used to address the patient's problem.
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Affiliation(s)
- Sandra A Hartasanchez
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Stuart W Grande
- Division of Health Policy and Management, School of Public Health, University of Minnesota, MN, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Marleen Kunneman
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA; Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Juan P Brito
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Sarah McCarthy
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Ian G Hargraves
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
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McCarthy SR, Golembiewski EH, Gravholt DL, Clark JE, Clark J, Fischer C, Mulholland H, Babcock K, Montori VM, Jones A. Documentation of Psychosocial Distress and Its Antecedents in Children with Rare or Life-Limiting Chronic Conditions. Children 2022; 9:children9050664. [PMID: 35626841 PMCID: PMC9139272 DOI: 10.3390/children9050664] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 04/21/2022] [Accepted: 04/29/2022] [Indexed: 11/16/2022]
Abstract
Children with rare or life-limiting chronic conditions and their families are at high risk of psychosocial distress. However, despite its impact on patient and family health and functioning, psychosocial distress and its antecedents may not routinely be captured in medical records. The purpose of this study was to characterize current medical record documentation practices around psychosocial distress among children with rare or life-limiting chronic conditions and their families. Medical records for patients with rare or life-limiting chronic conditions (n = 60) followed by a pediatric complex care program were reviewed. Study team members extracted both structured data elements (e.g., diagnoses, demographic information) and note narratives from the most recent visit with a clinician in the program. Psychosocial topics were analyzed using a mixed quantitative (i.e., frequency counts of topics) and qualitative approach. Topics related to psychosocial distress that were documented in notes included child and parent emotional problems, parent social support, sibling emotional or physical problems, family structure (e.g., whether parents were together), and financial concerns. However, 35% of notes lacked any mention of psychosocial concerns. Although examples of psychosocial concerns were included in some notes, none were present in over one-third of this sample. For both patients with rare or life-limiting chronic conditions and their caregivers, more active elicitation and standard documentation of psychosocial concerns may improve the ability of healthcare providers to identify and intervene on psychosocial concerns and their risk factors.
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Affiliation(s)
- Sarah R. McCarthy
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905, USA
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN 55905, USA; (E.H.G.); (D.L.G.); (V.M.M.)
- Correspondence: ; Tel.: +1-507-284-2933
| | - Elizabeth H. Golembiewski
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN 55905, USA; (E.H.G.); (D.L.G.); (V.M.M.)
| | - Derek L. Gravholt
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN 55905, USA; (E.H.G.); (D.L.G.); (V.M.M.)
| | - Jennifer E. Clark
- Department of Endocrinology, Diabetes, and Metabolism, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN 55905, USA;
| | - Jeannie Clark
- Mayo Clinic Children’s Center, Mayo Clinic, Rochester, MN 55905, USA; (J.C.); (C.F.)
| | - Caree Fischer
- Mayo Clinic Children’s Center, Mayo Clinic, Rochester, MN 55905, USA; (J.C.); (C.F.)
| | - Hannah Mulholland
- Section of Social Work, Mayo Clinic, Rochester, MN 55905, USA; (H.M.); (K.B.)
| | - Kristina Babcock
- Section of Social Work, Mayo Clinic, Rochester, MN 55905, USA; (H.M.); (K.B.)
| | - Victor M. Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN 55905, USA; (E.H.G.); (D.L.G.); (V.M.M.)
- Department of Endocrinology, Diabetes, and Metabolism, Mayo Clinic College of Medicine and Science, Mayo Clinic, Rochester, MN 55905, USA;
| | - Amie Jones
- Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN 55905, USA;
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Klonoff DC, Buckingham B, Christiansen JS, Montori VM, Tamborlane WV, Vigersky RA, Wolpert H. Withdrawn as duplicate: Corrigendum to: Continuous Glucose Monitoring: An Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab 2022; 107:e2220. [PMID: 34878114 DOI: 10.1210/clinem/dgab251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Indexed: 11/19/2022]
Abstract
This corrigendum has been withdrawn due to a publisher error that caused it to be duplicated. The definitive version of this corrigendum is published under DOI https://doi.org/10.1210/clinem/dgab250.
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Tilburt JC, Zahrieh D, Pacyna JE, Petereit DG, Kaur JS, Rapkin BD, Grubb RL, Chang GJ, Morris MJ, Kovac EZ, Babaian KN, Sloan JA, Basch EM, Peil ES, Dueck AC, Novotny PJ, Paskett ED, Buckner JC, Joyce DD, Montori VM, Frosch DL, Volk RJ, Kim SP. Decision aids for localized prostate cancer in diverse minority men: Primary outcome results from a multicenter cancer care delivery trial (Alliance A191402CD). Cancer 2022; 128:1242-1251. [PMID: 34890060 PMCID: PMC8882149 DOI: 10.1002/cncr.34062] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 10/14/2021] [Accepted: 11/03/2021] [Indexed: 12/14/2022]
Abstract
BACKGROUND Decision aids (DAs) can improve knowledge for prostate cancer treatment. However, the relative effects of DAs delivered within the clinical encounter and in more diverse patient populations are unknown. A multicenter cluster randomized controlled trial with a 2×2 factorial design was performed to test the effectiveness of within-visit and previsit DAs for localized prostate cancer, and minority men were oversampled. METHODS The interventions were delivered in urology practices affiliated with the NCI Community Oncology Research Program Alliance Research Base. The primary outcome was prostate cancer knowledge (percent correct on a 12-item measure) assessed immediately after a urology consultation. RESULTS Four sites administered the previsit DA (39 patients), 4 sites administered the within-visit DA (44 patients), 3 sites administered both previsit and within-visit DAs (25 patients), and 4 sites provided usual care (50 patients). The median percent correct in prostate cancer knowledge, based on the postvisit knowledge assessment after the intervention delivery, was as follows: 75% for the pre+within-visit DA study arm, 67% for the previsit DA only arm, 58% for the within-visit DA only arm, and 58% for the usual-care arm. Neither the previsit DA nor the within-visit DA had a significant impact on patient knowledge of prostate cancer treatments at the prespecified 2.5% significance level (P = .132 and P = .977, respectively). CONCLUSIONS DAs for localized prostate cancer treatment provided at 2 different points in the care continuum in a trial that oversampled minority men did not confer measurable gains in prostate cancer knowledge.
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Affiliation(s)
- Jon C Tilburt
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, Minnesota.,Division of General Internal Medicine, Mayo Clinic, Scottsdale, Arizona.,Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota
| | - David Zahrieh
- Alliance Statistics and Data Center, Mayo Clinic, Rochester, Minnesota
| | - Joel E Pacyna
- Biomedical Ethics Research Program, Mayo Clinic, Rochester, Minnesota
| | - Daniel G Petereit
- Rapid City Regional Cancer Care Institute, Monument Health, Rapid City, South Dakota
| | - Judith S Kaur
- Department of Hematology and Oncology, Mayo Clinic, Jacksonville, Florida
| | - Bruce D Rapkin
- Department of Epidemiology and Population Health, Division of Community Collaboration and Implementation Science, Albert Einstein College of Medicine, Bronx, New York
| | - Robert L Grubb
- Department of Urology, Medical University of South Carolina, Charleston, South Carolina
| | - George J Chang
- Department of Colon and Rectal Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Michael J Morris
- Genitourinary Oncology Service, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Evan Z Kovac
- Department of Urology, Rutgers New Jersey Medical School, Newark, New Jersey
| | - Kara N Babaian
- Department of Surgery, Southern Illinois University, Springfield, Illinois
| | - Jeff A Sloan
- Alliance Statistics and Data Center, Mayo Clinic, Rochester, Minnesota
| | - Ethan M Basch
- Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina
| | - Elizabeth S Peil
- Alliance Statistics and Data Center, Mayo Clinic, Rochester, Minnesota
| | - Amylou C Dueck
- Alliance Statistics and Data Center, Mayo Clinic, Scottsdale, Arizona
| | - Paul J Novotny
- Alliance Statistics and Data Center, Mayo Clinic, Rochester, Minnesota
| | - Electra D Paskett
- Ohio State University College of Medicine, The Ohio State University, Columbus, Ohio
| | - Jan C Buckner
- Department of Oncology, Mayo Clinic, Rochester, Minnesota
| | - Daniel D Joyce
- Department of Urology, Mayo Clinic, Rochester, Minnesota
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota
| | - Dominick L Frosch
- Palo Alto Medical Foundation Research Institute, Palo Alto, California
| | - Robert J Volk
- Division of Cancer Prevention and Population Sciences, Department of Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Simon P Kim
- Division of Urology, Anschutz Medical Center, University of Colorado, Aurora, Colorado
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Boehmer KR, Gallacher KI, Lippiett KA, Mair FS, May CR, Montori VM. Minimally Disruptive Medicine: Progress 10 Years Later. Mayo Clin Proc 2022; 97:210-220. [PMID: 35120690 DOI: 10.1016/j.mayocp.2021.09.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 09/03/2021] [Accepted: 09/13/2021] [Indexed: 12/17/2022]
Affiliation(s)
- Kasey R Boehmer
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA; Division of Health Care Delivery Research, Mayo Clinic, Rochester, MN, USA.
| | - Katie I Gallacher
- General Practice and Primary Care, University of Glasgow, Glasgow, UK
| | - Kate A Lippiett
- Macmillan Survivorship Research Group, University of Southampton, Southampton, UK
| | - Frances S Mair
- General Practice and Primary Care, University of Glasgow, Glasgow, UK
| | - Carl R May
- Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
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Kunneman M, Branda ME, Ridgeway JL, Tiedje K, May CR, Linzer M, Inselman J, Buffington ALH, Coffey J, Boehm D, Deming J, Dick S, van Houten H, LeBlanc A, Liesinger J, Lima J, Nordeen J, Pencille L, Poplau S, Reed S, Vannelli A, Yost KJ, Ziegenfuss JY, Smith SA, Montori VM, Shah ND. Making sense of diabetes medication decisions: a mixed methods cluster randomized trial using a conversation aid intervention. Endocrine 2022; 75:377-391. [PMID: 34499328 PMCID: PMC8428215 DOI: 10.1007/s12020-021-02861-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 08/27/2021] [Indexed: 12/11/2022]
Abstract
PURPOSE To determine the effectiveness of a shared decision-making (SDM) tool versus guideline-informed usual care in translating evidence into primary care, and to explore how use of the tool changed patient perspectives about diabetes medication decision making. METHODS In this mixed methods multicenter cluster randomized trial, we included patients with type 2 diabetes mellitus and their primary care clinicians. We compared usual care with or without a within-encounter SDM conversation aid. We assessed participant-reported decisions made and quality of SDM (knowledge, satisfaction, and decisional conflict), clinical outcomes, adherence, and observer-based patient involvement in decision-making (OPTION12-scale). We used semi-structured interviews with patients to understand their perspectives. RESULTS We enrolled 350 patients and 99 clinicians from 20 practices and interviewed 26 patients. Use of the conversation aid increased post-encounter patient knowledge (correct answers, 52% vs. 45%, p = 0.02) and clinician involvement of patients (Mean between-arm difference in OPTION12, 7.3 (95% CI 3, 12); p = 0.003). There were no between-arm differences in treatment choice, patient or clinician satisfaction, encounter length, medication adherence, or glycemic control. Qualitative analyses highlighted differences in how clinicians involved patients in decision making, with intervention patients noting how clinicians guided them through conversations using factors important to them. CONCLUSIONS Using an SDM conversation aid improved patient knowledge and involvement in SDM without impacting treatment choice, encounter length, medication adherence or improved diabetes control in patients with type 2 diabetes. Future interventions may need to focus specifically on patients with signs of poor treatment fit. CLINICAL TRIAL REGISTRATION ClinicalTrial.gov: NCT01502891.
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Affiliation(s)
- Marleen Kunneman
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Megan E Branda
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
- Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado-Denver Anschutz Medical Campus, Aurora, CO, USA
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Jennifer L Ridgeway
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Kristina Tiedje
- Laboratoire d'anthropologie des enjeux contemporains, Lyon, France
| | - Carl R May
- Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK
| | - Mark Linzer
- Department of Medicine, Hennepin Healthcare and University of Minnesota, Minneapolis, MN, USA
| | - Jonathan Inselman
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, MN, USA
| | - Angela L H Buffington
- Department of Psychiatry and Psychology, Mayo Clinic Health System, Mankato, MN, USA
- Department of Family Medicine and Community Health, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Jordan Coffey
- Practice-Based Research Network, Mayo Clinic, Rochester, MN, US
- Center for Translational Science Activities, Mayo Clinic, Rochester, MN, USA
| | - Deborah Boehm
- Center for Patient and Provider Experience, Hennepin County Medical Center, Minneapolis, MN, USA
- School of Nursing, University of Minnesota, Minneapolis, MN, USA
- Decision Partners for Health, Richfield, MN, USA
| | - James Deming
- Mayo Clinic Health System Northwest Wisconsin, (dept) Home Health and Hospice, Eau Claire, WI, USA
| | - Sara Dick
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
| | - Holly van Houten
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Annie LeBlanc
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
- Department of Family and Emergency Medicine, Faculty of Medicine, Laval University, Quebec, QC, Canada
| | - Juliette Liesinger
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, MN, USA
| | - Janet Lima
- Park Nicollet International Diabetes Center, St. Louis Park, MN, USA
| | | | - Laurie Pencille
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
- Kern Center for the Science of Health Care Deliver, Mayo Clinic, Rochester, MN, USA
| | - Sara Poplau
- Office of Professional Worklife, Hennepin Healthcare, Minneapolis, MN, USA
| | - Steven Reed
- Department of Internal Medicine, Park Nicollet Clinic, Brooklyn Center, MN, USA
| | - Anna Vannelli
- Park Nicollet International Diabetes Center, St. Louis Park, MN, USA
| | - Kathleen J Yost
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Jeanette Y Ziegenfuss
- Division of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
- Center for Evaluation and Survey Research, HealthPartners Institute, Bloomington, USA
| | - Steven A Smith
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Division of Endocrinology, Diabetes, Metabolism, and Nutrition, Mayo Clinic, Rochester, MN, USA
| | - Nilay D Shah
- Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
- Mayo Clinic Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Rochester, MN, USA.
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Hartasanchez SA, Heen AF, Kunneman M, García-Bautista A, Hargraves IG, Prokop LJ, May CR, Montori VM. Remote shared decision making through telemedicine: A systematic review of the literature. Patient Educ Couns 2022; 105:356-365. [PMID: 34147314 DOI: 10.1016/j.pec.2021.06.012] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Revised: 06/02/2021] [Accepted: 06/09/2021] [Indexed: 06/12/2023]
Abstract
OBJECTIVES To assess the extent to which shared decision making (SDM) can take place in telemedicine (remote SDM). METHODS We searched Medline, Cochrane, and Scopus from 2010 until August 7th, 2020 for articles on remote SDM in the care of any patient using any technology. We also conducted a search for telemedicine articles citing key reports on SDM outcome measures. Two reviewers independently screened titles and abstracts, reviewed full text eligible studies, and synthesized their content using thematic analysis. RESULTS Of the 12 eligible articles, most were European with patients with chronic disease or mental and behavioral health. 8 articles used synchronous remote SDM and 1 used asynchronous remote SDM. Themes related to interactional workability of both telemedicine technologies and SDM emerged, namely access to broadband, digital literacy, and satisfaction with the convenience of remote visits. CONCLUSIONS Telemedicine technologies may foster virtual interactions that support remote SDM, which, in turn, may promote productive patient-clinician interactions and patient-centered care. PRACTICE IMPLICATIONS Digitally-mediated consultations surged amidst the COVID-19 pandemic. The extent to which SDM frameworks developed for in-person use need any adaptation for remote SDM remains unclear. Investment in innovation, design, implementation, and effectiveness research to advance remote SDM are needed.
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Affiliation(s)
- Sandra A Hartasanchez
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Anja Fog Heen
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA; Department of Medicine, Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Marleen Kunneman
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA; Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | - Andrea García-Bautista
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | - Ian G Hargraves
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
| | | | - Carl R May
- Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA.
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Noseworthy PA, Branda ME, Kunneman M, Hargraves IG, Sivly AL, Brito JP, Burnett B, Zeballos-Palacios C, Linzer M, Suzuki T, Lee AT, Gorr H, Jackson EA, Hess E, Brand-McCarthy SR, Shah ND, Montori VM. Effect of Shared Decision-Making for Stroke Prevention on Treatment Adherence and Safety Outcomes in Patients With Atrial Fibrillation: A Randomized Clinical Trial. J Am Heart Assoc 2022; 11:e023048. [PMID: 35023356 PMCID: PMC9238511 DOI: 10.1161/jaha.121.023048] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Background Guidelines promote shared decision-making (SDM) for anticoagulation in patients with atrial fibrillation. We recently showed that adding a within-encounter SDM tool to usual care (UC) increases patient involvement in decision-making and clinician satisfaction, without affecting encounter length. We aimed to estimate the extent to which use of an SDM tool changed adherence to the decided care plan and clinical safety end points. Methods and Results We conducted a multicenter, encounter-level, randomized trial assessing the efficacy of UC with versus without an SDM conversation tool for use during the clinical encounter (Anticoagulation Choice) in patients with nonvalvular atrial fibrillation considering starting or reviewing anticoagulation treatment. We conducted a chart and pharmacy review, blinded to randomization status, at 10 months after enrollment to assess primary adherence (proportion of patients who were prescribed an anticoagulant who filled their first prescription) and secondary adherence (estimated using the proportion of days for which treatment was supplied and filled for direct oral anticoagulant, and as time in therapeutic range for warfarin). We also noted any strokes, transient ischemic attacks, major bleeding, or deaths as safety end points. We enrolled 922 evaluable patient encounters (Anticoagulation Choice=463, and UC=459), of which 814 (88%) had pharmacy and clinical follow-up. We found no differences between arms in either primary adherence (78% of patients in the SDM arm filled their first prescription versus 81% in UC arm) or secondary adherence to anticoagulation (percentage days covered of the direct oral anticoagulant was 74.1% in SDM versus 71.6% in UC; time in therapeutic range for warfarin was 66.6% in SDM versus 64.4% in UC). Safety outcomes, mostly bleeds, occurred in 13% of participants in the SDM arm and 14% in the UC arm. Conclusions In this large, randomized trial comparing UC with a tool to promote SDM against UC alone, we found no significant differences between arms in primary or secondary adherence to anticoagulation or in clinical safety outcomes. Registration URL: https://www.clinicaltrials.gov; Unique identifier: clinicaltrials.gov. Identifier: NCT02905032.
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Affiliation(s)
- Peter A Noseworthy
- Knowledge and Evaluation Research Unit Mayo Clinic Rochester MN.,Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery Mayo Clinic Rochester MN.,Heart Rhythm Services Department of Cardiovascular Diseases Mayo Clinic Rochester MN
| | - Megan E Branda
- Knowledge and Evaluation Research Unit Mayo Clinic Rochester MN.,Division of Biomedical Statistics and Informatics Department of Health Sciences Research Mayo Clinic Rochester MN.,Department of Biostatistics and Informatics Colorado School of Public Health University of Colorado-Denver Anschutz Medical Campus Aurora CO
| | - Marleen Kunneman
- Knowledge and Evaluation Research Unit Mayo Clinic Rochester MN.,Biomedical Data Sciences Leiden University Medical Center Leiden the Netherlands
| | - Ian G Hargraves
- Knowledge and Evaluation Research Unit Mayo Clinic Rochester MN
| | - Angela L Sivly
- Knowledge and Evaluation Research Unit Mayo Clinic Rochester MN
| | - Juan P Brito
- Knowledge and Evaluation Research Unit Mayo Clinic Rochester MN
| | - Bruce Burnett
- Thrombosis Clinic and Anticoagulation ServicesPark Nicollet Health Services St Louis Park MN
| | | | - Mark Linzer
- Department of Medicine Hennepin Healthcare, and the University of Minnesota Minneapolis MN
| | - Takeki Suzuki
- Department of Medicine Krannert Institute of CardiologyIndiana University Indianapolis IN
| | - Alexander T Lee
- Division of Biomedical Statistics and Informatics Department of Health Sciences Research Mayo Clinic Rochester MN
| | - Haeshik Gorr
- Department of Medicine Hennepin Healthcare, and the University of Minnesota Minneapolis MN
| | - Elizabeth A Jackson
- Division of Cardiovascular Disease Department of Internal Medicine University of Alabama at Birmingham Birmingham AL
| | - Erik Hess
- Department of Emergency Medicine for Vanderbilt University Medical Center Nashville TN
| | - Sarah R Brand-McCarthy
- Knowledge and Evaluation Research Unit Mayo Clinic Rochester MN.,Department of Psychiatry and Psychology Mayo Clinic Rochester MN
| | - Nilay D Shah
- Knowledge and Evaluation Research Unit Mayo Clinic Rochester MN
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Camilleri M, Andresen V, Keller J, Layer P, Montori VM. Pharmacological and non-pharmacological interventions for symptomatic gastroparesis. Hippokratia 2022. [DOI: 10.1002/14651858.cd007116.pub2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Michael Camilleri
- Clinical Enteric Neuroscience Translational & Epidemiological Research; Mayo Clinic; Rochester Minnesota USA
| | - Viola Andresen
- Internal Medicine; Israelitic Hospital, University of Hamburg; Hamburg Germany
| | - Jutta Keller
- Internal Medicine; Israelitic Hospital, University of Hamburg; Hamburg Germany
| | - Peter Layer
- Internal Medicine; Israelitic Hospital, University of Hamburg; Hamburg Germany
| | - Victor M Montori
- Division of Endocrinology, Department of Internal Medicine; Mayo Clinic; Rochester Minnesota USA
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Branda ME, Kunneman M, Meza-Contreras AI, Shah ND, Hess EP, LeBlanc A, Linderbaum JA, Nelson DM, Mc Donah MR, Sanvick C, Van Houten HK, Coylewright M, Dick SR, Ting HH, Montori VM. Shared Decision-Making for Patients Hospitalized with Acute Myocardial Infarction: A Randomized Trial. Patient Prefer Adherence 2022; 16:1395-1404. [PMID: 35673524 PMCID: PMC9167591 DOI: 10.2147/ppa.s363528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 05/19/2022] [Indexed: 11/23/2022] Open
Abstract
OBJECTIVE Adherence to guideline-recommended medications after acute myocardial infarction (AMI) is suboptimal. Patient fidelity to treatment regimens may be related to their knowledge of the risk of death following AMI, the pros and cons of medications, and to their involvement in treatment decisions. Shared decision-making may improve both patients' knowledge and involvement in treatment decisions. METHODS In a pilot trial, patients hospitalized with AMI were randomized to the use of the AMI Choice conversation tool or to usual care. AMI Choice includes a pictogram of the patient's estimated risk of mortality at 6 months with and without guideline-recommended medications, ie, aspirin, statins, beta-blockers, and angiotensin-converting enzyme inhibitors. Primary outcomes were patient knowledge and conflict with the decision made assessed via post-encounter surveys. Secondary outcomes were patient involvement in the decision-making process (observer-based OPTION12 scale) and 6-month medication adherence. RESULTS Patient knowledge of the expected survival benefit from taking medications was significantly higher (62% vs 16%, p<0.0001) in the AMI Choice group (n = 53) compared to the usual care group (n = 53). Both groups reported similarly low levels of conflict with the decision to start the medications (13 (SD 24.2) vs 16 (SD 22) out of 100; p=0.16). The extent to which clinicians in the AMI Choice group involved their patients in the decision-making process was high (OPTION12 score 53 out of 100, SD 12). Medication adherence at 6-months was relatively high in both groups and not different between groups. CONCLUSION The AMI Choice conversation tool improved patients' knowledge of their estimated risk of short-term mortality after an AMI and the pros and cons of treatments to reduce this risk. The effect on patient fidelity to recommended medications of using this SDM tool and of SDM in general should be tested in larger trials enrolling patients at high risk for nonadherence. TRIAL REGISTRATION NUMBER NCT00888537.
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Affiliation(s)
- Megan E Branda
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
- Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Marleen Kunneman
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
- Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands
| | - Alejandra I Meza-Contreras
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | | | - Erik P Hess
- Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Annie LeBlanc
- Faculty of Medicine, Laval University, Quebec City, Quebec, Canada
| | - Jane A Linderbaum
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Danika M Nelson
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | | | | | - Holly K Van Houten
- Robert D and Patricia E Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, MN, USA
| | - Megan Coylewright
- Section of Cardiovascular Medicine, Erlanger Heart and Lung Institute, Chattanooga, TN, USA
| | - Sara R Dick
- Education Project Management Office, Mayo Clinic, Rochester, MN, USA
| | | | - Victor M Montori
- Knowledge and Evaluation Research Unit, Department of Medicine, Mayo Clinic, Rochester, MN, USA
- Correspondence: Victor M Montori, 200 First Street SW, Rochester, MN, 55905, USA, Tel +1 507-284-2511, Email
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Chung MK, Fagerlin A, Wang PJ, Ajayi TB, Allen LA, Baykaner T, Benjamin EJ, Branda M, Cavanaugh KL, Chen LY, Crossley GH, Delaney RK, Eckhardt LL, Grady KL, Hargraves IG, Hills MT, Kalscheur MM, Kramer DB, Kunneman M, Lampert R, Langford AT, Lewis KB, Lu Y, Mandrola JM, Martinez K, Matlock DD, McCarthy SR, Montori VM, Noseworthy PA, Orland KM, Ozanne E, Passman R, Pundi K, Roden DM, Saarel EV, Schmidt MM, Sears SF, Stacey D, Stafford RS, Steinberg BA, Wass SY, Wright JM. Shared Decision Making in Cardiac Electrophysiology Procedures and Arrhythmia Management. Circ Arrhythm Electrophysiol 2021; 14:e007958. [PMID: 34865518 PMCID: PMC8692382 DOI: 10.1161/circep.121.007958] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Shared decision making (SDM) has been advocated to improve patient care, patient decision acceptance, patient-provider communication, patient motivation, adherence, and patient reported outcomes. Documentation of SDM is endorsed in several society guidelines and is a condition of reimbursement for selected cardiovascular and cardiac arrhythmia procedures. However, many clinicians argue that SDM already occurs with clinical encounter discussions or the process of obtaining informed consent and note the additional imposed workload of using and documenting decision aids without validated tools or evidence that they improve clinical outcomes. In reality, SDM is a process and can be done without decision tools, although the process may be variable. Also, SDM advocates counter that the low-risk process of SDM need not be held to the high bar of demonstrating clinical benefit and that increasing the quality of decision making should be sufficient. Our review leverages a multidisciplinary group of experts in cardiology, cardiac electrophysiology, epidemiology, and SDM, as well as a patient advocate. Our goal is to examine and assess SDM methodology, tools, and available evidence on outcomes in patients with heart rhythm disorders to help determine the value of SDM, assess its possible impact on electrophysiological procedures and cardiac arrhythmia management, better inform regulatory requirements, and identify gaps in knowledge and future needs.
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Affiliation(s)
| | - Angela Fagerlin
- University of Utah, Salt Lake City, UT
- Salt Lake City Veterans Affairs Informatics Decision-Enhancement and Analytic Sciences Center for Innovation, Salt Lake City, UT
| | | | | | | | | | | | - Megan Branda
- University of Colorado, Aurora, CO
- Mayo Clinic, Rochester, MN
| | | | | | | | | | | | | | | | | | | | | | - Marleen Kunneman
- Mayo Clinic, Rochester, MN
- Leiden University Medical Center, Leiden, the Netherlands
| | | | | | | | - Ying Lu
- Stanford University, Stanford, CA
| | | | | | | | | | | | | | | | | | | | | | - Dan M. Roden
- Vanderbilt University Medical Center, Nashville, TN
| | | | | | | | | | | | | | - Sojin Youn Wass
- Cleveland Clinic, Cleveland, OH
- University Hospitals Cleveland Medical Center, Cleveland, OH
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Affiliation(s)
- Frances S Mair
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester MN, USA
- The Patient Revolution, Inc., Rochester, MN, USA
| | - Carl R May
- London School of Hygiene and Tropical Medicine, London, UK
- NIHR North London Applied Research Collaborative, London, UK
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Taksler GB, Hu B, DeGrandis F, Montori VM, Fagerlin A, Nagykaldi Z, Rothberg MB. Effect of Individualized Preventive Care Recommendations vs Usual Care on Patient Interest and Use of Recommendations: A Pilot Randomized Clinical Trial. JAMA Netw Open 2021; 4:e2131455. [PMID: 34726747 PMCID: PMC8564576 DOI: 10.1001/jamanetworkopen.2021.31455] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/06/2021] [Accepted: 08/25/2021] [Indexed: 01/24/2023] Open
Abstract
Importance This randomized clinical trial examines the feasibility and acceptability of a decision-making tool for increasing patient interest in individualized recommendations for preventive care services. Objective To pilot a tool to help patients compare life expectancy gains from evidence-based preventive services. Design, Setting, and Participants This randomized clinical trial examined patient and physician responses to a pilot decision tool incorporating personalized risk factors at 3 US primary care clinics between 2017 and 2020. Eligible patients were between ages 45 to 70 years with 2 or more high-risk factors. Patients were followed-up after 1 year. Interventions The gain in life expectancy associated with guideline adherence to each recommended preventive service was estimated. Personalized estimates incorporating risk factors in electronic health records were displayed in a physician-distributed visual aid. During development, physicians discussed individualized results with patients using shared decision-making (SDM). During the trial, patients were randomized to receive individualized recommendations or usual care (nonmasked, parallel, 1:1 ratio). Main Outcomes and Measures Primary outcome was patient interest in individualized recommendations, assessed by survey. Secondary outcomes were use of SDM, decisional comfort, readiness to change, and preventive services received within 1 year. Results The study enrolled 104 patients (31 development, 39 intervention, 34 control), of whom 101 were included in analysis (mean [SD] age, 56.5 [5.3] years; 73 [72.3%] women; 80 [79.2%] Black patients) and 20 physicians. Intervention patients found the tool helpful and wanted to use it again, rating it a median 9 of 10 (IQR, 8-10) and 10 of 10 (8-10), respectively. Compared with the control group, intervention patients more often correctly identified the service least likely (18 [46%] vs 0; P = .03) to improve their life expectancy. A greater number of patients also identified the service most likely to improve their life expectancy (26 [69%] vs 10 [30%]; P = .07), although this result was not statistically significant. Intervention patients reported greater mean [SD] improvement in SDM (4.7 [6.9] points) and near-term readiness to change (13.8 points for top-3-ranked recommendations). Point estimates indicated that patients in the intervention group experienced greater, although non-statistically significant, reductions in percentage of body weight (-2.96%; 95% CI, -8.18% to 2.28%), systolic blood pressure (-6.42 mm Hg; 95% CI, -16.12 to 3.27 mm Hg), hemoglobin A1c (-0.68%; 95% CI, -1.82% to 0.45%), 10-year atherosclerotic cardiovascular disease risk score (-1.20%; 95% CI, -3.65% to 1.26%), and low-density lipoprotein cholesterol (-8.46 mg/dL; 95% CI, -26.63 to 9.70 mg/dL) than the control group. Nineteen of 20 physicians wanted to continue using the decision tool in the future. Conclusions and Relevance In this clinical trial, an individualized preventive care decision support tool improved patient understanding of primary prevention and demonstrated promise for improved shared decision-making and preventive care utilization. Trial Registration ClinicalTrials.gov Identifier: NCT03023813.
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Affiliation(s)
- Glen B. Taksler
- Cleveland Clinic Community Care, Cleveland Clinic, Cleveland, Ohio
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio
- Population Health Research Institute, Case Western Reserve University at MetroHealth System, Cleveland, Ohio
| | - Bo Hu
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio
| | | | - Victor M. Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota
| | - Angela Fagerlin
- Department of Population Heath Sciences, University of Utah, Salt Lake City
- Salt Lake City VA Informatics Decision-Enhancement and Analytic Sciences Center for Innovation, Salt Lake City, Utah
| | - Zsolt Nagykaldi
- Department of Family and Preventive Medicine, University of Oklahoma, Oklahoma City
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Torres Roldan VD, Ponce OJ, Urtecho M, Torres GF, Belluzzo T, Montori V, Liu C, Barrera F, Diaz A, Prokop L, Guyatt G, Montori VM. Understanding treatment-subgroup effect in primary and secondary prevention of cardiovascular disease: An exploration using meta-analyses of individual patient data. J Clin Epidemiol 2021; 139:160-166. [PMID: 34400257 DOI: 10.1016/j.jclinepi.2021.08.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 08/05/2021] [Accepted: 08/10/2021] [Indexed: 11/17/2022]
Abstract
BACKGROUND AND OBJECTIVE Recommendations for preventing cardiovascular (CV) disease are currently separated into primary and secondary prevention. We hypothesize that relative effects of interventions for CV prevention are not different across primary and secondary prevention cohorts. Our aim was to test for differences in relative effects on CV events in common preventive CV interventions across primary and secondary prevention cohorts. METHODS AND RESULTS A systematic search was performed to identify individual patient data (IPD) meta-analyses that included both primary and secondary prevention populations. Eligibility assessment, data extraction, and risk of bias assessment were conducted independently and in duplicate. We extracted relative risks (RR) with 95% confidence intervals (95% CI) of the interventions over patient-important outcomes and estimated the ratio of RR for primary and secondary prevention populations. We identified five eligible IPDs representing 524,570 participants. Quality assessment resulted in overall low-to-moderate methodological quality. We found no subgroup effect across prevention categories in any of the outcomes assessed. CONCLUSION In the absence of significant treatment-subgroup interactions between primary and secondary CV prevention cohorts for common preventive interventions, clinical practice guidelines could offer recommendations tailored to individual estimates of CV risk without regard to membership to primary and secondary prevention cohorts. This would require the development of reliable ASCVD risk estimators that apply across both cohorts.
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Affiliation(s)
| | - Oscar J Ponce
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | - Meritxell Urtecho
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | - Gabriel F Torres
- School of Medicine, Cayetano Heredia Peruvian University, Lima, Peru
| | - Tereza Belluzzo
- Internal Medicine, Jablonec nad Nisou Hospital, Jablonec nad Nisou, Czech Republic
| | - Victor Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | - Carolina Liu
- School of Medicine, Cayetano Heredia Peruvian University, Lima, Peru
| | - Francisco Barrera
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA; Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic (KER Unit Mexico), School of Medicine, Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo Leon, Mexico
| | - Alejandro Diaz
- Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic (KER Unit Mexico), School of Medicine, Universidad Autonoma de Nuevo Leon, Monterrey, Nuevo Leon, Mexico
| | - Larry Prokop
- Department of Library-Public Services, Mayo Clinic, Rochester, MN, USA
| | | | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA.
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Montori VM. Removing the blindfold: The centrality of care in caring for patients with multiple chronic conditions. Health Serv Res 2021; 56 Suppl 1:969-972. [PMID: 34378207 DOI: 10.1111/1475-6773.13865] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Revised: 07/28/2021] [Accepted: 08/01/2021] [Indexed: 11/27/2022] Open
Affiliation(s)
- Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
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