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Tafur AJ, Barnes GD, Bhagirath VC, Douketis J. Anticoagulation Stewardship to Bridge the Implementation Gap in Perioperative Anticoagulation Management. TH Open 2024; 8:e114-e120. [PMID: 38476982 PMCID: PMC10927368 DOI: 10.1055/a-2259-0911] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2023] [Accepted: 12/18/2023] [Indexed: 03/14/2024] Open
Abstract
Lack of alignment of care protocols among providers in health care is a driver of increased costs and suboptimal patient outcomes. Perioperative anticoagulation management is a good example of a complex area where protocol creation is a clinical challenge that demands input from multiple experts. Questions regarding the need for anticoagulation interruptions are frequent. Yet, due to layers of complexity involving analysis of anticoagulation indication, surgical risk, and anesthesia-associated bleeding risk as well as institutional practices, there is heterogeneity in how these interruptions are approached. The recent perioperative anticoagulation guidelines from the American College of Chest Physicians summarize extensive evidence for the management of anticoagulant and antiplatelet medications in patients who undergo elective interventions. However, implementation of these guidelines by individual clinicians is highly varied and often does not follow the best available clinical evidence. Against this background, anticoagulation stewardship units, which exist to improve safety and quality monitoring for the anticoagulated patient, are of growing interest. These units provide a bridge for the implementation of value-based, high-quality guidelines for patients who need perioperative anticoagulation interruption. We use a case to pragmatically illustrate the problem and tactics for change management and implementation science that may facilitate the adoption of perioperative anticoagulation guidelines.
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Affiliation(s)
- Alfonso J. Tafur
- Department of Medicine, Vascular Medicine, NorthShore—Edward-Elmhurst Health, Evanston, Illinois, United States
- Department of Medicine-Cardiovascular Medicine, Pritzker School of Medicine, University of Chicago, Chicago, Illinois, United States
| | - Geoffrey D. Barnes
- Frankel Cardiovascular Center and Institute for Healthcare Policy and Innovation Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, United States
| | | | - James Douketis
- Department of Medicine, McMaster University, Hamilton, Ontario, Canada
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McCarthy AM, Fernandez Perez C, Beidas RS, Bekelman JE, Blumenthal D, Mack E, Bauer AM, Ehsan S, Conant EF, Wheeler BC, Guerra CE, Nunes LW, Gabriel P, Doucette A, Wileyto EP, Buttenheim AM, Asch DA, Rendle KA, Shelton RC, Fayanju OM, Ware S, Plag M, Hyland S, Gionta T, Shulman LN, Schnoll R. Protocol for a pragmatic stepped wedge cluster randomized clinical trial testing behavioral economic implementation strategies to increase supplemental breast MRI screening among patients with extremely dense breasts. Implement Sci 2023; 18:65. [PMID: 38001506 PMCID: PMC10668465 DOI: 10.1186/s13012-023-01323-x] [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: 09/19/2023] [Accepted: 11/14/2023] [Indexed: 11/26/2023] Open
Abstract
BACKGROUND Increased breast density augments breast cancer risk and reduces mammography sensitivity. Supplemental breast MRI screening can significantly increase cancer detection among women with dense breasts. However, few women undergo this exam, and screening is consistently lower among racially minoritized populations. Implementation strategies informed by behavioral economics ("nudges") can promote evidence-based practices by improving clinician decision-making under conditions of uncertainty. Nudges directed toward clinicians and patients may facilitate the implementation of supplemental breast MRI. METHODS Approximately 1600 patients identified as having extremely dense breasts after non-actionable mammograms, along with about 1100 clinicians involved with their care at 32 primary care or OB/GYN clinics across a racially diverse academically based health system, will be enrolled. A 2 × 2 randomized pragmatic trial will test nudges to patients, clinicians, both, or neither to promote supplemental breast MRI screening. Before implementation, rapid cycle approaches informed by clinician and patient experiences and behavioral economics and health equity frameworks guided nudge design. Clinicians will be clustered into clinic groups based on existing administrative departments and care patterns, and these clinic groups will be randomized to have the nudge activated at different times per a stepped wedge design. Clinicians will receive nudges integrated into the routine mammographic report or sent through electronic health record (EHR) in-basket messaging once their clinic group (i.e., wedge) is randomized to receive the intervention. Independently, patients will be randomized to receive text message nudges or not. The primary outcome will be defined as ordering or scheduling supplemental breast MRI. Secondary outcomes include MRI completion, cancer detection rates, and false-positive rates. Patient sociodemographic information and clinic-level variables will be examined as moderators of nudge effectiveness. Qualitative interviews conducted at the trial's conclusion will examine barriers and facilitators to implementation. DISCUSSION This study will add to the growing literature on the effectiveness of behavioral economics-informed implementation strategies to promote evidence-based interventions. The design will facilitate testing the relative effects of nudges to patients and clinicians and the effects of moderators of nudge effectiveness, including key indicators of health disparities. The results may inform the introduction of low-cost, scalable implementation strategies to promote early breast cancer detection. TRIAL REGISTRATION ClinicalTrials.gov NCT05787249. Registered on March 28, 2023.
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Affiliation(s)
- Anne Marie McCarthy
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA.
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104, USA.
| | | | - Rinad S Beidas
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Justin E Bekelman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Daniel Blumenthal
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Elizabeth Mack
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Anna-Marika Bauer
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Sarah Ehsan
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Emily F Conant
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Carmen E Guerra
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Linda W Nunes
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Peter Gabriel
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Abigail Doucette
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - E Paul Wileyto
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Alison M Buttenheim
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Asch
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Katharine A Rendle
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Blockley Hall, 423 Guardian Drive, Philadelphia, PA, 19104, USA
| | - Rachel C Shelton
- Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Oluwadamilola M Fayanju
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Sue Ware
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Martina Plag
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Steven Hyland
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Tracy Gionta
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Lawrence N Shulman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Robert Schnoll
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
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Symecko H, Schnoll R, Beidas RS, Bekelman JE, Blumenthal D, Bauer AM, Gabriel P, Boisseau L, Doucette A, Powers J, Cappadocia J, McKenna DB, Richardville R, Cuff L, Offer R, Clement EG, Buttenheim AM, Asch DA, Rendle KA, Shelton RC, Fayanju OM, Wileyto EP, Plag M, Ware S, Shulman LN, Nathanson KL, Domchek SM. Protocol to evaluate sequential electronic health record-based strategies to increase genetic testing for breast and ovarian cancer risk across diverse patient populations in gynecology practices. Implement Sci 2023; 18:57. [PMID: 37932730 PMCID: PMC10629034 DOI: 10.1186/s13012-023-01308-w] [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: 08/29/2023] [Accepted: 09/29/2023] [Indexed: 11/08/2023] Open
Abstract
BACKGROUND Germline genetic testing is recommended by the National Comprehensive Cancer Network (NCCN) for individuals including, but not limited to, those with a personal history of ovarian cancer, young-onset (< 50 years) breast cancer, and a family history of ovarian cancer or male breast cancer. Genetic testing is underused overall, and rates are consistently lower among Black and Hispanic populations. Behavioral economics-informed implementation strategies, or nudges, directed towards patients and clinicians may increase the use of this evidence-based clinical practice. METHODS Patients meeting eligibility for germline genetic testing for breast and ovarian cancer will be identified using electronic phenotyping algorithms. A pragmatic cohort study will test three sequential strategies to promote genetic testing, two directed at patients and one directed at clinicians, deployed in the electronic health record (EHR) for patients in OB-GYN clinics across a diverse academic medical center. We will use rapid cycle approaches informed by relevant clinician and patient experiences, health equity, and behavioral economics to optimize and de-risk our strategies and methods before trial initiation. Step 1 will send patients messages through the health system patient portal. For non-responders, step 2 will reach out to patients via text message. For non-responders, Step 3 will contact patients' clinicians using a novel "pend and send" tool in the EHR. The primary implementation outcome is engagement with germline genetic testing for breast and ovarian cancer predisposition, defined as a scheduled genetic counseling appointment. Patient data collected through the EHR (e.g., race/ethnicity, geocoded address) will be examined as moderators of the impact of the strategies. DISCUSSION This study will be one of the first to sequentially examine the effects of patient- and clinician-directed strategies informed by behavioral economics on engagement with breast and ovarian cancer genetic testing. The pragmatic and sequential design will facilitate a large and diverse patient sample, allow for the assessment of incremental gains from different implementation strategies, and permit the assessment of moderators of strategy effectiveness. The findings may help determine the impact of low-cost, highly transportable implementation strategies that can be integrated into healthcare systems to improve the use of genomic medicine. TRIAL REGISTRATION ClinicalTrials.gov. NCT05721326. Registered February 10, 2023. https://www. CLINICALTRIALS gov/study/NCT05721326.
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Affiliation(s)
- Heather Symecko
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Robert Schnoll
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Rinad S Beidas
- Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Justin E Bekelman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Daniel Blumenthal
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Anna-Marika Bauer
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Peter Gabriel
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Leland Boisseau
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Abigail Doucette
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Jacquelyn Powers
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jacqueline Cappadocia
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Danielle B McKenna
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Robert Richardville
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Lauren Cuff
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ryan Offer
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Elizabeth G Clement
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alison M Buttenheim
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
- School of Nursing, University of Pennsylvania, Philadelphia, PA, USA
| | - David A Asch
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Katharine A Rendle
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Rachel C Shelton
- Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Oluwadamilola M Fayanju
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - E Paul Wileyto
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Martina Plag
- Center for Healthcare Transformation and Innovation, Penn Medicine, Philadelphia, PA, USA
| | - Sue Ware
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Interdisciplinary Research On Nicotine Addiction, University of Pennsylvania, Philadelphia, PA, USA
| | - Lawrence N Shulman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Katherine L Nathanson
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA
| | - Susan M Domchek
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Basser Center for BRCA, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Center for Cancer Care Innovation, Abramson Cancer Center, Penn Medicine, Philadelphia, PA, USA.
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Shakowski C, Page II RL, Wright G, Lunowa C, Marquez C, Suresh K, Allen LA, Glasgow RE, Lin CT, Wick A, Trinkley KE. Comparative effectiveness of generic commercial versus locally customized clinical decision support tools to reduce prescription of nonsteroidal anti-inflammatory drugs for patients with heart failure. J Am Med Inform Assoc 2023; 30:1516-1525. [PMID: 37352404 PMCID: PMC10436140 DOI: 10.1093/jamia/ocad109] [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: 12/02/2022] [Revised: 05/09/2023] [Accepted: 06/08/2023] [Indexed: 06/25/2023] Open
Abstract
OBJECTIVE To compare the effectiveness of 2 clinical decision support (CDS) tools to avoid prescription of nonsteroidal anti-inflammatory drugs (NSAIDs) in patients with heart failure (HF): a "commercial" and a locally "customized" alert. METHODS We conducted a retrospective cohort study of 2 CDS tools implemented within a large integrated health system. The commercial CDS tool was designed according to third-party drug content and EHR vendor specifications. The customized CDS tool underwent a user-centered design process informed by implementation science principles, with input from a cross disciplinary team. The customized CDS tool replaced the commercial CDS tool. Data were collected from the electronic health record via analytic reports and manual chart review. The primary outcome was effectiveness, defined as whether the clinician changed their behavior and did not prescribe an NSAID. RESULTS A random sample of 366 alerts (183 per CDS tool) was evaluated that represented 355 unique patients. The commercial CDS tool was effective for 7 of 172 (4%) patients, while the customized CDS tool was effective for 81 of 183 (44%) patients. After adjusting for age, chronic kidney disease, ejection fraction, NYHA class, concurrent prescription of an opioid or acetaminophen, visit type (inpatient or outpatient), and clinician specialty, the customized alerts were at 24.3 times greater odds of effectiveness compared to the commercial alerts (OR: 24.3 CI: 10.20-58.06). CONCLUSION Investing additional resources to customize a CDS tool resulted in a CDS tool that was more effective at reducing the total number of NSAID orders placed for patients with HF compared to a commercially available CDS tool.
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Affiliation(s)
| | - Robert L Page II
- Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Garth Wright
- Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Cali Lunowa
- Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Clyde Marquez
- Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Krithika Suresh
- Adult and Child Center for Outcomes Research and Delivery Science Center, Aurora, Colorado, USA
- Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, USA
| | - Larry A Allen
- Adult and Child Center for Outcomes Research and Delivery Science Center, Aurora, Colorado, USA
- Division of Cardiology, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Russel E Glasgow
- Adult and Child Center for Outcomes Research and Delivery Science Center, Aurora, Colorado, USA
- Department of Family Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Chen-Tan Lin
- UCHealth, Aurora, Colorado, USA
- Division of Internal Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | | | - Katy E Trinkley
- UCHealth, Aurora, Colorado, USA
- Department of Clinical Pharmacy, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
- Adult and Child Center for Outcomes Research and Delivery Science Center, Aurora, Colorado, USA
- Department of Family Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
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Fuery MA, Kadhim B, Samsky MD, Freeman JV, Clark K, Desai NR, Wilson FP, Ahmed T, Ahmad T. Electronic Health Record Embedded Strategies for Improving Care of Patients With Heart Failure. Curr Heart Fail Rep 2023; 20:280-286. [PMID: 37552356 DOI: 10.1007/s11897-023-00614-0] [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] [Accepted: 06/15/2023] [Indexed: 08/09/2023]
Abstract
PURPOSE A majority of clinical decisions use the electronic health record (EHR) and there is an unmet need to use its capability to help providers to make evidence-based decisions that improve care for heart failure patients. These electronic nudges are rooted in the human psychology of decision-making and often target specific cognitive biases. This review outlines the development of novel EHR nudges and specific lessons learned from each experience to inform the development of future interventions. RECENT FINDINGS There have been several randomized clinical trials examining the impact of EHR alerts on quality of care for heart failure patients. These interventions have targeted both clinicians and patients. There are features of each trial that inform best practices and future directions for EHR nudges. Recent clinical trials have demonstrated that some EHR alerts can improve care for heart failure patients. These trials utilized default options, involved clinicians in the alert design process, provided actionable recommendations, and aimed to minimize disruptions to typical workflow. Alerts aimed at improving care should be examined in a randomized fashion in order to evaluate their impact on clinician satisfaction and patient care.
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Affiliation(s)
- Michael A Fuery
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, 06517, USA
| | - Bashar Kadhim
- Clinical and Translational Research Accelerator (CTRA), Yale School of Medicine, New Haven, CT, USA
| | - Marc D Samsky
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, 06517, USA
| | - James V Freeman
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, 06517, USA
| | - Katherine Clark
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, 06517, USA
| | - Nihar R Desai
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, 06517, USA
| | - Francis P Wilson
- Clinical and Translational Research Accelerator (CTRA), Yale School of Medicine, New Haven, CT, USA
| | - Treeny Ahmed
- Yale Center for Customer Insights, Yale School of Management, New Haven, CT, USA
| | - Tariq Ahmad
- Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT, 06517, USA.
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MacLeod J, Abdelrahim M, Painter S, Maddula R, Steward A, Hamid A, Cheng RK, Zaha V, Addison D, Bauer B, Brown SA. Ten step academic-industry digital health collaboration methodology: A case-based guide for digital health research teams with the example of cardio-oncology. Front Cardiovasc Med 2022; 9:982059. [PMID: 36247469 PMCID: PMC9562627 DOI: 10.3389/fcvm.2022.982059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 09/12/2022] [Indexed: 11/13/2022] Open
Affiliation(s)
- James MacLeod
- Medical College of Wisconsin, Milwaukee, WI, United States
| | | | - Sabrina Painter
- Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
| | | | - Austin Steward
- Medical College of Wisconsin, Milwaukee, WI, United States
| | | | - Richard K. Cheng
- Division of Cardiovascular Medicine, University of Washington, Seattle, WA, United States
| | - Vlad Zaha
- Cardiology Division, University of Texas Southwestern, Dallas, TX, United States
| | - Daniel Addison
- Cardio-Oncology Program, Division of Cardiovascular Medicine, The Ohio State University, Columbus, OH, United States
| | - Brenton Bauer
- COR Healthcare Associates, Torrance Memorial Medical Center, Torrance, CA, United States
| | - Sherry-Ann Brown
- Cardio-Oncology Program, Division of Cardiovascular Medicine, Medical College of Wisconsin, Milwaukee, WI, United States
- *Correspondence: Sherry-Ann Brown
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Hallek M, Ockenfels A, Wiesen D. Behavioral Economics Interventions to Improve Medical Decision-Making. Dtsch Arztebl Int 2022; 119:633-639. [PMID: 35912421 PMCID: PMC9764346 DOI: 10.3238/arztebl.m2022.0275] [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] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 09/30/2021] [Accepted: 04/07/2022] [Indexed: 01/05/2023]
Abstract
BACKGROUND In medicine, a wide gap exists between the medical care that ought to be possible in the light of the current state of medical research and the care that is actually provided. Behavioral biases and noise are two major reasons for this. METHODS We present the findings of a selective literature review and illustrate how interventions based on behavioral economics can help physicians make better decisions and thereby improve treatment outcomes. RESULTS A number of behavioral economics interventions, making use of, for example, default settings, active decision rules, social norms, and self-commitments, may improve physicians' clinical decision-making. Evidence on long-term effects is, however, mostly lacking. CONCLUSION Despite their apparent potential, the application of behavioral economic interventions to improve medical decisionmaking is still in its infancy, particularly in Germany.
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Affiliation(s)
- Michael Hallek
- University Hospital of Cologne, Internal Medicine Clinic I and Center for Integrated Oncology Aachen Bonn Cologne Dusseldorf (CIO)
| | - Axel Ockenfels
- Cologne University, Department of Economics, Center for Social and Economic Behavior (C-SEB) and Cluster of Excellence ECONtribute
| | - Daniel Wiesen
- Cologne University, Seminar for General Business Administration and Management in Healthcare and Center for Social and Economic Behavior (C-SEB),*Seminar for General Business Administration and Management in Healthcare University of Cologne Albertus-Magnus-Platz 50931 Cologne
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8
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Khazanov GK, Forbes CN, Dunn BD, Thase ME. Addressing anhedonia to increase depression treatment engagement. Br J Clin Psychol 2021; 61:255-280. [PMID: 34625993 DOI: 10.1111/bjc.12335] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [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: 03/17/2021] [Revised: 08/30/2021] [Indexed: 12/14/2022]
Abstract
Anhedonia, or reward system dysfunction, is associated with poorer treatment outcomes among depressed individuals. The role of anhedonia in treatment engagement, however, has not yet been explored. We review research on components of reward functioning impaired in depression, including effort valuation, reward anticipation, initial responsiveness, reward learning, reward probability, and reward delay, highlighting potential barriers to treatment engagement associated with these components. We then propose interventions to improve treatment initiation and continuation by addressing deficits in each component of reward functioning, focusing on modifications of existing evidence-based interventions to meet the needs of individuals with heightened anhedonia. We describe potential settings for these interventions and times at which they can be delivered during the process of referring individuals to mental health treatment, conducting intakes or assessments, and providing treatment. Additionally, we note the advantages of using screening processes already in place in primary care, workplace, school, and online settings to identify individuals with heightened anhedonia who may benefit from these interventions. We conclude with suggestions for future research on the impact of anhedonia on treatment engagement and the efficacy of interventions to address it. PRACTITIONER POINTS: Many depressed individuals who might benefit from treatment do not initiate it or discontinue early. One barrier to treatment engagement may be anhedonia, a core symptom of depression characterized by loss of interest or pleasure in usual activities. We describe brief interventions to improve treatment engagement in individuals with anhedonia that can be implemented during the referral process or early in treatment. We argue that interventions aiming to improve treatment engagement in depressed individuals that target anhedonia may be particularly effective.
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Affiliation(s)
- Gabriela K Khazanov
- Mental Illness Research, Education, and Clinical Center of the Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
| | | | | | - Michael E Thase
- Mental Illness Research, Education, and Clinical Center of the Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
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Wang X, Vouk N, Heaukulani C, Buddhika T, Martanto W, Lee J, Morris RJ. HOPES: An Integrative Digital Phenotyping Platform for Data Collection, Monitoring, and Machine Learning. J Med Internet Res 2021; 23:e23984. [PMID: 33720028 PMCID: PMC8074871 DOI: 10.2196/23984] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [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: 08/31/2020] [Revised: 12/04/2020] [Accepted: 01/18/2021] [Indexed: 01/20/2023] Open
Abstract
The collection of data from a personal digital device to characterize current health conditions and behaviors that determine how an individual's health will evolve has been called digital phenotyping. In this paper, we describe the development of and early experiences with a comprehensive digital phenotyping platform: Health Outcomes through Positive Engagement and Self-Empowerment (HOPES). HOPES is based on the open-source Beiwe platform but adds a wider range of data collection, including the integration of wearable devices and further sensor collection from smartphones. Requirements were partly derived from a concurrent clinical trial for schizophrenia that required the development of significant capabilities in HOPES for security, privacy, ease of use, and scalability, based on a careful combination of public cloud and on-premises operation. We describe new data pipelines to clean, process, present, and analyze data. This includes a set of dashboards customized to the needs of research study operations and clinical care. A test use case for HOPES was described by analyzing the digital behavior of 22 participants during the SARS-CoV-2 pandemic.
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Affiliation(s)
- Xuancong Wang
- Office for Healthcare Transformation, Ministry of Health, Singapore, Singapore
| | - Nikola Vouk
- Office for Healthcare Transformation, Ministry of Health, Singapore, Singapore
| | | | - Thisum Buddhika
- Office for Healthcare Transformation, Ministry of Health, Singapore, Singapore
| | - Wijaya Martanto
- Office for Healthcare Transformation, Ministry of Health, Singapore, Singapore
| | - Jimmy Lee
- Institute of Mental Health, Singapore, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Robert Jt Morris
- Office for Healthcare Transformation, Ministry of Health, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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Adusumalli S, Aragam G, Patel M. A Nudge Towards Cardiovascular Health: Applications of Behavioral Economics for Primary and Secondary Cardiovascular Prevention. Curr Treat Options Cardio Med 2020. [DOI: 10.1007/s11936-020-00824-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Abstract
Patients with cancer are at a higher risk of cardiovascular disease, which contributes to significant morbidity and mortality. The rapid progress in the field of oncological treatments has led to a steady increase in long-term cancer survivors. Care for cardiovascular complications is therefore becoming increasingly important. In addition, the establishment of new oncological therapies has resulted in the identification of previously unknown cardiovascular side effects. Oncocardiology aims to detect and treat cardiovascular diseases associated with cancer and cancer therapy. Continuous scientific, clinical, and structural developments are necessary as the basis for the best care of the growing number of affected patients. This review summarizes current developments in the field of oncocardiology with regard to advances in cancer therapy and challenges in clinical oncocardiology work. Cardiovascular side effects by targeted cancer therapies are characterized and recent advances in the field of cardiovascular diagnostics are outlined. Developments to better integrate oncocardiology into the medical care system and perspectives for modern, patient-oriented care are shown. In light of the coronavirus disease 2019 (COVID-19) pandemic, current challenges and opportunities are highlighted. The relevance of profitable further advances in oncocardiology including standardized guidelines and educational programs is delineated as a mandatory requirement for the successful development of oncocardiology.
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