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Byrne RA, Rossello X, Coughlan JJ, Barbato E, Berry C, Chieffo A, Claeys MJ, Dan GA, Dweck MR, Galbraith M, Gilard M, Hinterbuchner L, Jankowska EA, Jüni P, Kimura T, Kunadian V, Leosdottir M, Lorusso R, Pedretti RFE, Rigopoulos AG, Rubini Gimenez M, Thiele H, Vranckx P, Wassmann S, Wenger NK, Ibanez B. 2023 ESC Guidelines for the management of acute coronary syndromes. EUROPEAN HEART JOURNAL. ACUTE CARDIOVASCULAR CARE 2024; 13:55-161. [PMID: 37740496 DOI: 10.1093/ehjacc/zuad107] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/24/2023]
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Levine DA, Whitney RT, Galecki AT, Fagerlin A, Wallner LP, Shore S, Langa KM, Nallamothu BK, Morgenstern LB, Giordani B, Reale BK, Blair EM, Sharma A, Kabeto MU, Plassman BL, Zahuranec DB. Patient Cognitive Status and Physician Recommendations for Cardiovascular Disease Treatment: Results of Two Nationwide, Randomized Survey Studies. J Gen Intern Med 2023; 38:3134-3143. [PMID: 37620721 PMCID: PMC10651817 DOI: 10.1007/s11606-023-08295-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 06/16/2023] [Indexed: 08/26/2023]
Abstract
BACKGROUND Clinical guidelines recommend that older patients (65+) with mild cognitive impairment (MCI) and early-stage dementia receive similar guideline-concordant care after cardiovascular disease (CVD) events as those with normal cognition (NC). However, older patients with MCI and dementia receive less care for CVD and other conditions than those with NC. Whether physician recommendations for guideline-concordant treatments after two common CVD events, acute myocardial infarction (AMI) and acute ischemic stroke (stroke), differ between older patients with NC, MCI, and early-stage dementia is unknown. OBJECTIVE To test the influence of patient cognitive status (NC, MCI, early-stage dementia) on physicians' recommendations for guideline-concordant treatments for AMI and stroke. DESIGN We conducted two parallel, randomized survey studies for AMI and stroke in the US using clinical vignettes where the hypothetical patient's cognitive status was randomized between physicians. PARTICIPANTS The study included cardiologists, neurologists, and generalists who care for most patients hospitalized for AMI and stroke. MAIN MEASURES The primary outcome was a composite quality score representing the number of five guideline-concordant treatments physicians recommended for a hypothetical patient after AMI or stroke. KEY RESULTS 1,031 physicians completed the study (58.5% response rate). Of 1,031 respondents, 980 physicians had complete information. After adjusting for physician factors, physicians recommended similar treatments after AMI and stroke in hypothetical patients with pre-existing MCI (adjusted ratio of expected composite quality score, 0.98 [95% CI, 0.94, 1.02]; P = 0.36) as hypothetical patients with NC. Physicians recommended fewer treatments to hypothetical patients with pre-existing early-stage dementia than to hypothetical patients with NC (adjusted ratio of expected composite quality score, 0.90 [0.86, 0.94]; P < 0.001). CONCLUSION In these randomized survey studies, physicians recommended fewer guideline-concordant AMI and stroke treatments to hypothetical patients with early-stage dementia than those with NC. We did not find evidence that physicians recommend fewer treatments to hypothetical patients with MCI than those with NC.
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Affiliation(s)
- Deborah A Levine
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA.
- Department of Neurology and Stroke Program, U-M, Ann Arbor, MI, USA.
- Institute for Healthcare Policy and Innovation, U-M, Ann Arbor, MI, USA.
- Division of General Medicine, U-M, Ann Arbor, MI, USA.
| | - Rachael T Whitney
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA
| | - Andrzej T Galecki
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA
- Department of Biostatistics, U-M, Ann Arbor, MI, USA
| | - Angela Fagerlin
- Department of Population Health Sciences, University of Utah, and Salt Lake City VA Informatics Decision-Enhancement and Analytic Sciences (IDEAS 2.0) Center for Innovation, Salt Lake City, UT, USA
| | - Lauren P Wallner
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, U-M, Ann Arbor, MI, USA
- Department of Epidemiology, U-M, Ann Arbor, MI, USA
| | - Supriya Shore
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA
| | - Kenneth M Langa
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, U-M, Ann Arbor, MI, USA
- Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
- Institute for Social Research, U-M, Ann Arbor, MI, USA
| | - Brahmajee K Nallamothu
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, U-M, Ann Arbor, MI, USA
- Center for Clinical Management Research, VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Lewis B Morgenstern
- Department of Neurology and Stroke Program, U-M, Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, U-M, Ann Arbor, MI, USA
- Department of Epidemiology, U-M, Ann Arbor, MI, USA
| | - Bruno Giordani
- Department of Psychiatry, U-M, Ann Arbor, MI, USA
- Michigan Alzheimer's Disease Center, U-M, Ann Arbor, MI, USA
| | - Bailey K Reale
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA
- Lake Erie College of Osteopathic Medicine, Erie, PA, USA
| | - Emilie M Blair
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA
| | - Anupriya Sharma
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA
| | - Mohammed U Kabeto
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan (U-M), Ann Arbor, MI, USA
| | - Brenda L Plassman
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
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Byrne RA, Rossello X, Coughlan JJ, Barbato E, Berry C, Chieffo A, Claeys MJ, Dan GA, Dweck MR, Galbraith M, Gilard M, Hinterbuchner L, Jankowska EA, Jüni P, Kimura T, Kunadian V, Leosdottir M, Lorusso R, Pedretti RFE, Rigopoulos AG, Rubini Gimenez M, Thiele H, Vranckx P, Wassmann S, Wenger NK, Ibanez B. 2023 ESC Guidelines for the management of acute coronary syndromes. Eur Heart J 2023; 44:3720-3826. [PMID: 37622654 DOI: 10.1093/eurheartj/ehad191] [Citation(s) in RCA: 399] [Impact Index Per Article: 399.0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/26/2023] Open
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van der Horst DEM, Garvelink MM, Bos WJW, Stiggelbout AM, Pieterse AH. For which decisions is Shared Decision Making considered appropriate? - A systematic review. PATIENT EDUCATION AND COUNSELING 2023; 106:3-16. [PMID: 36220675 DOI: 10.1016/j.pec.2022.09.015] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 08/26/2022] [Accepted: 09/26/2022] [Indexed: 06/16/2023]
Abstract
OBJECTIVE To identify decision characteristics for which SDM authors deem SDM appropriate or not, and what arguments are used. METHODS We applied two search strategies: we included SDM models from an earlier review (strategy 1) and conducted a new search in eight databases to include papers other than describing an SDM model, such as original research, opinion papers and reviews (strategy 2). RESULTS From the 92 included papers, we identified 18 decision characteristics for which authors deemed SDM appropriate, including preference-sensitive, equipoise and decisions where patient commitment is needed in implementing the decision. SDM authors indicated limits to SDM, especially when there are immediate life-saving measures needed. We identified four decision characteristics on which authors of different papers disagreed on whether or not SDM is appropriate. CONCLUSION The findings of this review show the broad range of decision characteristics for which authors deem SDM appropriate, the ambiguity of some, and potential limits of SDM. PRACTICE IMPLICATIONS The findings can stimulate clinicians to (re)consider pursuing SDM in situations in which they did not before. Additionally, it can inform SDM campaigns and educational programs as it shows for which decision situations SDM might be more or less challenging to practice.
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Affiliation(s)
- Dorinde E M van der Horst
- St. Antonius Hospital, Department of Internal Medicine, Nieuwegein, the Netherlands; Santeon, Utrecht, the Netherlands; Leiden University Medical Centre, Department of Internal Medicine, Leiden, the Netherlands.
| | - Mirjam M Garvelink
- St. Antonius Hospital, Department of Value Based Healthcare, Nieuwegein, the Netherlands
| | - Willem Jan W Bos
- St. Antonius Hospital, Department of Internal Medicine, Nieuwegein, the Netherlands; Leiden University Medical Centre, Department of Internal Medicine, Leiden, the Netherlands
| | - Anne M Stiggelbout
- Leiden University Medical Centre, Department of Biomedical Data Sciences, Leiden, the Netherlands; Erasmus School of Health Policy and Management, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Arwen H Pieterse
- Leiden University Medical Centre, Department of Biomedical Data Sciences, Leiden, the Netherlands
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The Association Between Mild Cognitive Impairment Diagnosis and Patient Treatment Preferences: a Survey of Older Adults. J Gen Intern Med 2022; 37:1925-1934. [PMID: 33963503 PMCID: PMC9198187 DOI: 10.1007/s11606-021-06839-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 03/25/2021] [Accepted: 04/20/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Older patients (65+) with mild cognitive impairment (MCI) receive less guideline-concordant care for cardiovascular disease (CVD) and other conditions than patients with normal cognition (NC). One potential explanation is that patients with MCI want less treatment than patients with NC; however, the treatment preferences of patients with MCI have not been studied. OBJECTIVE To determine whether patients with MCI have different treatment preferences than patients with NC. DESIGN Cross-sectional survey conducted at two academic medical centers from February to December 2019 PARTICIPANTS: Dyads of older outpatients with MCI and NC and patient-designated surrogates. MAIN MEASURES The modified Life-Support Preferences-Predictions Questionnaire score measured patients' preferences for life-sustaining treatment decisions in six health scenarios including stroke and acute myocardial infarction (range, 0-24 treatments rejected with greater scores indicating lower desire for treatment). KEY RESULTS The survey response rate was 73.4%. Of 136 recruited dyads, 127 (93.4%) completed the survey (66 MCI and 61 NC). The median number of life-sustaining treatments rejected across health scenarios did not differ significantly between patients with MCI and patients with NC (4.5 vs 6.0; P=0.55). Most patients with MCI (80%) and NC (80%) desired life-sustaining treatments in their current health (P=0.99). After adjusting for patient and surrogate factors, the difference in mean counts of rejected treatments between patients with MCI and patients with NC was not statistically significant (adjusted ratio, 1.08, 95% CI, 0.80-1.44; P=0.63). CONCLUSION We did not find evidence that patients with MCI want less treatment than patients with NC. These findings suggest that other provider and system factors might contribute to patients with MCI getting less guideline-concordant care.
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Blair EM, Zahuranec DB, Forman J, Reale BK, Langa KM, Giordani B, Fagerlin A, Kollman C, Whitney RT, Levine DA. Physician Diagnosis and Knowledge of Mild Cognitive Impairment. J Alzheimers Dis 2021; 85:273-282. [PMID: 34806602 DOI: 10.3233/jad-210565] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Older adults with mild cognitive impairment (MCI) receive fewer guideline-concordant treatments for multiple health conditions than those with normal cognition. Reasons for this disparity are unclear. OBJECTIVE To better understand this disparity, we describe physician understanding and experience with patient MCI, particularly physician identification of MCI, ability to distinguish between MCI and dementia, and perspectives on education and training in MCI and dementia. METHODS As part of a mixed-methods study assessing the influence of patient MCI on physician recommendations for acute myocardial infraction and stroke treatments, we conducted a descriptive qualitative study using semi-structured interviews of physicians from three specialties. Key question topics included participants' identification of MCI, impressions of MCI and dementia awareness within their practice specialty, and perspectives on training and education in MCI. RESULTS The study included 22 physicians (8 cardiologists, 7 neurologists, and 7 internists). We identified two primary themes: There is 1) a lack of adequate understanding of the distinction between MCI and dementia; and 2) variation in physician approaches to identifying whether an older adult has MCI. CONCLUSION These findings suggest that physicians have a poor understanding of MCI. Our results suggest that interventions that improve physician knowledge of MCI are needed.
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Affiliation(s)
- Emilie M Blair
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
| | - Darin B Zahuranec
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA.,Department of Neurology and Stroke Program, University of Michigan, Ann Arbor, MI, USA
| | - Jane Forman
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA.,VA Ann Arbor Healthcare System, Ann Arbor, MI, USA
| | - Bailey K Reale
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
| | - Kenneth M Langa
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA.,VA Ann Arbor Healthcare System, Ann Arbor, MI, USA.,Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA.,Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Bruno Giordani
- Department of Psychiatry & Michigan Alzheimer's Disease Center, University of Michigan, Ann Arbor, MI, USA
| | - Angela Fagerlin
- Department of Population Health Sciences, UT and Salt Lake City VA Informatics Decision-Enhancement and Analytic Sciences (IDEAS 2.0) Center for Innovation, University of Utah, Salt Lake City, UT, USA
| | | | - Rachael T Whitney
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA
| | - Deborah A Levine
- Department of Internal Medicine and Cognitive Health Services Research Program, University of Michigan, Ann Arbor, MI, USA.,Department of Neurology and Stroke Program, University of Michigan, Ann Arbor, MI, USA.,Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA
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Waddell A, Lennox A, Spassova G, Bragge P. Barriers and facilitators to shared decision-making in hospitals from policy to practice: a systematic review. Implement Sci 2021; 16:74. [PMID: 34332601 PMCID: PMC8325317 DOI: 10.1186/s13012-021-01142-y] [Citation(s) in RCA: 61] [Impact Index Per Article: 20.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 07/03/2021] [Indexed: 11/10/2022] Open
Abstract
Background Involving patients in their healthcare using shared decision-making (SDM) is promoted through policy and research, yet its implementation in routine practice remains slow. Research into SDM has stemmed from primary and secondary care contexts, and research into the implementation of SDM in tertiary care settings has not been systematically reviewed. Furthermore, perspectives on SDM beyond those of patients and their treating clinicians may add insights into the implementation of SDM. This systematic review aimed to review literature exploring barriers and facilitators to implementing SDM in hospital settings from multiple stakeholder perspectives. Methods The search strategy focused on peer-reviewed qualitative studies with the primary aim of identifying barriers and facilitators to implementing SDM in hospital (tertiary care) settings. Studies from the perspective of patients, clinicians, health service administrators, and decision makers, government policy makers, and other stakeholders (for example researchers) were eligible for inclusion. Reported qualitative results were mapped to the Theoretical Domains Framework (TDF) to identify behavioural barriers and facilitators to SDM. Results Titles and abstracts of 8724 articles were screened and 520 were reviewed in full text. Fourteen articles met inclusion criteria. Most studies (n = 12) were conducted in the last four years; only four reported perspectives in addition to the patient-clinician dyad. In mapping results to the TDF, the dominant themes were Environmental Context and Resources, Social/Professional Role and Identity, Knowledge and Skills, and Beliefs about Capabilities. A wide range of barriers and facilitators across individual, organisational, and system levels were reported. Barriers specific to the hospital setting included noisy and busy ward environments and a lack of private spaces in which to conduct SDM conversations. Conclusions SDM implementation research in hospital settings appears to be a young field. Future research should build on studies examining perspectives beyond the clinician-patient dyad and further consider the role of organisational- and system-level factors. Organisations wishing to implement SDM in hospital settings should also consider factors specific to tertiary care settings in addition to addressing their organisational and individual SDM needs. Trial Registration The protocol for the review is registered on the Open Science Framework and can be found at https://osf.io/da645/, DOI 10.17605/OSF.IO/DA645. Supplementary Information The online version contains supplementary material available at 10.1186/s13012-021-01142-y.
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Affiliation(s)
- Alex Waddell
- Monash Sustainable Development Institute, Monash University, 8 Scenic Boulevard, Clayton Campus, Melbourne, VIC, 3800, Australia. .,Safer Care Victoria, 50 Lonsdale St, Melbourne, VIC, 3000, Australia.
| | - Alyse Lennox
- Monash Sustainable Development Institute, Monash University, 8 Scenic Boulevard, Clayton Campus, Melbourne, VIC, 3800, Australia
| | - Gerri Spassova
- Department of Marketing, Monash Business School, Level 6, Building S, Caulfield Campus 26 Sir John Monash Drive, Caulfield East, VIC, 3145, Australia
| | - Peter Bragge
- Monash Sustainable Development Institute, Monash University, 8 Scenic Boulevard, Clayton Campus, Melbourne, VIC, 3800, Australia
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