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Feng Z, Li H, Chen X, Zhang T, Chen Y, Shao S, Du J. Patient Participation in Medication Safety for Noncommunicable Diseases: A Qualitative Study of General Practitioners, Pharmacists, and Outpatients' Perspectives in Beijing. Patient Prefer Adherence 2024; 18:1907-1918. [PMID: 39296427 PMCID: PMC11409925 DOI: 10.2147/ppa.s474921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 09/10/2024] [Indexed: 09/21/2024] Open
Abstract
Purpose Our study aimed to explore the current status of patient participation in medication safety from the perspectives of general practitioners (GPs), pharmacists, and outpatients in Beijing, China. Patients and Methods A qualitative study using semi-structured in-depth individual interviews with GPs, pharmacists, and outpatients. Subjects were identified by purposive sampling until code saturation. Semi-structured qualitative interviews were conducted with GPs, pharmacists, and patients from community health service centers in three urban districts of Beijing, China. The interviews were transcribed verbatim and the text was analysed using thematic analysis techniques including familiarising with data, generating initial codes, searching for themes, reviewing themes, defining and naming themes, and producing the report. Results A total of eight GPs, seven pharmacists, and 18 outpatients were interviewed. Data analysis led to the generation of five key themes: (1) mutual trust between patient and GP, (2) communication with healthcare professionals, (3) acquisition of knowledge about medication safety, (4) implementation of medication self-management at home, and (5) different attitudes toward participation in medication decisions. Patients participated in medication safety in multiple ways. However, insufficient knowledge about medication safety, lack of awareness of the patient's role in ensuring medication safety, shortage of consultation lengths, and being misled by some information were problems with patient participation in medication safety. Conclusion This exploratory study contributes to our initial understanding of patient participation in medication safety. There were still many issues and barriers in the process of patient participation. Appropriate policies and measures, such as providing various forms of patient education, ensuring sufficient physician-patient communication, giving full play to the role of pharmacists, and making judicious use of digital health tools should be taken to improve medication safety by fully utilising the role of patients.
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Affiliation(s)
- Zhengwen Feng
- School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China
| | - Hui Li
- School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China
| | - Xiaolei Chen
- School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China
| | - Tiancheng Zhang
- Department of General Practice, Dahongmen Community Health Service Center, Beijing, Fengtai District, People's Republic of China
| | - Yanxiang Chen
- Department of general practice, Changying Community Health Service Center, Beijing, Chaoyang District, People's Republic of China
| | - Shuang Shao
- School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China
| | - Juan Du
- School of General Practice and Continuing Education, Capital Medical University, Beijing, People's Republic of China
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Geta ET, Terefa DR, Hailu WB, Olani W, Merdassa E, Dessalegn M, Gelchu M, Diriba DC. Effectiveness of shared decision-making for glycaemic control among type 2 diabetes mellitus adult patients: A systematic review and meta-analysis. PLoS One 2024; 19:e0306296. [PMID: 39083503 PMCID: PMC11290692 DOI: 10.1371/journal.pone.0306296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Accepted: 06/16/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND In diabetes care and management guidelines, shared decision-making (SDM) implementation is explicitly recommended to help patients and health care providers to make informed shared decisions that enable informed choices and the selection of treatments. Despite widespread calls for SDM to be embedded in health care, there is little evidence to support SDM in the management and care of diabetes. It is still not commonly utilized in routine care settings because its effects remain poorly understood. Hence, the current systematic review and meta-analysis aimed to evaluate the effectiveness of SDM for glycaemic control among type 2 diabetes adult patients. METHODS Literature sources were searched in MEDLINE, PubMed, Cochrane library and HINARI bibliographic databases and Google Scholar. When these records were searched and reviewed, the PICO criteria (P: population, I: intervention, C: comparator, and O: outcome) were applied. The extracted data was exported to RevMan software version 5.4 and STATA 17 for further analysis. The mean differences (MD) of glycated hemoglobin (HbA1c) were pooled using a random effect model (REM), and sub-group analysis were performed to evaluate the effect size differences across the duration of the follow-up period, modes of intervention, and baseline glycated hemoglobin level of patient groups. The sensitivity analysis was performed using a leave-one-out meta-analysis to quantify the impact of each study on the overall effect size in mean difference HbA1c%. Finally, the statistically significant MD of HbA1c% between the intervention groups engaged in SDM and control groups received usual care was declared at P ˂0.05, using a 95% confidence interval (CI). RESULTS In the database search, 425 records were retrieved, with only 17 RCT studies fulfilling the inclusion criteria and were included in the meta-analysis. A total of 5416 subjects were included, out of which 2782(51.4%) were included in trial arms receiving SDM and 2634(48.6%) were included in usual diabetes care. The Higgins (I2) test statistics were calculated to be 59.1%, P = 0.002, indicating statistically significant heterogeneity was observed among the included studies, and REM was used as a remedial to estimate the pooled MD of HbA1c% level between patients who participated in SDM and received usual care. As a result, the pooled MD showed that the SDM significantly lowered HbA1c by 0.14% compared to the usual care (95% CI = [-0.26, -0.02], P = 0.02). SDM significantly decreased the level of HbA1c by 0.14% (95% CI = -0.28, -0.01, P = 0.00) when shared decisions were made in person or face-to-face at the point of care, but there was no statistically significant reduction in HbA1c levels when patients were engaged in online SDM. In patients with poorly controlled glycaemic level (≥ 8%), SDM significantly reduced level of HbA1c by 0.13%, 95% CI = [-0.29, -0.03], P = 0.00. However, significant reduction in HbA1c was not observed in patients with ˂ 8%, HbA1c baseline level. CONCLUSIONS Overall, statistically significant reduction of glycated hemoglobin level was observed among T2DM adult patients who participated in shared decision-making compared to those patients who received diabetes usual care that could lead to improved long-term health outcomes, reducing the risk of diabetes-related complications. Therefore, we strongly suggest that health care providers and policy-makers should integrate SDM into diabetes health care and management, and further study should focus on the level of patients' empowerment, health literacy, and standardization of decision supporting tools to evaluate the effectiveness of SDM in diabetes patients.
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Affiliation(s)
- Edosa Tesfaye Geta
- School of Public Health, Institute of Health Sciences, Wollega University, Nekemte, Ethiopia
| | - Dufera Rikitu Terefa
- School of Public Health, Institute of Health Sciences, Wollega University, Nekemte, Ethiopia
| | - Wase Benti Hailu
- School of Public Health, Institute of Health Sciences, Wollega University, Nekemte, Ethiopia
| | - Wolkite Olani
- School of Public Health, Institute of Health Sciences, Wollega University, Nekemte, Ethiopia
| | - Emiru Merdassa
- School of Public Health, Institute of Health Sciences, Wollega University, Nekemte, Ethiopia
| | - Markos Dessalegn
- School of Public Health, Institute of Health Sciences, Wollega University, Nekemte, Ethiopia
| | - Miesa Gelchu
- School of Public Health, Institute of Health, Bule Hora University, Bule Hora, Ethiopia
| | - Dereje Chala Diriba
- School of Nursing and Midwifery, Institute of Health Sciences, Wollega University, Nekemte, Ethiopia
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Vaseur RME, Te Braake E, Beinema T, d'Hollosy WON, Tabak M. Technology-supported shared decision-making in chronic conditions: A systematic review of randomized controlled trials. PATIENT EDUCATION AND COUNSELING 2024; 124:108267. [PMID: 38547638 DOI: 10.1016/j.pec.2024.108267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 03/15/2024] [Accepted: 03/20/2024] [Indexed: 05/06/2024]
Abstract
OBJECTIVES To describe the role of patients with a chronic disease, healthcare professionals (HCPs) and technology in shared decision making (SDM) and the use of clinical decision support systems (CDSSs), and to evaluate the effectiveness of SDM and CDSSs interventions. METHODS Randomized controlled studies published between 2011 and 2021 were identified and screened independently by two reviewers, followed by data extraction and analysis. SDM elements and interactive styles were identified to shape the roles of patients, HCPs and technology. RESULTS Forty-three articles were identified and reported on 21 SDM-studies, 15 CDSS-studies, 2 studies containing both an SDM-tool and a CDSS, and 5 studies with other decision support components. SDM elements were mostly identified in SDM-tools and interactions styles were least common in the other decision support components. CONCLUSIONS Patients within the included RCTs mainly received information from SDM-tools and occasionally CDSSs when it concerns treatment strategies. HCPs provide and clarify information using SDM-tools and CDSSs. Technology provides interactions, which can support more active SDM. SDM-tools mostly showed evidence for positive effects on SDM outcomes, while CDSSs mostly demonstrated positive effects on clinical outcomes. PRACTICE IMPLICATIONS Technology-supported SDM has potential to optimize SDM when patients, HCPs and technology collaborate well together.
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Affiliation(s)
- Roswita M E Vaseur
- Department of Biomedical Signals and Systems; University of Twente, Enschede, The Netherlands.
| | - Eline Te Braake
- Department of Biomedical Signals and Systems; University of Twente, Enschede, The Netherlands; Roessingh Research and Development, Enschede, The Netherlands
| | - Tessa Beinema
- Department of Human-Media Interaction; University of Twente, Enschede, The Netherlands
| | | | - Monique Tabak
- Department of Biomedical Signals and Systems; University of Twente, Enschede, The Netherlands
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Jaeken J, Billiouw C, Mertens L, Van Bostraeten P, Bekkering G, Vermandere M, Aertgeerts B, van Mileghem L, Delvaux N. A systematic review of shared decision making training programs for general practitioners. BMC MEDICAL EDUCATION 2024; 24:592. [PMID: 38811922 PMCID: PMC11137915 DOI: 10.1186/s12909-024-05557-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 05/15/2024] [Indexed: 05/31/2024]
Abstract
BACKGROUND Shared decision making (SDM) has been presented as the preferred approach for decisions where there is more than one acceptable option and has been identified a priority feature of high-quality patient-centered care. Considering the foundation of trust between general practitioners (GPs) and patients and the variety of diseases in primary care, the primary care context can be viewed as roots of SDM. GPs are requesting training programs to improve their SDM skills leading to a more patient-centered care approach. Because of the high number of training programs available, it is important to overview these training interventions specifically for primary care and to explore how these training programs are evaluated. METHODS This review was reported in accordance with the PRISMA guideline. Eight different databases were used in December 2022 and updated in September 2023. Risk of bias was assessed using ICROMS. Training effectiveness was analyzed using the Kirkpatrick evaluation model and categorized according to training format (online, live or blended learning). RESULTS We identified 29 different SDM training programs for GPs. SDM training has a moderate impact on patient (SMD 0.53 95% CI 0.15-0.90) and observer reported SDM skills (SMD 0.59 95%CI 0.21-0.97). For blended training programs, we found a high impact for quality of life (SMD 1.20 95% CI -0.38-2.78) and patient reported SDM skills (SMD 2.89 95%CI -0.55-6.32). CONCLUSION SDM training improves patient and observer reported SDM skills in GPs. Blended learning as learning format for SDM appears to show better effects on learning outcomes than online or live learning formats. This suggests that teaching facilities designing SDM training may want to prioritize blended learning formats. More homogeneity in SDM measurement scales and evaluation approaches and direct comparisons of different types of educational formats are needed to develop the most appropriate and effective SDM training format. TRIAL REGISTRATION PROSPERO: A systematic review of shared-decision making training programs in a primary care setting. PROSPERO 2023 CRD42023393385 Available from: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023393385 .
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Affiliation(s)
- Jasmien Jaeken
- Department of PH&PC, Academic Center for General Practice, KU Leuven, Kapucijnenvoer 7 block h, box 7001, Leuven, 3000, Belgium.
| | - Cathoo Billiouw
- Department of PH&PC, Academic Center for General Practice, KU Leuven, Kapucijnenvoer 7 block h, box 7001, Leuven, 3000, Belgium
| | - Lien Mertens
- Department of PH&PC, Academic Center for General Practice, KU Leuven, Kapucijnenvoer 7 block h, box 7001, Leuven, 3000, Belgium
| | - Pieter Van Bostraeten
- Department of PH&PC, Academic Center for General Practice, KU Leuven, Kapucijnenvoer 7 block h, box 7001, Leuven, 3000, Belgium
| | - Geertruida Bekkering
- Department of PH&PC, Academic Center for General Practice, KU Leuven, Kapucijnenvoer 7 block h, box 7001, Leuven, 3000, Belgium
| | - Mieke Vermandere
- Department of PH&PC, Academic Center for General Practice, KU Leuven, Kapucijnenvoer 7 block h, box 7001, Leuven, 3000, Belgium
| | - Bert Aertgeerts
- Department of PH&PC, Academic Center for General Practice, KU Leuven, Kapucijnenvoer 7 block h, box 7001, Leuven, 3000, Belgium
| | - Laura van Mileghem
- Department of PH&PC, Academic Center for General Practice, KU Leuven, Kapucijnenvoer 7 block h, box 7001, Leuven, 3000, Belgium
| | - Nicolas Delvaux
- Department of PH&PC, Academic Center for General Practice, KU Leuven, Kapucijnenvoer 7 block h, box 7001, Leuven, 3000, Belgium
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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] [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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Elias S, Chen Y, Liu X, Slone S, Turkson-Ocran RA, Ogungbe B, Thomas S, Byiringiro S, Koirala B, Asano R, Baptiste DL, Mollenkopf NL, Nmezi N, Commodore-Mensah Y, Himmelfarb CRD. Shared Decision-Making in Cardiovascular Risk Factor Management: A Systematic Review and Meta-Analysis. JAMA Netw Open 2024; 7:e243779. [PMID: 38530311 PMCID: PMC10966415 DOI: 10.1001/jamanetworkopen.2024.3779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 01/30/2024] [Indexed: 03/27/2024] Open
Abstract
Importance The effect of shared decision-making (SDM) and the extent of its use in interventions to improve cardiovascular risk remain unclear. Objective To assess the extent to which SDM is used in interventions aimed to enhance the management of cardiovascular risk factors and to explore the association of SDM with decisional outcomes, cardiovascular risk factors, and health behaviors. Data Sources For this systematic review and meta-analysis, a literature search was conducted in the Medline, CINAHL, Embase, Cochrane, Web of Science, Scopus, and ClinicalTrials.gov databases for articles published from inception to June 24, 2022, without language restrictions. Study Selection Randomized clinical trials (RCTs) comparing SDM-based interventions with standard of care for cardiovascular risk factor management were included. Data Extraction and Synthesis The systematic search resulted in 9365 references. Duplicates were removed, and 2 independent reviewers screened the trials (title, abstract, and full text) and extracted data. Data were pooled using a random-effects model. The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guideline. Main Outcomes and Measures Decisional outcomes, cardiovascular risk factor outcomes, and health behavioral outcomes. Results This review included 57 RCTs with 88 578 patients and 1341 clinicians. A total of 59 articles were included, as 2 RCTs were reported twice. Nearly half of the studies (29 [49.2%]) tested interventions that targeted both patients and clinicians, and an equal number (29 [49.2%]) exclusively focused on patients. More than half (32 [54.2%]) focused on diabetes management, and one-quarter focused on multiple cardiovascular risk factors (14 [23.7%]). Most studies (35 [59.3%]) assessed cardiovascular risk factors and health behaviors as well as decisional outcomes. The quality of studies reviewed was low to fair. The SDM intervention was associated with a decrease of 4.21 points (95% CI, -8.21 to -0.21) in Decisional Conflict Scale scores (9 trials; I2 = 85.6%) and a decrease of 0.20% (95% CI, -0.39% to -0.01%) in hemoglobin A1c (HbA1c) levels (18 trials; I2 = 84.2%). Conclusions and Relevance In this systematic review and meta-analysis of the current state of research on SDM interventions for cardiovascular risk management, there was a slight reduction in decisional conflict and an improvement in HbA1c levels with substantial heterogeneity. High-quality studies are needed to inform the use of SDM to improve cardiovascular risk management.
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Affiliation(s)
- Sabrina Elias
- Johns Hopkins School of Nursing, Baltimore, Maryland
| | - Yuling Chen
- Johns Hopkins School of Nursing, Baltimore, Maryland
| | - Xiaoyue Liu
- New York University Rory Meyers College of Nursing, New York, New York
| | - Sarah Slone
- Johns Hopkins School of Nursing, Baltimore, Maryland
| | - Ruth-Alma Turkson-Ocran
- Division of General Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts
| | - Bunmi Ogungbe
- Johns Hopkins School of Nursing, Baltimore, Maryland
| | | | | | - Binu Koirala
- Johns Hopkins School of Nursing, Baltimore, Maryland
| | - Reiko Asano
- Catholic University of America, Washington, DC
| | | | | | - Nwakaego Nmezi
- MedStar National Rehabilitation Hospital, Washington, DC
| | - Yvonne Commodore-Mensah
- Johns Hopkins School of Nursing, Baltimore, Maryland
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Cheryl R. Dennison Himmelfarb
- Johns Hopkins School of Nursing, Baltimore, Maryland
- Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Johns Hopkins School of Medicine, Baltimore, Maryland
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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: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [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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8
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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] [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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9
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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] [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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