1
|
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.
Collapse
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
| |
Collapse
|
2
|
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.
Collapse
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
| |
Collapse
|
3
|
Venkatesh KK, Wu J, Trinh A, Cross S, Rice D, Powe CE, Brindle S, Andreatta S, Bartholomew A, MacPherson C, Costantine MM, Saade G, McAlearney AS, Grobman WA, Landon MB. Patient Priorities, Decisional Comfort, and Satisfaction with Metformin versus Insulin for the Treatment of Gestational Diabetes Mellitus. Am J Perinatol 2024; 41:e3170-e3182. [PMID: 38049101 DOI: 10.1055/s-0043-1777334] [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] [Indexed: 12/06/2023]
Abstract
OBJECTIVE We compared patient priorities, decisional comfort, and satisfaction with treating gestational diabetes mellitus (GDM) with metformin versus insulin among pregnant individuals with GDM requiring pharmacotherapy. STUDY DESIGN We conducted a cross-sectional study of patients' perspectives about GDM pharmacotherapy in an integrated prenatal and diabetes care program from October 19, 2022, to August 24, 2023. The exposure was metformin versus insulin as the initial medication decision. Outcomes included standardized measures of patient priorities, decisional comfort, and satisfaction about their medication decision. RESULTS Among 144 assessed individuals, 60.4% were prescribed metformin and 39.6% were prescribed insulin. Minoritized individuals were more likely to receive metformin compared with non-Hispanic White individuals (34.9 vs. 17.5%; p = 0.03). Individuals who were willing to participate in a GDM pharmacotherapy clinical trial were more likely to receive insulin than those who were unwilling (30.4 vs. 19.5%; p = 0.02). Individuals receiving metformin were more likely to report prioritizing avoiding injections (62.4 vs. 19.3%; adjusted odds ratio [aOR]: 2.83; 95% confidence interval [CI]: 1.10-7.31), wanting to take a medication no more than twice daily (56.0 vs. 30.4%; aOR: 3.67; 95% CI: 1.56-8.67), and believing that both medications can equally prevent adverse pregnancy outcomes (70.9 vs. 52.6%; aOR: 2.67; 95% CI: 1.19-6.03). Conversely, they were less likely to report prioritizing a medication that crosses the placenta (39.1 vs. 82.5%; aOR: 0.09; 95% CI: 0.03-0.25) and needing supplemental insulin to achieve glycemic control (21.2 vs. 47.4%; aOR: 0.36; 95% CI: 0.15-0.90). Individuals reported similarly high (mean score > 80%) levels of decisional comfort, personal satisfaction with medication decision-making, and satisfaction about their conversation with their provider about their medication decision with metformin and insulin (p ≥ 0.05 for all). CONCLUSION Individuals with GDM requiring pharmacotherapy reported high levels of decision comfort and satisfaction with both metformin and insulin, although they expressed different priorities in medication decision-making. These results can inform future patient-centered GDM treatment strategies. KEY POINTS · Pregnant individuals with GDM requiring pharmacotherapy expressed a high level of decisional comfort and satisfaction with medication decision making.. · Individuals placed different priorities on deciding to take metformin versus insulin.. · These results can inform interventions aimed at delivering person-centered diabetes care in pregnancy that integrates patient autonomy and knowledge about treatment options..
Collapse
Affiliation(s)
- Kartik K Venkatesh
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University College of Medicine, Columbus, Ohio
| | - Jiqiang Wu
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University College of Medicine, Columbus, Ohio
| | - Anne Trinh
- Center for Health Outcomes and Policy Evaluation Studies, The Ohio State University, Columbus, Ohio
| | - Sharon Cross
- Department of Patient Experience, The Ohio State University Wexner Medical Center, Columbus, Ohio
| | - Donna Rice
- DiabetesSisters, Raleigh, North Carolina
| | - Camille E Powe
- Departments of Medicine and Obstetrics, Gynecology, and Reproductive Biology, Diabetes Unit, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Stephanie Brindle
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University College of Medicine, Columbus, Ohio
| | - Sophia Andreatta
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University College of Medicine, Columbus, Ohio
| | - Anna Bartholomew
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University College of Medicine, Columbus, Ohio
| | - Cora MacPherson
- Department of Epidemiology and Biostatistics, George Washington University, Washington, District of Columbia
| | - Maged M Costantine
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University College of Medicine, Columbus, Ohio
| | - George Saade
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Eastern Virginia Medical College, Norfolk, Virginia
| | - Ann Scheck McAlearney
- CATALYST-The Center for the Advancement of Team Science, Analytics, and Systems Thinking in Health Services and Implementation Science Research, The Ohio State University, Columbus, Ohio
- Department of Family and Community Medicine, College of Medicine, The Ohio State University, Columbus, Ohio
| | - William A Grobman
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University College of Medicine, Columbus, Ohio
| | - Mark B Landon
- Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University College of Medicine, Columbus, Ohio
| |
Collapse
|
4
|
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] [Grants] [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.
Collapse
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
| |
Collapse
|
5
|
Stacey D, Lewis KB, Smith M, Carley M, Volk R, Douglas EE, Pacheco-Brousseau L, Finderup J, Gunderson J, Barry MJ, Bennett CL, Bravo P, Steffensen K, Gogovor A, Graham ID, Kelly SE, Légaré F, Sondergaard H, Thomson R, Trenaman L, Trevena L. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev 2024; 1:CD001431. [PMID: 38284415 PMCID: PMC10823577 DOI: 10.1002/14651858.cd001431.pub6] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2024]
Abstract
BACKGROUND Patient decision aids are interventions designed to support people making health decisions. At a minimum, patient decision aids make the decision explicit, provide evidence-based information about the options and associated benefits/harms, and help clarify personal values for features of options. This is an update of a Cochrane review that was first published in 2003 and last updated in 2017. OBJECTIVES To assess the effects of patient decision aids in adults considering treatment or screening decisions using an integrated knowledge translation approach. SEARCH METHODS We conducted the updated search for the period of 2015 (last search date) to March 2022 in CENTRAL, MEDLINE, Embase, PsycINFO, EBSCO, and grey literature. The cumulative search covers database origins to March 2022. SELECTION CRITERIA We included published randomized controlled trials comparing patient decision aids to usual care. Usual care was defined as general information, risk assessment, clinical practice guideline summaries for health consumers, placebo intervention (e.g. information on another topic), or no intervention. DATA COLLECTION AND ANALYSIS Two authors independently screened citations for inclusion, extracted intervention and outcome data, and assessed risk of bias using the Cochrane risk of bias tool. Primary outcomes, based on the International Patient Decision Aid Standards (IPDAS), were attributes related to the choice made (informed values-based choice congruence) and the decision-making process, such as knowledge, accurate risk perceptions, feeling informed, clear values, participation in decision-making, and adverse events. Secondary outcomes were choice, confidence in decision-making, adherence to the chosen option, preference-linked health outcomes, and impact on the healthcare system (e.g. consultation length). We pooled results using mean differences (MDs) and risk ratios (RRs) with 95% confidence intervals (CIs), applying a random-effects model. We conducted a subgroup analysis of 105 studies that were included in the previous review version compared to those published since that update (n = 104 studies). We used Grading of Recommendations Assessment, Development, and Evaluation (GRADE) to assess the certainty of the evidence. MAIN RESULTS This update added 104 new studies for a total of 209 studies involving 107,698 participants. The patient decision aids focused on 71 different decisions. The most common decisions were about cardiovascular treatments (n = 22 studies), cancer screening (n = 17 studies colorectal, 15 prostate, 12 breast), cancer treatments (e.g. 15 breast, 11 prostate), mental health treatments (n = 10 studies), and joint replacement surgery (n = 9 studies). When assessing risk of bias in the included studies, we rated two items as mostly unclear (selective reporting: 100 studies; blinding of participants/personnel: 161 studies), due to inadequate reporting. Of the 209 included studies, 34 had at least one item rated as high risk of bias. There was moderate-certainty evidence that patient decision aids probably increase the congruence between informed values and care choices compared to usual care (RR 1.75, 95% CI 1.44 to 2.13; 21 studies, 9377 participants). Regarding attributes related to the decision-making process and compared to usual care, there was high-certainty evidence that patient decision aids result in improved participants' knowledge (MD 11.90/100, 95% CI 10.60 to 13.19; 107 studies, 25,492 participants), accuracy of risk perceptions (RR 1.94, 95% CI 1.61 to 2.34; 25 studies, 7796 participants), and decreased decisional conflict related to feeling uninformed (MD -10.02, 95% CI -12.31 to -7.74; 58 studies, 12,104 participants), indecision about personal values (MD -7.86, 95% CI -9.69 to -6.02; 55 studies, 11,880 participants), and proportion of people who were passive in decision-making (clinician-controlled) (RR 0.72, 95% CI 0.59 to 0.88; 21 studies, 4348 participants). For adverse outcomes, there was high-certainty evidence that there was no difference in decision regret between the patient decision aid and usual care groups (MD -1.23, 95% CI -3.05 to 0.59; 22 studies, 3707 participants). Of note, there was no difference in the length of consultation when patient decision aids were used in preparation for the consultation (MD -2.97 minutes, 95% CI -7.84 to 1.90; 5 studies, 420 participants). When patient decision aids were used during the consultation with the clinician, the length of consultation was 1.5 minutes longer (MD 1.50 minutes, 95% CI 0.79 to 2.20; 8 studies, 2702 participants). We found the same direction of effect when we compared results for patient decision aid studies reported in the previous update compared to studies conducted since 2015. AUTHORS' CONCLUSIONS Compared to usual care, across a wide variety of decisions, patient decision aids probably helped more adults reach informed values-congruent choices. They led to large increases in knowledge, accurate risk perceptions, and an active role in decision-making. Our updated review also found that patient decision aids increased patients' feeling informed and clear about their personal values. There was no difference in decision regret between people using decision aids versus those receiving usual care. Further studies are needed to assess the impact of patient decision aids on adherence and downstream effects on cost and resource use.
Collapse
Affiliation(s)
- Dawn Stacey
- School of Nursing, University of Ottawa, Ottawa, Canada
- Centre for Implementation Research, Ottawa Hospital Research Institute, Ottawa, Canada
| | | | | | - Meg Carley
- Centre for Implementation Research, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Robert Volk
- The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Elisa E Douglas
- Health Services Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Jeanette Finderup
- Department of Renal Medicine, Aarhus University Hospital, Aarhus, Denmark
| | | | - Michael J Barry
- Informed Medical Decisions Program, Massachusetts General Hospital, Boston, MA, USA
| | - Carol L Bennett
- Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada
| | - Paulina Bravo
- Education and Cancer Prevention, Fundación Arturo López Pérez, Santiago, Chile
| | - Karina Steffensen
- Center for Shared Decision Making, IRS - Lillebælt Hospital, Vejle, Denmark
| | - Amédé Gogovor
- VITAM - Centre de recherche en santé durable, Université Laval, Quebec, Canada
| | - Ian D Graham
- Centre for Implementation Research, Ottawa Hospital Research Institute, Ottawa, Canada
- School of Epidemiology, Public Health and Preventative Medicine, University of Ottawa, Ottawa, Canada
| | - Shannon E Kelly
- Cardiovascular Research Methods Centre, University of Ottawa Heart Institute, Ottawa, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Canada
| | - France Légaré
- Centre de recherche sur les soins et les services de première ligne de l'Université Laval (CERSSPL-UL), Université Laval, Quebec, Canada
| | | | - Richard Thomson
- Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
| | - Logan Trenaman
- Department of Health Systems and Population Health, School of Public Health, University of Washington, Seattle, WA, USA
| | | |
Collapse
|
6
|
Li Z, Jin Y, Lu C, Luo R, Wang J, Liu Y. Effects of patient decision aids in patients with type 2 diabetes mellitus: A systematic review and meta-analysis. Int J Nurs Pract 2021; 27:e12914. [PMID: 33657667 DOI: 10.1111/ijn.12914] [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: 05/21/2020] [Revised: 11/13/2020] [Accepted: 12/08/2020] [Indexed: 11/26/2022]
Abstract
AIMS This study aimed to systematically evaluate the effectiveness of patient decision aids on knowledge, decisional conflict and decisional self-efficacy outcomes in patients with diabetes. METHODS A comprehensive database search was performed using the Web of Science, Cochrane Library, PubMed, Embase, PsycINFO (Ovid), CINAHL (EBASCO), CNKI, VIP, Wan Fang Database and the Ottawa Decision Aid Library Inventory (http://decisionaid.ohri.ca/index.html) from inception to 13 October 2019. Two reviewers independently searched databases, screened articles, extracted data and evaluated the risk bias of included studies. Then Rev Man 5.3 software was adopted for statistical analysis. RESULTS Ten articles containing 1,452 people with diabetes were selected. The results of meta-analysis showed that patient decision aids had a positive effect on reducing decisional conflict and improving decisional self-efficacy among patients with type 2 diabetes. Meanwhile, this article also revealed that patient decision aids have beneficial short-term effects on improving knowledge, but there was no significant long-term effect. CONCLUSION Patient decision aids are capable of becoming support tools to improve shared decision making. Further implementation studies are required to transform patient decision aids tools into clinical practice.
Collapse
Affiliation(s)
- Zimeng Li
- School of Nursing, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yinghui Jin
- Center for Evidence-Based and Translational Medicine, Zhongnan Hospital of Wuhan University, Center for Evidence-Based and Translational Medicine, Wuhan University, Hubei, China
| | - Cui Lu
- Emergency Department, Tianjin TEDA Hospital, Tianjin, China
| | - Ruzhen Luo
- School of Nursing, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Jiayao Wang
- School of Nursing, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yanhui Liu
- School of Nursing, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| |
Collapse
|
7
|
Coronado-Vázquez V, Canet-Fajas C, Delgado-Marroquín MT, Magallón-Botaya R, Romero-Martín M, Gómez-Salgado J. Interventions to facilitate shared decision-making using decision aids with patients in Primary Health Care: A systematic review. Medicine (Baltimore) 2020; 99:e21389. [PMID: 32769870 PMCID: PMC7593011 DOI: 10.1097/md.0000000000021389] [Citation(s) in RCA: 56] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Shared decision making (SDM) is a process within the physician-patient relationship applicable to any clinical action, whether diagnostic, therapeutic, or preventive in nature. It has been defined as a process of mutual respect and participation between the doctor and the patient. The aim of this study is to determine the effectiveness of decision aids (DA) in primary care based on changes in adherence to treatments, knowledge, and awareness of the disease, conflict with decisions, and patients' and health professionals' satisfaction with the intervention. METHODS A systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted in Medline, CINAHL, Embase, the Cochrane Central Register of Controlled Trials, and the NHS Economic Evaluation Database. The inclusion criteria were randomized clinical trials as study design; use of SDM with DA as an intervention; primary care as clinical context; written in English, Spanish, and Portuguese; and published between January 2007 and January 2019. The risk of bias of the included studies in this review was assessed according to the Cochrane Collaboration's tool. RESULTS Twenty four studies were selected out of the 201 references initially identified. With the use of DA, the use of antibiotics was reduced in cases of acute respiratory infection and decisional conflict was decreased when dealing with the treatment choice for atrial fibrillation and osteoporosis. The rate of determination of prostate-specific antigen (PSA) in the prostate cancer screening decreased and colorectal cancer screening increased. Both professionals and patients increased their knowledge about depression, type 2 diabetes, and the perception of risk of acute myocardial infarction at 10 years without statins and with statins. The satisfaction was greater with the use of DA in choosing the treatment for depression, in cardiovascular risk management, in the treatment of low back pain, and in the use of statin therapy in diabetes. Blinding of outcomes assessment was the most common bias. CONCLUSIONS DA used in primary care are effective to reduce decisional conflict and improve knowledge on the disease and treatment options, awareness of risk, and satisfaction with the decisions made. More studies are needed to assess the impact of shared decision making in primary care.
Collapse
Affiliation(s)
- Valle Coronado-Vázquez
- Aragonese Primary Care Research Group B21-17R. Health Research Institute of Aragon (IIS). Department of Nursing. Faculty of Health Sciences. Catholic University of Ávila. Castilla La Mancha Health Service, Toledo
| | | | - Maria Teresa Delgado-Marroquín
- Bioethics Research Group. Health Research Institute of Aragon (IIS). Faculty of Medicine, University of Zaragoza. Delicias Norte Primary Care Health Center, Zaragoza
| | - Rosa Magallón-Botaya
- Aragonese Primary Care Research Group B21-17R. Health Research Institute of Aragon (IIS). Department of Medicine, University of Zaragoza. Arrabal Primary Care Health Center, Zaragoza
| | | | - Juan Gómez-Salgado
- Department of Sociology, Social Work and Public Health, Faculty of Labour Sciences, University of Huelva, Huelva, Spain
- Safety and Health Postgraduate Program, Espiritu Santo University, Guayaquil, Ecuador
| |
Collapse
|
8
|
Cross AJ, Elliott RA, Petrie K, Kuruvilla L, George J. Interventions for improving medication-taking ability and adherence in older adults prescribed multiple medications. Cochrane Database Syst Rev 2020; 5:CD012419. [PMID: 32383493 PMCID: PMC7207012 DOI: 10.1002/14651858.cd012419.pub2] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Older people taking multiple medications represent a large and growing proportion of the population. Managing multiple medications can be challenging, and this is especially the case for older people, who have higher rates of comorbidity and physical and cognitive impairment than younger adults. Good medication-taking ability and medication adherence are necessary to ensure safe and effective use of medications. OBJECTIVES To evaluate the effectiveness of interventions designed to improve medication-taking ability and/or medication adherence in older community-dwelling adults prescribed multiple long-term medications. SEARCH METHODS We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO, CINAHL Plus, and International Pharmaceutical Abstracts from inception until June 2019. We also searched grey literature, online trial registries, and reference lists of included studies. SELECTION CRITERIA We included randomised controlled trials (RCTs), quasi-RCTs, and cluster-RCTs. Eligible studies tested interventions aimed at improving medication-taking ability and/or medication adherence among people aged ≥ 65 years (or of mean/median age > 65 years), living in the community or being discharged from hospital back into the community, and taking four or more regular prescription medications (or with group mean/median of more than four medications). Interventions targeting carers of older people who met these criteria were also included. DATA COLLECTION AND ANALYSIS Two review authors independently reviewed abstracts and full texts of eligible studies, extracted data, and assessed risk of bias of included studies. We conducted meta-analyses when possible and used a random-effects model to yield summary estimates of effect, risk ratios (RRs) for dichotomous outcomes, and mean differences (MDs) or standardised mean differences (SMDs) for continuous outcomes, along with 95% confidence intervals (CIs). Narrative synthesis was performed when meta-analysis was not possible. We assessed overall certainty of evidence for each outcome using Grades of Recommendation, Assessment, Development and Evaluation (GRADE). Primary outcomes were medication-taking ability and medication adherence. Secondary outcomes included health-related quality of life (HRQoL), emergency department (ED)/hospital admissions, and mortality. MAIN RESULTS We identified 50 studies (14,269 participants) comprising 40 RCTs, six cluster-RCTs, and four quasi-RCTs. All included studies evaluated interventions versus usual care; six studies also reported a comparison between two interventions as part of a three-arm RCT design. Interventions were grouped on the basis of their educational and/or behavioural components: 14 involved educational components only, 7 used behavioural strategies only, and 29 provided mixed educational and behavioural interventions. Overall, our confidence in results regarding the effectiveness of interventions was low to very low due to a high degree of heterogeneity of included studies and high or unclear risk of bias across multiple domains in most studies. Five studies evaluated interventions for improving medication-taking ability, and 48 evaluated interventions for improving medication adherence (three studies evaluated both outcomes). No studies involved educational or behavioural interventions alone for improving medication-taking ability. Low-quality evidence from five studies, each using a different measure of medication-taking ability, meant that we were unable to determine the effects of mixed interventions on medication-taking ability. Low-quality evidence suggests that behavioural only interventions (RR 1.22, 95% CI 1.07 to 1.38; 4 studies) and mixed interventions (RR 1.22, 95% CI 1.08 to 1.37; 12 studies) may increase the proportions of people who are adherent compared with usual care. We could not include in the meta-analysis results from two studies involving mixed interventions: one had a positive effect on adherence, and the other had little or no effect. Very low-quality evidence means that we are uncertain of the effects of educational only interventions (5 studies) on the proportions of people who are adherent. Low-quality evidence suggests that educational only interventions (SMD 0.16, 95% CI -0.12 to 0.43; 5 studies) and mixed interventions (SMD 0.47, 95% CI -0.08 to 1.02; 7 studies) may have little or no impact on medication adherence assessed through continuous measures of adherence. We excluded 10 studies (4 educational only and 6 mixed interventions) from the meta-analysis including four studies with unclear or no available results. Very low-quality evidence means that we are uncertain of the effects of behavioural only interventions (3 studies) on medication adherence when assessed through continuous outcomes. Low-quality evidence suggests that mixed interventions may reduce the number of ED/hospital admissions (RR 0.67, 95% CI 0.50 to 0.90; 11 studies) compared with usual care, although results from six further studies that we were unable to include in meta-analyses indicate that the intervention may have a smaller, or even no, effect on these outcomes. Similarly, low-quality evidence suggests that mixed interventions may lead to little or no change in HRQoL (7 studies), and very low-quality evidence means that we are uncertain of the effects on mortality (RR 0.93, 95% CI 0.67 to 1.30; 7 studies). Moderate-quality evidence shows that educational interventions alone probably have little or no effect on HRQoL (6 studies) or on ED/hospital admissions (4 studies) when compared with usual care. Very low-quality evidence means that we are uncertain of the effects of behavioural interventions on HRQoL (1 study) or on ED/hospital admissions (2 studies). We identified no studies evaluating effects of educational or behavioural interventions alone on mortality. Six studies reported a comparison between two interventions; however due to the limited number of studies assessing the same types of interventions and comparisons, we are unable to draw firm conclusions for any outcomes. AUTHORS' CONCLUSIONS Behavioural only or mixed educational and behavioural interventions may improve the proportion of people who satisfactorily adhere to their prescribed medications, but we are uncertain of the effects of educational only interventions. No type of intervention was found to improve adherence when it was measured as a continuous variable, with educational only and mixed interventions having little or no impact and evidence of insufficient quality to determine the effects of behavioural only interventions. We were unable to determine the impact of interventions on medication-taking ability. The quality of evidence for these findings is low due to heterogeneity and methodological limitations of studies included in the review. Further well-designed RCTs are needed to investigate the effects of interventions for improving medication-taking ability and medication adherence in older adults prescribed multiple medications.
Collapse
Affiliation(s)
- Amanda J Cross
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, Australia
| | - Rohan A Elliott
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, Australia
- Pharmacy Department, Austin Health, Heidelberg, Australia
| | - Kate Petrie
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, Australia
| | - Lisha Kuruvilla
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, Australia
- Pharmacy Department, Barwon Health, North Geelong, Australia
| | - Johnson George
- Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, Australia
| |
Collapse
|
9
|
|
10
|
Wieringa TH, Rodriguez-Gutierrez R, Spencer-Bonilla G, de Wit M, Ponce OJ, Sanchez-Herrera MF, Espinoza NR, Zisman-Ilani Y, Kunneman M, Schoonmade LJ, Montori VM, Snoek FJ. Decision aids that facilitate elements of shared decision making in chronic illnesses: a systematic review. Syst Rev 2019; 8:121. [PMID: 31109357 PMCID: PMC6528254 DOI: 10.1186/s13643-019-1034-4] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/22/2018] [Accepted: 04/29/2019] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Shared decision making (SDM) is a patient-centered approach in which clinicians and patients work together to find and choose the best course of action for each patient's particular situation. Six SDM key elements can be identified: situation diagnosis, choice awareness, option clarification, discussion of harms and benefits, deliberation of patient preferences, and making the decision. The International Patient Decision Aid Standards (IPDAS) require that a decision aid (DA) support these key elements. Yet, the extent to which DAs support these six key SDM elements and how this relates to their impact remain unknown. METHODS We searched bibliographic databases (from inception until November 2017), reference lists of included studies, trial registries, and experts for randomized controlled trials of DAs in patients with cardiovascular, or chronic respiratory conditions or diabetes. Reviewers worked in duplicate and independently selected studies for inclusion, extracted trial, and DA characteristics, and evaluated the quality of each trial. RESULTS DAs most commonly clarified options (20 of 20; 100%) and discussed their harms and benefits (18 of 20; 90%; unclear in two DAs); all six elements were clearly supported in 4 DAs (20%). We found no association between the presence of these elements and SDM outcomes. CONCLUSIONS DAs for selected chronic conditions are mostly designed to transfer information about options and their harms and benefits. The extent to which their support of SDM key elements relates to their impact on SDM outcomes could not be ascertained. SYSTEMATIC REVIEW REGISTRATION PROSPERO registration number: CRD42016050320 .
Collapse
Affiliation(s)
- Thomas H Wieringa
- Department of Medical Psychology, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands.
| | - Rene Rodriguez-Gutierrez
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA.,Division of Endocrinology, Department of Internal Medicine, "Dr. Jose E. González" University Hospital, Autonomous University of Nuevo Leon, Monterrey, Nuevo Leon, Mexico.,Plataforma INVEST Medicina UANL-KER Unit Mayo Clinic, KER Unit México, "Dr. Jose E. González" University Hospital, Autonomous University of Nuevo Leon, Monterrey, Nuevo Leon, Mexico
| | - Gabriela Spencer-Bonilla
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA.,Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Maartje de Wit
- Department of Medical Psychology, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| | - Oscar J Ponce
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | | | - Nataly R Espinoza
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | | | - Marleen Kunneman
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA.,Medical Decision Making, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands
| | | | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, MN, USA
| | - Frank J Snoek
- Department of Medical Psychology, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, the Netherlands
| |
Collapse
|
11
|
Karagiannis T, Andreadis P, Manolopoulos A, Malandris K, Avgerinos I, Karagianni A, Tsapas A. Decision aids for people with Type 2 diabetes mellitus: an effectiveness rapid review and meta-analysis. Diabet Med 2019; 36:557-568. [PMID: 30791131 DOI: 10.1111/dme.13939] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/19/2019] [Indexed: 12/13/2022]
Abstract
AIMS To perform a rapid review and meta-analysis of randomized controlled trials (RCTs) evaluating patient decision aids (PtDAs) for people with Type 2 diabetes mellitus. METHODS We searched Medline and the Cochrane Library for RCTs assessing PtDAs in people with Type 2 diabetes. PtDAs were defined as tools designed to help people engage in decision-making about healthcare options, such as making treatment choices or setting therapeutic goals. The study selection process was facilitated by an automated screening tool to identify RCTs. We classified outcomes into seven domains and conducted meta-analyses using random effects models. RESULTS We included a total of 15 studies, nine of which were cluster RCTs, that evaluated 10 PtDAs. Thirteen trials compared a PtDA with usual care or usual care plus educational material, whereas two RCTs compared individually tailored vs. non-tailored PtDAs. Meta-analyses showed a favourable effect of PtDAs compared with usual care in reducing decisional conflict [weighted mean difference (WMD) -4.66, 95% confidence interval (CI) -7.93 to -1.39] and in improving knowledge (WMD 20.46, 95% CI 9.13 to 3.77). Use of PtDAs resulted in more active involvement in decision-making during the consultation, although no effect was evident in terms of glycaemic control or self-reported medication adherence. CONCLUSIONS PtDAs for people with Type 2 diabetes can improve the quality of decision-making and increase knowledge transfer. Interpretation of our findings is attenuated due to limitations related to the rapid review approach, including searching only two databases and performing data extraction and risk of bias assessment by a single reviewer.
Collapse
Affiliation(s)
- T Karagiannis
- Clinical Research and Evidence-Based Medicine Unit, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - P Andreadis
- Clinical Research and Evidence-Based Medicine Unit, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - A Manolopoulos
- Clinical Research and Evidence-Based Medicine Unit, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - K Malandris
- Clinical Research and Evidence-Based Medicine Unit, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - I Avgerinos
- Clinical Research and Evidence-Based Medicine Unit, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - A Karagianni
- Clinical Research and Evidence-Based Medicine Unit, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - A Tsapas
- Clinical Research and Evidence-Based Medicine Unit, Aristotle University of Thessaloniki, Thessaloniki, Greece
- Harris Manchester College, University of Oxford, Oxford, UK
| |
Collapse
|
12
|
Urman RD, Southerland WA, Shapiro FE, Joshi GP. Concepts for the Development of Anesthesia-Related Patient Decision Aids. Anesth Analg 2019; 128:1030-1035. [DOI: 10.1213/ane.0000000000003804] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
|
13
|
Scalia P, Durand MA, Berkowitz JL, Ramesh NP, Faber MJ, Kremer JAM, Elwyn G. The impact and utility of encounter patient decision aids: Systematic review, meta-analysis and narrative synthesis. PATIENT EDUCATION AND COUNSELING 2019; 102:817-841. [PMID: 30612829 DOI: 10.1016/j.pec.2018.12.020] [Citation(s) in RCA: 80] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2018] [Revised: 11/23/2018] [Accepted: 12/18/2018] [Indexed: 06/09/2023]
Abstract
OBJECTIVE To determine the effect of encounter patient decision aids (PDAs) as evaluated in randomized controlled trials (RCTs) and conduct a narrative synthesis of non-randomized studies assessing feasibility, utility and their integration into clinical workflows. METHODS Databases were systematically searched for RCTs of encounter PDAs to enable the conduct of a meta-analysis. We used a framework analysis approach to conduct a narrative synthesis of non-randomized studies. RESULTS We included 23 RCTs and 30 non-randomized studies. Encounter PDAs significantly increased knowledge (SMD = 0.42; 95% CI 0.30, 0.55), lowered decisional conflict (SMD= -0.33; 95% CI -0.56, -0.09), increased observational-based assessment of shared decision making (SMD = 0.94; 95% CI 0.40, 1.48) and satisfaction with the decision-making process (OR = 1.78; 95% CI 1.19, 2.66) without increasing visit durations (SMD= -0.06; 95% CI -0.29, 0.16). The narrative synthesis showed that encounter tools have high utility for patients and clinicians, yet important barriers to implementation exist (i.e. time constraints) at the clinical and organizational level. CONCLUSION Encounter PDAs have a positive impact on patient-clinician collaboration, despite facing implementation barriers. PRACTICAL IMPLICATIONS The potential utility of encounter PDAs requires addressing the systemic and structural barriers that prevent adoption in clinical practice.
Collapse
Affiliation(s)
- Peter Scalia
- The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, One Medical Center Drive, Lebanon, NH, 03756, USA.
| | - Marie-Anne Durand
- The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, One Medical Center Drive, Lebanon, NH, 03756, USA.
| | - Julia L Berkowitz
- The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, One Medical Center Drive, Lebanon, NH, 03756, USA.
| | - Nithya P Ramesh
- The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, One Medical Center Drive, Lebanon, NH, 03756, USA.
| | - Marjan J Faber
- Radboud university medical center, Scientific Institute for Quality of Healthcare, PO Box 9101, Nijmegen, 6500, HB, the Netherlands.
| | - Jan A M Kremer
- Radboud university medical center, Scientific Institute for Quality of Healthcare, PO Box 9101, Nijmegen, 6500, HB, the Netherlands.
| | - Glyn Elwyn
- The Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, One Medical Center Drive, Lebanon, NH, 03756, USA.
| |
Collapse
|
14
|
Macalalad-Josue AA, Palileo-Villanueva LA, Sandoval MA, Panuda JP. Development of a Patient Decision Aid on the Choice of Diabetes Medication for Filipino Patients with Type 2 Diabetes Mellitus. J ASEAN Fed Endocr Soc 2019; 34:44-55. [PMID: 33442136 PMCID: PMC7784104 DOI: 10.15605/jafes.034.01.08] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Accepted: 08/20/2018] [Indexed: 12/05/2022] Open
Abstract
OBJECTIVE To develop a locally adapted patient decision aid (PtDA) on treatment intensification among Filipino patients with Type 2 Diabetes Mellitus and to test the feasibility of using PtDAs in a low middle-income country. METHODOLOGY A qualitative approach and an iterative process of development of a PtDA were employed for this study. We describe the process of developing a Filipino version of the Diabetes Medication Decision Aid. This PtDA was designed to help the patient choose the appropriate treatment intensification based on his own values and preferences, in consultation with his physician. The process involved decisional needs assessment through focus group discussions and key informant interviews, systematic literature review, iterative process of the development of a PtDA with clinical encounters (pilot testing), and preliminary field testing. RESULTS Decisional needs assessment revealed that Filipino patients are open to participate in shared decision-making if given the opportunity, including those with low socioeconomic status who likely have low health literacy. Physicians prefer to have visual aid tools to help them support their patient's decision-making. A PtDA prototype of a set of flash cards in Filipino was created and revised in an iterative method. We developed a more visually appealing tool after inputs from the expert panel and patient advisory group. Its use during clinical encounters provided additional insights from patients and clinicians on how to improve the PtDA. Preliminary field testing showed that its use is feasible in the target patient population. CONCLUSION Filipino patients, clinicians, and diabetes nurse educators have contributed to the creation of the first Filipino PtDA for diabetes treatment intensification.
Collapse
Affiliation(s)
- Anna Angelica Macalalad-Josue
- Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of the Philippines-Philippine General Hospital
| | | | - Mark Anthony Sandoval
- Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of the Philippines-Philippine General Hospital
| | - Jose Paolo Panuda
- Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, University of the Philippines-Philippine General Hospital
| |
Collapse
|
15
|
Southerland WA, Tollinche LE, Shapiro FE. Decision Aids: The Role of the Patient in Perioperative Safety. Int Anesthesiol Clin 2019; 57:4-11. [PMID: 31577233 PMCID: PMC6777351 DOI: 10.1097/aia.0000000000000231] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Affiliation(s)
| | - Luis E. Tollinche
- Department of Anesthesiology & Critical Care Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Fred E. Shapiro
- Department of Anesthesiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| |
Collapse
|
16
|
Buhse S, Kuniss N, Liethmann K, Müller UA, Lehmann T, Mühlhauser I. Informed shared decision-making programme for patients with type 2 diabetes in primary care: cluster randomised controlled trial. BMJ Open 2018; 8:e024004. [PMID: 30552272 PMCID: PMC6303685 DOI: 10.1136/bmjopen-2018-024004] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
OBJECTIVE To translate an informed shared decision-making programme (ISDM-P) for patients with type 2 diabetes from a specialised diabetes centre to the primary care setting. DESIGN Patient-blinded, two-arm multicentre, cluster randomised controlled trial of 6 months follow-up; concealed randomisation of practices after patient recruitment and acquisition of baseline data. SETTING 22 general practices providing care according to the German Disease Management Programme (DMP) for type 2 diabetes. PARTICIPANTS 279 of 363 eligible patients without myocardial infarction or stroke. INTERVENTIONS The ISDM-P comprises a patient decision aid, a corresponding group teaching session provided by medical assistants and a structured patient-physician encounter.Control group received standard DMP care. PRIMARY AND SECONDARY OUTCOME MEASURES Primary endpoint was patient adherence to antihypertensive or statin drug therapy by comparing prescriptions and patient-reported uptake after 6 months. Secondary endpoints included informed choice, risk knowledge (score 0-11 from 11 questions) and prioritised treatment goals of patients and doctors. RESULTS ISDM-P: 11 practices with 151 patients; standard care: 11 practices with 128 patients; attrition rate: 3.9%. There was no difference between groups regarding the primary endpoint. Mean drug adherence rates were high for both groups (80% for antihypertensive and 91% for statin treatment). More ISDM-P patients made informed choices regarding statin intake, 34% vs 3%, OR 16.6 (95% CI 4.4 to 63.0), blood pressure control, 39% vs 3%, OR 22.2 (95% CI 5.3 to 93.3) and glycated haemoglobin, 43% vs 3%, OR 26.0 (95% CI 6.5 to 104.8). ISDM-P patients achieved higher levels of risk knowledge, with a mean score of 6.96 vs 2.86, difference 4.06 (95% CI 2.96 to 5.17). In the ISDM-P group, agreement on prioritised treatment goals between patients and doctors was higher, with 88.5% vs 57%. CONCLUSIONS The ISDM-P was successfully implemented in general practices. Adherence to medication was very high making improvements hardly detectable. TRIAL REGISTRATION NUMBER ISRCTN77300204; Results.
Collapse
Affiliation(s)
- Susanne Buhse
- Health Sciences and Education, University of Hamburg, Hamburg, Germany
| | - Nadine Kuniss
- Department of Internal Medicine III, Endocrinology and Metabolic Diseases, Jena University Hospital, Jena, Germany
- Diabetes Centre Thuringia, Jena, Germany
| | - Kathrin Liethmann
- Health Sciences and Education, University of Hamburg, Hamburg, Germany
- Institute of Medical Psychology and Sociology, University Medical Center Schleswig Holstein, Kiel, Germany
| | - Ulrich Alfons Müller
- Department of Internal Medicine III, Endocrinology and Metabolic Diseases, Jena University Hospital, Jena, Germany
- Diabetes Centre Thuringia, Jena, Germany
| | - Thomas Lehmann
- Centre for Clinical Studies, Jena University Hospital, Jena, Germany
| | - Ingrid Mühlhauser
- Health Sciences and Education, University of Hamburg, Hamburg, Germany
| |
Collapse
|
17
|
Dobler CC, Sanchez M, Gionfriddo MR, Alvarez-Villalobos NA, Singh Ospina N, Spencer-Bonilla G, Thorsteinsdottir B, Benkhadra R, Erwin PJ, West CP, Brito JP, Murad MH, Montori VM. Impact of decision aids used during clinical encounters on clinician outcomes and consultation length: a systematic review. BMJ Qual Saf 2018; 28:499-510. [PMID: 30301874 DOI: 10.1136/bmjqs-2018-008022] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2018] [Revised: 08/21/2018] [Accepted: 09/03/2018] [Indexed: 11/04/2022]
Abstract
BACKGROUND Clinicians' satisfaction with encounter decision aids is an important component in facilitating implementation of these tools. We aimed to determine the impact of decision aids supporting shared decision making (SDM) during the clinical encounter on clinician outcomes. METHODS We searched nine databases from inception to June 2017. Randomised clinical trials (RCTs) of decision aids used during clinical encounters with an unaided control group were eligible for inclusion. Due to heterogeneity among included studies, we used a narrative evidence synthesis approach. RESULTS Twenty-five papers met inclusion criteria including 22 RCTs and 3 qualitative or mixed-methods studies nested in an RCT, together representing 23 unique trials. These trials evaluated healthcare decisions for cardiovascular prevention and treatment (n=8), treatment of diabetes mellitus (n=3), treatment of osteoporosis (n=2), treatment of depression (n=2), antibiotics to treat acute respiratory infections (n=3), cancer prevention and treatment (n=4) and prenatal diagnosis (n=1). Clinician outcomes were measured in only a minority of studies. Clinicians' satisfaction with decision making was assessed in only 8 (and only 2 of them showed statistically significantly greater satisfaction with the decision aid); only three trials asked if clinicians would recommend the decision aid to colleagues and only five asked if clinicians would use decision aids in the future. Outpatient consultations were not prolonged when a decision aid was used in 9 out of 13 trials. The overall strength of the evidence was low, with the major risk of bias related to lack of blinding of participants and/or outcome assessors. CONCLUSION Decision aids can improve clinicians' satisfaction with medical decision making and provide helpful information without affecting length of consultation time. Most SDM trials, however, omit outcomes related to clinicians' perspective on the decision making process or the likelihood of using a decision aid in the future.
Collapse
Affiliation(s)
- Claudia Caroline Dobler
- Evidence-Based Practice Center, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA .,Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Manuel Sanchez
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Michael R Gionfriddo
- Center for Pharmacy Innovation and Outcomes, Geisinger, Forty Fort, Pennsylvania, USA
| | - Neri A Alvarez-Villalobos
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA.,Facultad de Medicina y Hospital Universitario, Unidad de Investigación Clínica, Universidad Autonoma de Nuevo León, Monterrey, Mexico
| | - Naykky Singh Ospina
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA.,Division of Endocrinology, Department of Medicine, University of Florida, Gainesville, Florida, USA
| | | | - Bjorg Thorsteinsdottir
- Evidence-Based Practice Center, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA.,Division of Primary Care Internal Medicine, Department of Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA
| | - Raed Benkhadra
- Evidence-Based Practice Center, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Colin P West
- Division of General Internal Medicine, Mayo Clinic, Rochester, Minnesota, USA.,Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, Minnesota, USA
| | - Juan P Brito
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| | - Mohammad Hassan Murad
- Evidence-Based Practice Center, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, Minnesota, USA
| | - Victor M Montori
- Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota, USA
| |
Collapse
|