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      Ethical Aspects of Physician Decision-Making for Deprescribing Among Older Adults With Dementia

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          Key Points

          Question

          Do physicians prioritize different ethical considerations when considering deprescribing medications for older adults (aged ≥65 years) with dementia?

          Findings

          In this national survey study of 890 primary care physicians, 9 factors influencing deprescribing decisions for older adults with dementia were prioritized. When a medication may increase risk of an adverse drug event or have limited benefit as a treatment, physicians are sensitive to concerns that deprescribing would worsen symptoms, are more reluctant to deprescribe a medication started by someone else, and less concerned about the cost of medication.

          Meaning

          Results of this survey study suggest that managing symptoms and well-being and working with other clinicians are priorities for clinicians managing medications for older adults with dementia.

          Abstract

          Importance

          Physicians endorse deprescribing of risky or unnecessary medications for older adults (aged ≥65 years) with dementia, but there is a lack of information on what influences decisions to deprescribe in this population.

          Objective

          To understand how physicians make decisions to deprescribe for older adults with moderate dementia and ethical and pragmatic concerns influencing those decisions.

          Design, Setting, and Participants

          A cross-sectional national mailed survey study of a random sample of 3000 primary care physicians from the American Medical Association Physician Masterfile who care for older adults was conducted from January 15 to December 31, 2021.

          Main Outcomes and Measures

          The study randomized participants to consider 2 clinical scenarios in which a physician may decide to deprescribe a medication for older adults with moderate dementia: 1 in which the medication could cause an adverse drug event if continued and the other in which there is no evidence of benefit. Participants ranked 9 factors related to possible ethical and pragmatic concerns through best-worst scaling methods (from greatest barrier to smallest barrier to deprescribing). Conditional logit regression quantified the relative importance for each factor as a barrier to deprescribing.

          Results

          A total of 890 physicians (35.0%) returned surveys; 511 (57.4%) were male, and the mean (SD) years since graduation was 26.0 (11.7). Most physicians had a primary specialty in family practice (50.4% [449 of 890]) and internal medicine (43.5% [387 of 890]). A total of 689 surveys were sufficiently complete to analyze. In both clinical scenarios, the 2 greatest barriers to deprescribing were (1) the patient or family reporting symptomatic benefit from the medication (beneficence and autonomy) and (2) the medication having been prescribed by another physician (autonomy and nonmaleficence). The least influential factor was ease of paying for the medication (justice).

          Conclusions and Relevance

          Findings from this national survey study of primary care physicians suggests that understanding ethical aspects of physician decision-making can inform clinician education about medication management and deprescribing decisions for older adults with moderate dementia.

          Abstract

          This survey study of primary care physicians assesses the prioritization of different ethical considerations when considering deprescribing medications for older adults with dementia.

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          Most cited references48

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            Reducing inappropriate polypharmacy: the process of deprescribing.

            Inappropriate polypharmacy, especially in older people, imposes a substantial burden of adverse drug events, ill health, disability, hospitalization, and even death. The single most important predictor of inappropriate prescribing and risk of adverse drug events in older patients is the number of prescribed drugs. Deprescribing is the process of tapering or stopping drugs, aimed at minimizing polypharmacy and improving patient outcomes. Evidence of efficacy for deprescribing is emerging from randomized trials and observational studies. A deprescribing protocol is proposed comprising 5 steps: (1) ascertain all drugs the patient is currently taking and the reasons for each one; (2) consider overall risk of drug-induced harm in individual patients in determining the required intensity of deprescribing intervention; (3) assess each drug in regard to its current or future benefit potential compared with current or future harm or burden potential; (4) prioritize drugs for discontinuation that have the lowest benefit-harm ratio and lowest likelihood of adverse withdrawal reactions or disease rebound syndromes; and (5) implement a discontinuation regimen and monitor patients closely for improvement in outcomes or onset of adverse effects. Whereas patient and prescriber barriers to deprescribing exist, resources and strategies are available that facilitate deliberate yet judicious deprescribing and deserve wider application.
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              Best--worst scaling: What it can do for health care research and how to do it.

              Statements like "quality of care is more highly valued than waiting time" can neither be supported nor refuted by comparisons of utility parameters from a traditional discrete choice experiment (DCE). Best--worst scaling can overcome this problem because it asks respondents to perform a different choice task. However, whilst the nature of the best--worst task is generally understood, there are a number of issues relating to the design and analysis of a best--worst choice experiment that require further exposition. This paper illustrates how to aggregate and analyse such data and using a quality of life pilot study demonstrates how richer insights can be drawn by the use of best--worst tasks.
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                Author and article information

                Journal
                JAMA Netw Open
                JAMA Netw Open
                JAMA Network Open
                American Medical Association
                2574-3805
                3 October 2023
                October 2023
                3 October 2023
                : 6
                : 10
                : e2336728
                Affiliations
                [1 ]Johns Hopkins University School of Medicine, Baltimore, Maryland
                [2 ]Institute for Health Research, Kaiser Permanente Colorado, Aurora
                [3 ]Department of Family Medicine, University of Colorado School of Medicine, Aurora
                [4 ]Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Melbourne, Victoria, Australia
                [5 ]Quality Use of Medicines and Pharmacy Research Centre, Clinical and Health Sciences, University of South Australia, Adelaide, South Australia
                [6 ]University of Colorado Center for Bioethics and Humanities, Anschutz Medical Campus, Aurora
                [7 ]Department of Internal Medicine, University of Colorado School of Medicine, Aurora
                [8 ]Department of Health Policy and Management, Colorado School of Public Health, Aurora
                [9 ]RCSI Hospitals Group, Connolly Hospital, Dublin, Ireland
                Author notes
                Article Information
                Accepted for Publication: August 27, 2023.
                Published: October 3, 2023. doi:10.1001/jamanetworkopen.2023.36728
                Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2023 Norton JD et al. JAMA Network Open.
                Corresponding Author: Cynthia M. Boyd, MD, MPH, 5200 Eastern Ave, Mason F. Lord Building, Center Tower, Room 317, Baltimore, MD 21224 ( cyboyd@ 123456jhmi.edu ).
                Author Contributions: Drs Boyd and Bayliss had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
                Concept and design: Norton, Bayliss, Reeve, Wynia, Drace, Sheehan, Boyd.
                Acquisition, analysis, or interpretation of data: Norton, Zeng, Bayliss, Shetterly, Williams, Reeve, Green, Gleason, Sheehan, Boyd.
                Drafting of the manuscript: Norton.
                Critical review of the manuscript for important intellectual content: All authors.
                Statistical analysis: Zeng, Shetterly.
                Obtained funding: Bayliss, Reeve, Boyd.
                Administrative, technical, or material support: Norton, Williams, Drace, Sheehan.
                Supervision: Bayliss, Sheehan, Boyd.
                Conflict of Interest Disclosures: Mr Norton reported receiving grants from the National Institute on Aging (NIA) during the conduct of the study. Dr Bayliss reported grants from NIA R33AG057289 during the conduct of the study. Ms Shetterly reported grants from the NIA during the conduct of the study. Ms Williams reported grants from the NIA during the conduct of the study. Dr Reeve reported grants from the NIA R33-AG057289, R33-AG057289-S1, grants from the National Health and Medical Research Council–Australian Research Council (NHMRC-ARC) Dementia Research Development Fellowship (GNT1105777), and grants from NHMRC investigator grant (GNT1195460) during the conduct of the study; and royalties from UpToDate for writing a chapter on deprescribing outside the submitted work. Dr Green reported grants from the NIA and grants from the NIA Impact Collaboratory outside the submitted work. Dr Boyd reported grants from NIA during the conduct of the study; other from UpToDate royalty chapter on multimorbidity outside the submitted work. No other disclosures were reported.
                Funding/Support: This study was supported by NIA grants R33-AG057289 and R33-AG057289-S1. Dr Green was also supported by NIA K23 AG054742. Dr Boyd was also supported by NIA K24 AG 05657. Dr Reeve is supported by a NHMRC-ARC Dementia Research Development Fellowship (APP1105777).
                Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
                Data Sharing Statement: See Supplement 2.
                Article
                zoi231061
                10.1001/jamanetworkopen.2023.36728
                10548310
                37787993
                c76dab1d-847f-4a5e-a809-e57c3d5879ae
                Copyright 2023 Norton JD et al. JAMA Network Open.

                This is an open access article distributed under the terms of the CC-BY License.

                History
                : 16 February 2023
                : 27 August 2023
                Categories
                Research
                Original Investigation
                Online Only
                Geriatrics

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