A Quantitative Framework for Medication Non-Adherence: Integrating Patient Treatment Expectations and Preferences.
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2023-01
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Abstract
Introduction
Medication non-adherence remains a significant challenge in healthcare, impacting treatment outcomes and the overall effectiveness of medical interventions. This article introduces a novel approach to understanding and predicting medication non-adherence by integrating patient beliefs, efficacy expectations, and perceived costs. Existing theoretical models often fall short in quantifying the impact of barrier removal on medication adherence and struggle to address cases where patients consciously choose not to follow prescribed medication regimens. In response to these limitations, this study presents an empirical framework that seeks to provide a quantifiable model for both individual and population-level prediction of non-adherence under different scenarios.Methods
We present an empirical framework that includes a health production function, specifically applied to antihypertensive medications nonadherence. Data collection involved a pilot study that utilized a double-bound contingent-belief (DBCB) questionnaire. Through this questionnaire, participants could express how efficacy and side effects were affected by controlled levels of non-adherence, allowing for the estimation of sensitivity in health outcomes and costs.Results
Parameters derived from the DBCB questionnaire revealed that on average, patients with hypertension anticipated that treatment efficacy was less sensitive to non-adherence than side effects. Our derived health production function suggests that patients may strategically manage adherence to minimize side effects, without compromising efficacy. Patients' inclination to manage medication intake is closely linked to the relative importance they assign to treatment efficacy and side effects. Model outcomes indicate that patients opt for full adherence when efficacy outweighs side effects. Our findings also indicated an association between income and patient expectations regarding the health of antihypertensive medications.Conclusion
Our framework represents a pioneering effort to quantitatively link non-adherence to patient preferences. Preliminary results from our pilot study of patients with hypertension suggest that the framework offers a viable alternative for evaluating the potential impact of interventions on treatment adherence.Type
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Muiruri, Charles, Eline M van den Broek-Altenburg, Hayden B Bosworth, Crystal W Cené and Juan Marcos Gonzalez (2023). A Quantitative Framework for Medication Non-Adherence: Integrating Patient Treatment Expectations and Preferences. Patient preference and adherence, 17. pp. 3135–3145. 10.2147/ppa.s434640 Retrieved from https://hdl.handle.net/10161/29587.
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Scholars@Duke
Charles Muiruri
Dr. Muiruri is a health services researcher, Assistant Professor in the Duke Department of Population Health Sciences, Assistant Research Professor in the Global Health Institute, and Adjunct lecturer at the Kilimanjaro Christian Medical University College, Moshi Tanzania.
Broadly, his research seeks to improve the quality of healthcare and reduce disparities for persons with multiple chronic conditions both in and outside the United States. His current work focuses on prevention of nonAIDS comorbidities among people living with HIV. His current projects funded by NIAID, NHLBI and NIMHD focus on improving the quality of cardiovascular disease prevention and care among people living with HIV in North Carolina and Tanzania.
Areas of Expertise: Mixed methods, Qualitative methods, Applied Econometrics in Health services Research, Preference research, Implementation Science, Global Health, Health Policy
Hayden Barry Bosworth
Dr. Bosworth is a health services researcher and Deputy Director of the Center of Innovation to Accelerate Discovery and Practice Transformation (ADAPT) at the Durham VA Medical Center. He is also Vice Chair of Education and Professor of Population Health Sciences. He is also a Professor of Medicine, Psychiatry, and Nursing at Duke University Medical Center and Adjunct Professor in Health Policy and Administration at the School of Public Health at the University of North Carolina at Chapel Hill. His research interests comprise three overarching areas of research: 1) clinical research that provides knowledge for improving patients’ treatment adherence and self-management in chronic care; 2) translation research to improve access to quality of care; and 3) eliminate health care disparities.
Dr. Bosworth is the recipient of an American Heart Association established investigator award, the 2013 VA Undersecretary Award for Outstanding Achievement in Health Services Research (The annual award is the highest honor for VA health services researchers), and a VA Senior Career Scientist Award. In terms of self-management, Dr. Bosworth has expertise developing interventions to improve health behaviors related to hypertension, coronary artery disease, and depression, and has been developing and implementing tailored patient interventions to reduce the burden of other chronic diseases. These trials focus on motivating individuals to initiate health behaviors and sustaining them long term and use members of the healthcare team, particularly pharmacists and nurses. He has been the Principal Investigator of over 30 trials resulting in over 400 peer reviewed publications and four books. This work has been or is being implemented in multiple arenas including Medicaid of North Carolina, private payers, The United Kingdom National Health System Direct, Kaiser Health care system, and the Veterans Affairs.
Areas of Expertise: Health Behavior, Health Services Research, Implementation Science, Health Measurement, and Health Policy
Juan Marcos Gonzalez
Dr. Gonzalez is an Associate Professor in the Department of Population Health Sciences. He is an expert in the design of stated-preference survey instruments and the use of advanced statistical tools to analyze stated-preference data. His research has focused on the transparency in benefit-risk evaluations of medical interventions, and the elicitation of health preferences from multiple stakeholders to support shared decision making.
Dr. Gonzalez co-led the first FDA-sponsored preference study which was highlighted in FDA’s recent precedent-setting guidance for submitting patient-preference evidence to inform regulatory benefit-risk evaluations of new medical devices. More recently, Dr. Gonzalez collaborated with the Medical Devices Innovation Consortium (MDIC) to prepare the first catalog of preference-elicitation methods (part of the Patient-Centered Benefit-Risk Assessment Framework) suitable for benefit-risk assessments of medical devices. As a core group member of the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Conjoint Analysis Task Force, Dr. Gonzalez helped draft good-practice recommendations for statistical analysis, interpretation, and reporting of health preference data. Currently, he is working with the Center for Devices and Radiological Health at FDA to support the Center’s capabilities for the review of stated-preference data in regulatory decisions.
Areas of expertise: Clinical Decision Sciences and Health Measurement
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