Improving Patient Engagement Through Patient Decision Support

Published:December 03, 2020DOI:
      During the past decade, patient engagement has been the buzz phrase of health information technology, with dozens of vendors offering text message interventions, smartphone applications (apps), electronic patient portals, and other patient-facing software innovations. These technologies crunch data to deliver targeted health advice and promise better outcomes, lower costs, and higher satisfaction. However, a closer look at the burgeoning and diverse array of patient-facing technologies reveals that each operationalizes patient engagement differently. The label is applied to innovations as different as text reminders, chatbots, paper brochures, and health maintenance apps. What is the common denominator that constitutes patient engagement? What is the goal with engaging patients or what should it be?
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        • Carman KL
        • Dardess P
        • Maurer M
        • et al.
        Patient and family engagement: a framework for understanding the elements and developing interventions and policies.
        Health Aff (Millwood). 2013; 32: 223-231
        • Osheroff JA
        • Teich JM
        • Levick D
        • et al.
        Improving Outcomes With Clinical Decision Support: An Implementer's Guide.
        2nd ed. Healthcare Information and Management Systems Society, New York, NY2012
      1. U.S. Food and Drug Administration. Clinical and patient decision support software: draft guidance for industry and Food and Drug Administration staff. Silver Spring, MD: U.S. Food and Drug Administration. Published December 8, 2017. Accessed August 14, 2020.

        • Coulter A
        Engaging Patients in Healthcare.
        McGraw Hill Education, New York, NY2011
      2. Institute of Medicine, Olsen LA, Saunders RS, et al. Engaging patients to improve science and value in a learning health system. In: Patients Charting the Course: Citizen Engagement in the Learning Health System: Workshop Summary. Washington, DC: National Academies Press; 2011:95–118. Accessed August 14, 2020.

        • Hibbard JH
        • Mahoney ER
        • Stockard J
        • Tusler M
        Development and testing of a short form of the patient activation measure.
        Health Serv Res. 2005; 40: 1918-1930
        • Greene J
        • Hibbard JH
        Why does patient activation matter? An examination of the relationships between patient activation and health-related outcomes.
        J Gen Intern Med. 2012; 27: 520-526
        • Stacey D
        • Légaré F
        • Lewis K
        • et al.
        Decision aids for people facing health treatment or screening decisions.
        Cochrane Database Syst Rev. 2017; 4CD001431
        • Witteman HO
        • Zikmund-Fisher BJ
        Communicating laboratory results to patients and families.
        Clin Chem Lab Med. 2019; 57: 359-364
        • Zikmund-Fisher BJ
        Helping people know whether measurements have good or bad implications: increasing the evaluability of health and science data communications.
        Policy Insights Behav Brain Sci. 2019; 6: 29-37
        • Zikmund-Fisher BJ
        • Scherer AM
        • Witteman HO
        • et al.
        Graphics help patients distinguish between urgent and non-urgent deviations in laboratory test results.
        J Am Med Inform Assoc. 2017; 24: 520-528
        • Gaglio B
        • Shoup JA
        • Glasgow RE
        The RE-AIM framework: a systematic review of use over time.
        Am J Public Health. 2013; 103: e38-e46
        • Dukhanin V
        • Topazian R
        • DeCamp M
        Metrics and evaluation tools for patient engagement in healthcare organization - and system-level decision-making: a systematic review.
        Int J Health Policy Manag. 2018; 7: 889-903
        • Coiera E
        When conversation is better than computation.
        J Am Med Inform Assoc. 2000; 7: 277-286
        • Leventhal H
        • Phillips LA
        • Burns E
        The Common-Sense Model of Self-Regulation (CSM): a dynamic framework for understanding illness self-management.
        J Behav Med. 2016; 39: 935-946
        • Galesic M
        • Garcia-Retamero R
        Graph literacy: a cross-cultural comparison.
        Med Decis Making. 2011; 31: 444-457
        • Reading Turchioe M
        • Grossman LV
        • Myers AC
        • Baik D
        • Goyal P
        • Masterson Creber RM
        Visual analogies, not graphs, increase patients’ comprehension of changes in their health status.
        J Am Med Inform Assoc. 2020; 27: 677-689
        • van der Sijs H
        • Aarts J
        • Vulto A
        • Berg M
        Overriding of drug safety alerts in computerized physician order entry.
        J Am Med Inform Assoc. 2006; 13: 138-147
        • Capozza K
        • Woolsey S
        • Georgsson M
        • et al.
        Going mobile with diabetes support: a randomized study of a text message-based personalized behavioral intervention for type 2 diabetes self-care.
        Diabetes Spectr. 2015; 28: 83-91
        • Ancker JS
        • Mauer E
        • Hauser D
        • Calman N
        Expanding access to high-quality plain-language patient education information through context-specific hyperlinks.
        AMIA Annu Symp Proc. 2017; 2016: 277-284
        Date accessed: August 14, 2020
        • Veinot TC
        • Mitchell H
        • Ancker JS
        Good intentions are not enough: how informatics interventions can worsen inequality.
        J Am Med Inform Assoc. 2018; 25: 1080-1088
        • Ancker JS
        • Nosal S
        • Hauser D
        • Way C
        • Calman N
        Access policy and the digital divide in patient access to medical records.
        Health Policy Technol. 2017; 6: 3-11