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      Patient-Centered Care, Yes; Patients As Consumers, No

      1 , 2 , 3
      Health Affairs
      Health Affairs (Project Hope)

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          Understanding patients' experiences of treatment burden in chronic heart failure using normalization process theory.

          Our goal was to assess the burden associated with treatment among patients living with chronic heart failure and to determine whether Normalization Process Theory (NPT) is a useful framework to help describe the components of treatment burden in these patients. We performed a secondary analysis of qualitative interview data, using framework analysis, informed by NPT, to determine the components of patient "work." Participants were 47 patients with chronic heart failure managed in primary care in the United Kingdom who had participated in an earlier qualitative study about living with this condition. We identified and examined data that fell outside of the coding frame to determine if important concepts or ideas were being missed by using the chosen theoretical framework. We were able to identify and describe components of treatment burden as distinct from illness burden using the framework. Treatment burden in chronic heart failure includes the work of developing an understanding of treatments, interacting with others to organize care, attending appointments, taking medications, enacting lifestyle measures, and appraising treatments. Factors that patients reported as increasing treatment burden included too many medications and appointments, barriers to accessing services, fragmented and poorly organized care, lack of continuity, and inadequate communication between health professionals. Patient "work" that fell outside of the coding frame was exclusively emotional or spiritual in nature. We identified core components of treatment burden as reported by patients with chronic heart failure. The findings suggest that NPT is a theoretical framework that facilitates understanding of experiences of health care work at the individual, as well as the organizational, level. Although further exploration and patient endorsement are necessary, our findings lay the foundation for a new target for treatment and quality improvement efforts toward patient-centered care.
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            Choice Inconsistencies Among the Elderly: Evidence from Plan Choice in the Medicare Part D Program.

            We evaluate the choices of elders across their insurance options under the Medicare Part D Prescription Drug plan, using a unique data set of prescription drug claims matched to information on the characteristics of choice sets. We document that elders place much more weight on plan premiums than on expected out of pocket costs; value plan financial characteristics beyond any impacts on their own financial expenses or risk; and place almost no value on variance reducing aspects of plans. Partial equilibrium welfare analysis implies that welfare would have been 27% higher if patients had all chosen rationally.
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              The Clinical Application of the Biopsychosocial Model

              G Engel (1981)
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                Author and article information

                Journal
                Health Affairs
                Health Affairs
                Health Affairs (Project Hope)
                0278-2715
                1544-5208
                March 2019
                March 2019
                : 38
                : 3
                : 368-373
                Affiliations
                [1 ]Michael K. Gusmano () is an associate professor of health policy at Rutgers University, in Piscataway Township, New Jersey, and a research scholar at the Hastings Center, a nonprofit bioethics research institute in Garrison, New York.
                [2 ]Karen J. Maschke is a research scholar at the Hastings Center.
                [3 ]Mildred Z. Solomon is president of the Hastings Center and professor, part time, in the Department of Global Health and Social Medicine, Harvard Medical School, in Boston, Massachusetts.
                Article
                10.1377/hlthaff.2018.05019
                30830817
                088d80e8-e645-4dda-a04d-8048bf23ee79
                © 2019
                History

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