What The Evidence Shows About Patient Activation: Better Health Outcomes And Care Experiences; Fewer Data On Costs

Health Affairs (Impact Factor: 4.97). 02/2013; 32(2):207-14. DOI: 10.1377/hlthaff.2012.1061
Source: PubMed


Patient engagement is an increasingly important component of strategies to reform health care. In this article we review the available evidence of the contribution that patient activation-the skills and confidence that equip patients to become actively engaged in their health care-makes to health outcomes, costs, and patient experience. There is a growing body of evidence showing that patients who are more activated have better health outcomes and care experiences, but there is limited evidence to date about the impact on costs. Emerging evidence indicates that interventions that tailor support to the individual's level of activation, and that build skills and confidence, are effective in increasing patient activation. Furthermore, patients who start at the lowest activation levels tend to increase the most. We conclude that policies and interventions aimed at strengthening patients' role in managing their health care can contribute to improved outcomes and that patient activation can-and should-be measured as an intermediate outcome of care that is linked to improved outcomes.

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Available from: Judith Hibbard, Oct 02, 2015
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    • "Patient activation specifies the level of patients' engagement [1] [2] and may contribute to better self-management [3], higher engagement in treatment [2] [3], and greater patient satisfaction [4] [5]. Patient activation is in addition associated with better health outcomes [2]. The Patient Activation Measure-13 (PAM-13), developed by Hibbard et al. [4] from the 22-item version [1], ascertains health engagement and thereby self-reported knowledge, skills, behaviours and confidence for self-management of health and chronic diseases. "
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    ABSTRACT: The Patient Activation Measure-13 (PAM-13) has been found useful for assessing patient knowledge, skills and confidence in management of chronic conditions, but the empirical evidence from mental health is sparse. The psychometric properties of PAM in out-patients waiting for treatment in community mental health centers (CMHC) have therefore been examined. A total of 290 adults from two CMHC completed PAM. An exploratory factor analysis was conducted with 273 patients. Data at baseline and after 4 weeks were used to analyze test-retest reliability (n=60) and to analyze the sensitivity to change (n=51). The exploratory factor analysis revealed a fit for a two-factor model (Cronbach's α was 0.86 and 0.67), and was assessed for a one-factor model (α=0.87). The test-retest intraclass correlation coefficient was 0.76. Sensitivity to change was good with a statistically significant activation improvement (p<0.001) on patients receiving a peer co-led-educational intervention (Cohen's d was 0.85). PAM has appropriate and acceptable psychometric properties in mental health settings. Assessing activation before treatment might be useful for scheduling the delivery of mental health services as well as evaluating educational interventions aimed at improving patient engagement in mental health. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
    Patient Education and Counseling 06/2015; 39. DOI:10.1016/j.pec.2015.06.009 · 2.20 Impact Factor
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    • "The study of Hibbard and Greene (2013) also suggests that it is possible to influence patients to become more active. In contrast to active patients, less active patients are associated with higher costs of health care (Hibbard et al., 2013). Many of the proponents of increasing the amount of personal responsibility taken by patients see the patient access to their medical records as a significant precondition of the anticipated healthcare revolution (e.g., Munir & Boaden, 2001; Sittig, 2002; Joubert et al., 2007; Gaunt, 2009; Hoerbst et al., 2010; Ammenwerth et al., 2012). "
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    ABSTRACT: Better knowledge of the habits and preferences of patients helps one understand why and how patients might need or want to access health services online and offline. Such knowledge provides a basis for designing systems for providing complementary health information. This article discusses how patients' conceptualizations of their health-information-related preferences, motivations, and needs are linked to the perceived role of medical records as an informational artifact. We identified seven subject positions: (P1) Hypothetically positive to e-health services generally, (P2) Positive to reading medical records due to implications, (P3) Positive to all Internet use including medical records online, (P4) Distrustful and wants to be in control of health treatment, (P5) Worried about health, (P6) Wants communication with health care professionals, and (P7) Do not understand their medical record. These subject positions can explain the worry and enthusiasm documented in earlier literature. The diversity of subject positions implies that health care information services should be planned with different subject positions in mind rather than a simple demographic group. Special attention needs to be given to finding flexible solutions that address the opportunities and worries of the identified subject positions.
    Journal of the Association for Information Science and Technology 05/2015; DOI:10.1002/asi.23343 · 2.23 Impact Factor
    • "Thus, depending on which survey instrument is implemented, program administrators are faced with the prospect of either losing entire observations or calculating scores that may be quite inaccurate, when any items on the survey are missing. The patient activation measure (PAM) is a 13-question survey instrument that is gaining increased attention because of efforts to increase patient self-management with the goal of improving health outcomes and reducing cost [3]. The PAM assesses patient knowledge, skills, and confidence for selfmanagement and has been demonstrated to be both valid and reliable for patients with and without chronic illnesses [4] [5]. "
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    ABSTRACT: The Patient Activation Measure (PAM) is an increasingly popular instrument used as the basis for interventions to improve patient engagement and as an outcome measure to assess intervention effect. However, when there are missing responses, the PAM uses extrapolation in scoring that may lead to substantial measurement error. In this paper, measurement error is systematically estimated across the full possible range of missing items (one to twelve), using simulation in which populated items were randomly replaced with missing data for each of 1,138 complete surveys obtained in a randomized controlled trial. The PAM score was then calculated using extrapolation, followed by comparisons of overall simulated average mean, minimum and maximum PAM scores to the true PAM score in order to assess the absolute percentage error (APE) for each comparison. With only one missing item, the average APE was 2.5% comparing the true PAM score to the simulated minimum score, and 4.3% compared to the simulated maximum score. APEs increased with additional missing items, such that surveys with 12 missing items had average APEs of 29.7% (minimum) and 44.4% (maximum). Several suggestions and alternative approaches are offered that could be pursued to improve measurement accuracy when responses are missing.
    BioMed Research International 03/2015; 2015(3). DOI:10.1155/2015/270168 · 2.71 Impact Factor
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