Reliability and validity of the patient activation measure in hospitalized patients

Prey, Jennifer E.; Qian, Min; Restaino, Susan; Hibbard, Judith H.; Bakken, Suzanne; Schnall, Rebecca; Rothenberg, Gloria; Vawdrey, David K.; Creber, Ruth Masterson

doi:10.1016/j.pec.2016.06.029

Cited by 68 publications

(44 citation statements)

References 28 publications

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“…[50][51][52][53][54][55][56] Our team has previously validated the PAM-13 in the inpatient setting. 57 To assess patient-identified medical errors, we asked patients to describe and categorize errors they noticed while enrolled in the trial. To assess patient satisfaction, patient engagement, perceived usefulness, and perceived ease-of-use, we adapted the Telemedicine Satisfaction and Usefulness Questionnaire.…”

Section: Measures and Data Sourcesmentioning

confidence: 99%

Technology Access, Technical Assistance, and Disparities in Inpatient Portal Use

et al. 2019

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Background Disadvantaged populations, including minorities and the elderly, use patient portals less often than relatively more advantaged populations. Limited access to and experience with technology contribute to these disparities. Free access to devices, the Internet, and technical assistance may eliminate disparities in portal use. Objective To examine predictors of frequent versus infrequent portal use among hospitalized patients who received free access to an iPad, the Internet, and technical assistance. Materials and Methods This subgroup analysis includes 146 intervention-arm participants from a pragmatic randomized controlled trial of an inpatient portal. The participants received free access to an iPad and inpatient portal while hospitalized on medical and surgical cardiac units, together with hands-on help using them. We used logistic regression to identify characteristics predictive of frequent use. Results More technology experience (adjusted odds ratio [OR] = 5.39, p = 0.049), less severe illness (adjusted OR = 2.07, p = 0.077), and private insurance (adjusted OR = 2.25, p = 0.043) predicted frequent use, with a predictive performance (area under the curve) of 65.6%. No significant differences in age, gender, race, ethnicity, level of education, employment status, or patient activation existed between the frequent and infrequent users in bivariate analyses. Significantly more frequent users noticed medical errors during their hospital stay. Discussion and Conclusion Portal use was not associated with several sociodemographic characteristics previously found to limit use in the inpatient setting. However, limited technology experience and high illness severity were still barriers to frequent use. Future work should explore additional strategies, such as enrolling health care proxies and improving usability, to reduce potential disparities in portal use.

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Section: Measures and Data Sourcesmentioning

confidence: 99%

Technology Access, Technical Assistance, and Disparities in Inpatient Portal Use

et al. 2019

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“…Consistent with other research, 7 we categorized patient activation as low (levels I and II) or high (levels III and IV). Self-care behavior related to HF was measured with the use of the European Heart Failure Self-Care Behavior Scale (EHFSC-9), a 9-item measure with scores that range from 9 to 45 (lower scores indicating better self-care).…”

Section: Methodsmentioning

confidence: 75%

“…7 PAM scores range from 0 to 100 (higher scores indicating higher activation) and are converted to 4 levels and labeled as follows: 1) Disengaged and overwhelmed, 2) Becoming aware, but still struggling, 3) Taking action, and 4) Maintaining behaviors and pushing further. 8 …”

Section: Methodsmentioning

confidence: 99%

Brief Report: Patient Activation Among Urban Hospitalized Patients With Heart Failure

Creber

Chen

Chao

et al. 2017

Journal of Cardiac Failure

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Background Patient activation influences patients’ ability to meaningfully engage in critical heart failure self-care. The purpose of this study was to identify whether patient activation is associated with patient-reported health outcomes in an urban and racially diverse inpatient sample of patients with heart failure. Methods We prospectively recruited patients with heart failure hospitalized at an urban academic medical center from October 2016 to May 2017 and measured patient activation, physical and affective symptoms, physical function, self-care, perceived control, and self-efficacy. Differences in patient-reported health outcomes between low and high activation groups were compared with the use of linear regression models adjusting for age, sex, education, left ventricular ejection fraction, and New York Heart Association functional classification. Results A total of 96 patients completed the study (mean age 57 ± 12.4 y); 39% identified as black and 35% as Latino, 35% were female, and 50% reported not having enough income to make ends meet. Based on the 4 levels of activation defined by the Patient Activation Measure–13, 22% of patients reported being “disengaged and overwhelmed,” 14% were “becoming aware, but still struggling,” 39% were “taking action,” and 26% were “maintaining behaviors and pushing further.” Higher patient activation was associated with better applied cognitive abilities, self-care behaviors, perceived control, and self-efficacy. Conclusion Patient activation can be easily measured in hospitalized patients with heart failure and is associated with clinically meaningful patient-reported health outcomes.

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“…Two variables contained in the "holistic framework" may be particularly relevant for future research seeking to gain clarity on predictors of unscheduled healthcare use in childhood asthma. These are: (1) provider-patient/family communication regarding asthma management (factor of extrinsic socioecological influences at the health system/organizational level); and (2) patient/family activation in asthma management (factor of intrinsic self-agency) [16][17][18][19][20][21][22][23]. These variables are particularly important for future research efforts, not only because they have been emphasized by national evidence based (NHLBI) asthma management guidelines, but also because they are directly relevant to increasing provider engagement in promoting asthma SME.…”

Section: Implications For Practice and Future Researchmentioning

confidence: 99%

Demographic and Risk-Factor Differences between Users and Non-Users of Unscheduled Healthcare among Pediatric Outpatients with Persistent Asthma

Rangachari

Griffin

Ghosh

et al. 2020

IJERPH

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This study assesses differences between users and non-users of unscheduled healthcare for persistent childhood asthma, with regard to select demographic and risk factors. The objectives are to provide important healthcare utilization information and a foundation for future research on self-management effectiveness (SME), informed by a recently developed "holistic framework" for measuring SME in childhood asthma. An 18-month retrospective chart review was conducted on 59 pediatric outpatients with persistent asthma-mild, moderate, or severe, to obtain data on various demographic and risk factors, and healthcare use for each child. The study examined five types of "unscheduled" healthcare use. Users had non-zero encounters (at least one) in any of the five types; non-users had zero encounters (not even one) in all five types. Differences between users and non-users were assessed using contingency table and logistic regression analysis. There were 25 users and 34 non-users of unscheduled healthcare. Each severity category contained users and non-users. The only statistically significant finding was that the mild persistent category had fewer users than severe persistent (p < 0.05). There were no significant differences between users and non-users for any other demographic or risk factor examined. After adjusting for asthma severity, there were no other significant differences between users and non-users of unscheduled healthcare. This is a crucial finding which suggests that something else is driving unscheduled healthcare use in these children, given there were users and non-users in each asthma severity category. These results provide impetus for future research on the role of other aspects of the "holistic framework" in explaining differences in uses of unscheduled healthcare in persistent childhood asthma. 12 of 12 21. Zandbelt, L.C.; Smets, E.M.; Oort, F.J.; Godfried, M.H.; Haes, H.C. Medical specialists' patient-centered communication and patient-reported outcomes. Med. Care 2007, 45, 330-339. [CrossRef] [PubMed] 22. Zill, J.M.; Christalle, E.; Müller, E.; Härter, M.; Dirmaier, J.; Scholl, I. Measurement of Physician-Patient Communication-A Systematic Review. PLoS ONE 2014, 9, e112637. [CrossRef] [PubMed] 23. Zolnierek, K.B.H.; DiMatteo, M.R. Physician communication and patient adherence to treatment: A meta-analysis. Med. Care 2009, 47, 826-834. [CrossRef] [PubMed] © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

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Reliability and validity of the patient activation measure in hospitalized patients

Cited by 68 publications

References 28 publications

Technology Access, Technical Assistance, and Disparities in Inpatient Portal Use

Technology Access, Technical Assistance, and Disparities in Inpatient Portal Use

Brief Report: Patient Activation Among Urban Hospitalized Patients With Heart Failure

Demographic and Risk-Factor Differences between Users and Non-Users of Unscheduled Healthcare among Pediatric Outpatients with Persistent Asthma

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