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Early experiences with patient generated health data: health system and patient perspectives.

ABSTRACT: OBJECTIVE:Although patient generated health data (PGHD) has stimulated excitement about its potential to increase patient engagement and to offer clinicians new insights into patient health status, we know little about these efforts at scale and whether they align with patient preferences. This study sought to characterize provider-led PGHD approaches, assess whether they aligned with patient preferences, and identify challenges to scale and impact. MATERIALS AND METHODS:We interviewed leaders from a geographically diverse set of health systems (n?=?6), leaders from large electronic health record vendors (n?=?3), and leaders from vendors providing PGHD solutions to health systems (n?=?3). Next, we interviewed patients with 1 or more chronic conditions (n?=?10), half of whom had PGHD experience. We conducted content analysis to characterize health system PGHD approaches, assess alignment with patient preferences, and identify challenges. RESULTS:In this study, 3 primary approaches were identified, and each was designed to support collection of a different type of PGHD: 1) health history, 2) validated questionnaires and surveys, and 3) biometric and health activity. Whereas patient preferences aligned with health system approaches, patients raised concerns about data security and the value of reporting. Health systems cited challenges related to lack of reimbursement, data quality, and clinical usefulness of PGHD. DISCUSSION:Despite a federal policy focus on PGHD, it is not yet being pursued at scale. Whereas many barriers contribute to this narrow pursuit, uncertainty around the value of PGHD, from both patients and providers, is a primary inhibitor. CONCLUSION:Our results reveal a fairly narrow set of approaches to PGHD currently pursued by health systems at scale.

SUBMITTER: Adler-Milstein J

PROVIDER: S-EPMC7647206 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Early experiences with patient generated health data: health system and patient perspectives.

Adler-Milstein Julia J Nong Paige P

Journal of the American Medical Informatics Association : JAMIA 20191001 10

<h4>Objective</h4>Although patient generated health data (PGHD) has stimulated excitement about its potential to increase patient engagement and to offer clinicians new insights into patient health status, we know little about these efforts at scale and whether they align with patient preferences. This study sought to characterize provider-led PGHD approaches, assess whether they aligned with patient preferences, and identify challenges to scale and impact.<h4>Materials and methods</h4>We interv ...[more]

PMID: 31329886

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Project description:BackgroundPatient-generated health data (PGHD) have been largely collected through mobile health (mHealth) apps and wearable devices. PGHD can be especially helpful in mental health, as patients' illness history and symptom narratives are vital to developing diagnoses and treatment plans. However, the extent to which clinicians use mental health-related PGHD is unknown.ObjectiveA mixed methods study was conducted to understand clinicians' perspectives on PGHD and current mental health apps. This approach uses information gathered from semistructured interviews, workflow analysis, and user-written mental health app reviews to answer the following research questions: (1) What is the current workflow of mental health practice and how are PGHD integrated into this workflow, (2) what are clinicians' perspectives on PGHD and how do they choose mobile apps for their patients, (3) and what are the features of current mobile apps in terms of interpreting and sharing PGHD?MethodsThe study consists of semistructured interviews with 12 psychiatrists and clinical psychologists from a large academic hospital. These interviews were thematically and qualitatively analyzed for common themes and workflow elements. User-posted reviews of 56 sleep and mood tracking apps were analyzed to understand app features in comparison with the information gathered from interviews.ResultsThe results showed that PGHD have been part of the workflow, but its integration and use are not optimized. Mental health clinicians supported the use of PGHD but had concerns regarding data reliability and accuracy. They also identified challenges in selecting suitable apps for their patients. From the app review, it was discovered that mHealth apps had limited features to support personalization and collaborative care as well as data interpretation and sharing.ConclusionsThis study investigates clinicians' perspectives on PGHD use and explored existing app features using the app review data in the mental health setting. A total of 3 design guidelines were generated: (1) improve data interpretation and sharing mechanisms, (2) consider clinical workflow and electronic health record integration, and (3) support personalized and collaborative care. More research is needed to demonstrate the best practices of PGHD use and to evaluate their effectiveness in improving patient outcomes.

Project description:BACKGROUND:Digital innovations continue to shape health and health care. As technology socially integrates into daily living, the lives of health care consumers are transformed into a key source of health information, commonly referred to as patient-generated health data (PGHD). With chronic disease prevalence signaling the need for a refocus on primary prevention, electronic PGHD might be essential in strengthening proactive and person-centered health care. OBJECTIVE:This study aimed to review and synthesize the existing literature on the utilization and implications of electronic PGHD for primary disease prevention and health promotion purposes. METHODS:Guided by a well-accepted methodological framework for scoping studies, we screened MEDLINE, CINAHL, PsycINFO, Scopus, Web of Science, EMBASE, and IEEE Digital Library. We hand-searched 5 electronic journals and 4 gray literature sources, additionally conducted Web searches, reviewed relevant Web pages, manually screened reference lists, and consulted authors. Screening was based on predefined eligibility criteria. Data extraction and synthesis were guided by an adapted PGHD-flow framework. Beyond initial quantitative synthesis, we reported narratively, following an iterative thematic approach. Raw data were coded, thematically clustered, and mapped, allowing for the identification of patterns. RESULTS:Of 183 eligible studies, targeting knowledge and self-awareness, behavior change, healthy environments, and remote monitoring, most literature (125/183, 68.3%) addressed weight reduction, either through physical activity or nutrition, applying a range of electronic tools from socially integrated to full medical devices. Participants generated their data actively (100/183, 54.6%), in combination with passive sensor-based trackers (63/183, 34.4%) or entirely passively (20/183, 10.9%). The proportions of active and passive data generation varied strongly across prevention areas. Most studies (172/183, 93.9%) combined electronic PGHD with reflective, process guiding, motivational and educational elements, highlighting the role of PGHD in multicomponent digital prevention approaches. Most of these interventions (110/183, 60.1%) were fully automatized, underlining broader trends toward low-resource and efficiency-driven care. Only a fraction (47/183, 25.6%) of studies provided indications on the impact of PGHD on prevention-relevant outcomes, suggesting overall positive trends, especially on vitals (eg, blood pressure) and body composition measures (eg, body mass index). In contrast, the impact of PGHD on health equity remained largely unexplored. Finally, our analysis identified a list of barriers and facilitators clustered around data collection and use, technical and design considerations, ethics, user characteristics, and intervention context and content, aiming to guide future PGHD research. CONCLUSIONS:The large, heterogeneous volume of the PGHD literature underlines the topic's emerging nature. Utilizing electronic PGHD to prevent diseases and promote health is a complex matter owing to mostly being integrated within automatized and multicomponent interventions. This underlines trends toward stronger digitalization and weaker provider involvement. A PGHD use that is sensitive to identified barriers, facilitators, consumer roles, and equity considerations is needed to ensure effectiveness.

Project description:IntroductionRapidly expanding digital innovations transform the perception, reception and provision of health services. Simultaneously, health system challenges underline the need for patient-centred, empowering and citizen-engaging care, which facilitates a focus on prevention and health promotion. Through enhanced patient-engagement, patient-provider interactions and reduced information gaps, electronic patient-generated health data (PGHD) may facilitate both patient-centeredness and preventive scare. Despite that, comprehensive knowledge syntheses on their utilisation for prevention and health promotion purposes are lacking. The review described in this protocol aims to fill that gap.Methods and analysisOur methodology is guided by Arksey and O' Malley's methodological framework for scoping reviews, as well as its advanced version by Levac, Colquhoun and O'Brien. Seven electronic databases will be systematically searched using predefined keywords. Key electronic journals will be hand searched, while reference lists of included documents and grey literature sources will be screened thoroughly. Two independent reviewers will complete study selection and data extraction. One of the team's senior research members will act as a third reviewer and make the final decision on disputed documents. We will include literature with a focus on electronic PGHD and linked to prevention and health promotion. Literature on prevention that is driven by existing discomfort or disability goes beyond the review's scope and will be excluded. Analysis will be narrative and guided by Shapiro et al's adapted framework on PGHD flow.Ethics and disseminationThe scoping review described in this protocol aims to establish a baseline understanding of electronic PGHD generation, collection, communication, sharing, interpretation, utilisation, context and impact for preventive purposes. The chosen methodology is based on the use of publicly available information and does not require ethical approval. Review findings will be disseminated in digital health conferences and symposia. Results will be published and additionally shared with relevant local and national authorities.

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Early experiences with patient generated health data: health system and patient perspectives.

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Early experiences with patient generated health data: health system and patient perspectives.

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