Integrating Patient-Generated Health Data Into Clinical Care Settings or Clinical Decision-Making: Lessons Learned From Project HealthDesign

Abstract

BackgroundPatient-generated health data (PGHD) are health-related data created or recorded by patients to inform their self-care and understanding about their own health. PGHD is different from other patient-reported outcome data because the collection of data is patient-driven, not practice- or research-driven. Technical applications for assisting patients to collect PGHD supports self-management activities such as healthy eating and exercise and can be important for preventing and managing disease. Technological innovations (eg, activity trackers) are making it more common for people to collect PGHD, but little is known about how PGHD might be used in outpatient clinics.ObjectiveThe objective of our study was to examine the experiences of health care professionals who use PGHD in outpatient clinics.MethodsWe conducted an evaluation of Project HealthDesign Round 2 to synthesize findings from 5 studies funded to test tools designed to help patients collect PGHD and share these data with members of their health care team. We conducted semistructured interviews with 13 Project HealthDesign study team members and 12 health care professionals that participated in these studies. We used an immersion-crystallization approach to analyze data. Our findings provide important information related to health care professionals’ attitudes toward and experiences with using PGHD in a clinical setting.ResultsHealth care professionals identified 3 main benefits of PGHD accessibility in clinical settings: (1) deeper insight into a patient’s condition; (2) more accurate patient information, particularly when of clinical relevance; and (3) insight into a patient’s health between clinic visits, enabling revision of care plans for improved health goal achievement, while avoiding unnecessary clinic visits. Study participants also identified 3 areas of consideration when implementing collection and use of PGHD data in clinics: (1) developing practice workflows and protocols related to PGHD collection and use; (2) data storage, accessibility at the point of care, and privacy concerns; and (3) ease of using PGHD data.ConclusionsPGHD provides value to both patients and health care professionals. However, more research is needed to understand the benefit of using PGHD in clinical care and to identify the strategies and clinic workflow needs for optimizing these tools.

Five key strategic priorities of integrating patient generated health data into United Kingdom electronic health records

“…Information presentation of PGHD in clinical systems is likely to pose the biggest challenge, as clinical users can feel overwhelmed being presented with large amounts of unsolicited data in electronic systems, which may distract clinicians and result in patient harm 38 – 40. This is complicated by the variety of stakeholders and different resulting data needs – each provider will need different contextualised information depending on the task at hand 16…”

“…However, this means that important opportunities for intervention may be missed. It is, therefore, critical to draw on the existing human factors literature to build an evidence base surrounding technical functionality and associated perceived value to individual users across settings 40. Work surrounding alert fatigue in clinical decision support systems may also offer valuable insights in relation to designing information presentation 41.…”

Long‐Term Nursing Home Entry: A Prognostic Model for Older Adults with a Family or Unpaid Caregiver

“…Having a clearer understanding of what factors affect risk of NH entry is particularly important and timely at this juncture because of population aging, efforts to promote community living, and promulgation of alternative payment programs that create incentives to understand and mitigate nonmedical risk factors that contribute to service use . The diffusion of risk prediction tools in clinical software and electronic medical records along with consumer‐generated electronic data capture make it increasingly possible to incorporate a broader set of factors into risk prediction, such as information available from family caregivers . Although many people require short‐term postacute care in a nursing facility, long‐term NH entry is a less common event that is highly concentrated in persons with disability.…”

“…14 The diffusion of risk prediction tools in clinical software and electronic medical records along with consumer-generated electronic data capture make it increasingly possible to incorporate a broader set of factors into risk prediction, such as information available from family caregivers. 15,16 Although many people require short-term postacute care in a nursing facility, long-term NH entry is a less common event that is highly concentrated in persons with disability. The availability of a prognostic model could facilitate more effective targeting of supports to delay or avert this outcome.…”

Present and Future Trends in Consumer Health Informatics and Patient-Generated Health Data

“…Cohen et al conducted semi-structured interviews to examine the experiences of health care professionals who use PGHD in an outpatient clinical setting [16]. The identified benefits included a deeper understanding of a patient's conditions, the availability of more accurate patient information, and the ability to monitor patient's health between clinic visits.…”