Measuring the outcomes of using person-generated health data: a case study of developing a PROM item bank

The Association of Learning Health System Practicing Hospitals and other Health Information Interested Hospitals with Patient-Generated Health Data Uptake

Patient generated health data (PGHD) has been described as a necessary addition to provider-generated information for improving care processes in US hospitals. This study evaluated the distribution of Health Information Interested (HII) US hospitals that are more likely to capture or use PGHD. The literature suggests that HII hospitals are more likely to capture and use PGHD. Cross-sectional analysis of the 2018 American Hospital Association's (AHA) health-IT-supplement and other supporting datasets showed that HII hospitals collectively and majority of HII hospital subcategories evaluated were associated with increased PGHD capture and use. The full Learning Health System (LHS) hospital subcategory had the highest association and hospitals in the meaningful use stage three compliant (MU3) and PCORI funded subcategory also had higher rates of PGHD capture or use when in combination with LHS hospitals. Hence, being LHS appears to be the strongest practice and policy lever to increase PGHD capture and use.

'We are very individual': anticipated effects on stroke survivors of using their person-generated health data

BACKGROUND

Person-generated health data (PGHD) are produced by people when they use health information technologies. People who use PGHD may experience changes in their health and care process, such as engagement with their own healthcare, and their sense of social support and connectedness. Research into evaluating those reported effects has not kept up; thus, a method for measuring PGHD outcomes was previously designed and applied to the exemplar case of Kinect-based stroke rehabilitation systems. A key step of the method ensures that the patient's voice is included. Allowing stroke survivors to participate in the development and evaluation of health services and treatment can inform healthcare providers on decisions about stroke care, and thereby improve health outcomes.

OBJECTIVE

This paper presents the perspectives of stroke survivors and clinicians on the anticipated effects of stroke survivors' use of PGHD from a poststroke simulated rehabilitation technology.

METHODS

This study gathered the perspectives of stroke survivors and clinicians through three focus groups and three interviews, recruited for convenience. Participants were also asked questions intended to encourage them to comment on the initial items of the patient-reported outcome measure-PGHD. Deductive thematic analysis was performed.

RESULTS

This paper has further demonstrated that outcomes of using PGHD can be measured. For instance, stroke survivors described that using PGHD could result in positive, negative and nil effects on their health behaviours. Survivors and clinicians had varying perspectives in three of the six themes presented, and emphasise the importance of allowing stroke survivors to participate in the evaluation of digital health services.

Enabling Better Use of Person-Generated Health Data in Stroke Rehabilitation Systems: Systematic Development of Design Heuristics

BACKGROUND

An established and well-known method for usability assessment of various human-computer interaction technologies is called heuristic evaluation (HE). HE has been adopted for evaluations in a wide variety of specialized contexts and with objectives that go beyond usability. A set of heuristics to evaluate how health information technologies (HITs) incorporate features that enable effective patient use of person-generated health data (PGHD) is needed in an era where there is a growing demand and variety of PGHD-enabled technologies in health care and where a number of remote patient-monitoring technologies do not yet enable patient use of PGHD. Such a set of heuristics would improve the likelihood of positive effects from patients' use of PGHD and lower the risk of negative effects.

OBJECTIVE

This study aims to describe the development of a set of heuristics for the design and evaluation of how well remote patient therapeutic technologies enable patients to use PGHD (PGHD enablement). We used the case of Kinect-based stroke rehabilitation systems (K-SRS) in this study.

METHODS

The development of a set of heuristics to enable better use of PGHD was primarily guided by the R3C methodology. Closer inspection of the methodology reveals that neither its development nor its application to a case study were described in detail. Thus, where relevant, each step was grounded through best practice activities in the literature and by using Nielsen's heuristics as a basis for determining the new set of heuristics. As such, this study builds on the R3C methodology, and the implementation of a mixed process is intended to result in a robust and credible set of heuristics.

RESULTS

A total of 8 new heuristics for PGHD enablement in K-SRS were created. A systematic and detailed process was applied in each step of heuristic development, which bridged the gaps described earlier. It is hoped that this would aid future developers of specialized heuristics, who could apply the detailed process of heuristic development for other domains of technology, and additionally for the case of PGHD enablement for other health conditions. The R3C methodology was also augmented through the use of qualitative studies with target users and domain experts, and it is intended to result in a robust and credible set of heuristics, before validation and refinement.

CONCLUSIONS

This study is the first to develop a new set of specialized heuristics to evaluate how HITs incorporate features that enable effective patient use of PGHD, with K-SRS as a key case study. In addition, it is the first to describe how the identification of initial HIT features and concepts to enable PGHD could lead to the development of a specialized set of heuristics.

Patient-Reported Outcome Measures of Utilizing Person-Generated Health Data in the Case of Simulated Stroke Rehabilitation: Development Method

BACKGROUND

Person-generated health data (PGHD) are health data that people generate, record, and analyze for themselves. Although the health benefits of PGHD use have been reported, there is no systematic way for patients to measure and report the health effects they experience from using their PGHD. Patient-reported outcome measures (PROMs) allow patients to systematically self-report their outcomes of a health care service. They generate first-hand evidence of the impact of health care services and are able to reflect the real-world diversity of actual patients and management approaches. Therefore, this paper argues that a PROM of utilizing PGHD, or PROM-PGHD, is necessary to help build evidence-based practice in clinical work with PGHD.

OBJECTIVE

This paper aims to describe a method for developing PROMs for people who are using PGHD in conjunction with their clinical care-PROM-PGHD, and the method is illustrated through a case study.

METHODS

The five-step qualitative item review (QIR) method was augmented to guide the development of a PROM-PGHD. However, using QIR as a guide to develop a PROM-PGHD requires additional socio-technical consideration of the PGHD and the health technologies from which they are produced. Therefore, the QIR method is augmented for developing a PROM-PGHD, resulting in the PROM-PGHD development method.

RESULTS

A worked example was used to illustrate how the PROM-PGHD development method may be used systematically to develop PROMs applicable across a range of PGHD technology types used in relation to various health conditions.

CONCLUSIONS

This paper describes and illustrates a method for developing a PROM-PGHD, which may be applied to many different cases of health conditions and technology categories. When applied to other cases of health conditions and technology categories, the method could have broad relevance for evidence-based practice in clinical work with PGHD.