JMIR Publications

ABSTRACT

Background:

In the US, patients can access their EHR data from a given provider through a patient portal. However, current patient portals are mainly focused on a single provider, with very limited data sharing capabilities and put low emphasis on independent sensemaking of the EHR data. This makes it very challenging for patients to switch between different portals and aggregate the data to obtain a complete picture of their medical history and to make sense of it. Due to this fragmentation, patients are exposed to numerous inconveniences such as medical errors, repeated tests, and limited self-advocacy.

Objective:

To overcome the above limitations of EHR patient portals, we designed and developed Discovery - a web application that aggregates EHR data from multiple providers and presents it to the patient for efficient exploration and sensemaking. To learn how well Discovery meets the patients’ sensemaking needs and what features should such applications include, we conducted an evaluation study.

Methods:

We conducted a qualitative evaluation study with 14 participants. In a 60 min session and relying on the think-aloud protocol, participants were asked to complete a variety of sensemaking tasks and provided feedback upon completion. The audio materials were transcribed for analysis and the video recordings of the users’ interactions with Discovery were annotated to provide additional context. These combined textual data was thematically analyzed to surface themes that reflect how participants utilized Discovery’s features, what sensemaking of their EHR data really entails, and what features are desirable to support that process better.

Results:

We found that Discovery provided much needed features and could be used in a variety of everyday scenarios, especially for preparing and during clinical visits, but also for raising awareness, reflection and planning. According to the study participants, Discovery provided a robust set of features for supporting independent exploration and sensemaking of their EHR data: summary and quick overview of the data, finding prevalence, periodicity, co-occurrence, and pre-post of medical events, as well as comparing Record types and subtypes across providers. Additionally, we extracted important design implications from the user feedback on data exploration with multiple views and non-standard UI elements.

Conclusions:

Patient-facing sensemaking support tools like Discovery should have a core set of features that can be learnt quickly and support the most common use cases for a variety of users. The user should be able to detect time-oriented patterns of medical events and get enough explanation and context on demand for making sense of the individual medical records. All that should be achieved with language easily understandable to the user in a single exploration view that feels familiar, warm and positive, and has enough “plasticity” to adjust to the user’s information needs as the exploration unfolds.