Enhancing Doctor-Patient Communication Through Self-tracking Data Sharing

Role: Project lead

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Example of patient generated data: A patient used Adobe Illustrator to create a medical timeline, and brought the printed version when visiting to a new doctor. The peach color represents gastrointestinal symptoms, and the blue represents Myasthenia Gravis.

Summary

Background: Patients are tracking and generating an increasingly large volume of personal health data outside the clinic due to the burgeoning development and availability of wearable sensing and mobile health (mHealth) apps. The potential usefulness of these data is enormous as they can provide good measures of everyday behavior and lifestyle. However, how we can fully leverage patient-generated data (PGD) and integrate them in clinical practice is less clear.

Goal: We aim to understand how patients and clinicians currently share patient-generated data in clinical care practice. So that we can gain insight on design technological intervention to enhance the sharing of PGD between patients and clinicians.

Method: We conducted semi-structured interviews with 9 clinicians and 12 patients, and utilized qualitative open coding to analyze the data.

Results: From the study, we identified technical, social, and organizational challenges in sharing and fully leveraging patient-generated data in clinical practices.

Contribution: Our findings can provide researchers potential avenues for enablers and barriers in sharing patient-generated data in clinical settings.

Self-tracking & Patient-Generated Data

Tracking can be categorized as Manual or Automated. Manual tracking includes digital, and manual journaling. Automated tracking includes: consumer health tracking devices, and medical devices. etc.

Definition of "PGD": We define Patient-Generated Data (PGD) as health-related data created, recorded, or gathered by patients (or by family members or other caregivers) to help address their health concerns. These data include physical activity, sleep, food, and blood glucose levels. They can be collected using manual journaling, consumer health tracking devices, smartphone apps, or medical devices (e.g., blood glucose meter). In addition, PGD includes any independent lab results or tests ordered by the patients themselves (e.g. ubiome, 23andMe, and LabCorp).

Example of patient-generated data. On the left, a patient used excel spreadsheets to track her health data. On the right, the other patient created a software that generates graphs to show the correlations of certain fitness data, such as Fitbit steps, Aerobic time, and weight.

Challenges in Patient-Clinician Data Sharing

Results

Clinician-Initiated vs. Patient-Initiated Tracking: Most of the clinician participants had experienced patients bringing their data to visits and sharing it voluntarily. We observed that clinicians’ receptiveness to PGD varied depending on who initiated the tracking. When clinicians initiated the tracking, it was often the case that they required PGD for a specific medical reasoning, thereby the value of the data was high. In these instances, patients became a “diagnostic agent” for clinicians, and thus played an active role in personal diagnoses. Patient-initiated tracking, however, was not always welcome by clinicians.

How is PGD Shared: Patients tracked factors such as exercise, treatment changes or medically relevant factors, food, alcohol, caffeine consumption, travel and lifestyle, symptoms and ailments, weight, period data, sleep and sleep patterns, test results, general health history, and chronic or persistent health problems (e.g., diabetes, high blood pressure). We examined how data is shared among patients and clinicians by employing the space-time matrix. According to the space-time matrix, PGD sharing can be categorized based on where it occurs (distributed vs. co-located) and when it occurs (synchronous vs. asynchronous).

Space-time matrix

In the paper, we analyze various PGD sharing practices based on space-time matrix, and described existing tensions between clinicians and patients, which discouraged the sharing of data, as well as barriers and enablers to leveraging PGD.

Suggestions

1. It is important to align the clinicians’ and patients’ perceptions about PGD as closely as possible.
2. Although PGD could have immense value for patient care, clinicians cannot effectively use this data until it is integrated into the clinical systems.
3. Clinicians need to be incentivized to incorporate PGD into their everyday workflows.
4. Clinicians need to understand and adapt to the cultural shift in healthcare, in which more patients are attempting to make healthcare a collaborative endeavor.

Conclusion

In this study, we described the current practices of PGD sharing among patients and clinicians. We particularly examined the differences between tracking initiated by clinicians versus patients. We then employed the space-time matrix to analyze various PGD sharing practices. After describing tensions between clinicians and patients, we identified barriers and enablers to PGD sharing. Many of the barriers were related to the lack of infrastructural support for data integration, but this was not merely a technological issue; a bigger challenge was how PGD sharing could be incorporated into clinicians’ workflow. Most of these barriers can compound to further inhibit patient-clinician communications. Understanding a clear picture of how PGD is currently shared and its associated challenges are important for the design of systems that can leverage PGD and integrate the data into clinical practices. This initial study provides new opportunities to study PGD sharing between patients and clinicians with better focus on the significant issues we identified. We are particularly interested in how information visualization can be designed to aid efficient data sharing. With the ever-increasing growth of personal health mobile applications and wearable sensors, patient generated data will only increase. We are only starting to understand the challenges that we need to address to integrate this data into the healthcare process.