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Patient-generated data (PGD) show great promise for informing the delivery of personalized and patient-centered care. However, patients' data tracking does not automatically lead to data sharing and discussion with clinicians, which can make it difficult to utilize and derive optimal benefit from PGD. In this paper, we investigate whether and how patients share their PGD with clinicians and the types of challenges that arise within this context. We describe patients' immediate experiences of PGD sharing with clinicians, based on our short onsite interviews with 57 patients who had just met with a clinician at a university health center. Our analyses identified overarching patterns in patients' PGD sharing practices and the associated challenges that arise from the information asymmetry between patients and clinicians and from patients' reliance on their memory to share their PGD. We discuss the implications of our findings for designing PGD-integrated health IT systems in ways to support patients' tracking of relevant PGD, clinicians' effective engagement with patients around PGD, and the efficient sharing and review of PGD within clinical settings.
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This content will become publicly available on April 6, 2027
Clinician Data Needs for Uncontrolled Comorbidities of Metabolic Syndrome: Insights on Assumption Testing
To support patient care, providers need insights from patient-generated data (PGD) to help them make sense of a patient’s health condition and inform future decisions. Provider needs for PGD use vary based on the health condition being treated. Research has identified the types of insights that providers need for treating individual health conditions. However, we need further understanding of clinicians’ PGD needs for collection, interpretation, and decision-making for treating patients with comorbidities, particularly when some comorbidities are uncontrolled. We interviewed 11 providers from Federally Qualified Health Centers (FQHCs) treating patients with uncontrolled metabolic syndrome. We identify the types of clinical assessments that providers need to make based on PGD in order to treat patients, including assessing changes in the level of control of comorbidities, negative events related to control level and comorbidity type, and interference of factors across comorbidities. These needs influenced the types and frequency of PGD collection and the interpretation of trends or relations between specific types of data streams. Providers also interpreted data in light of the patient’s social determinants of health. We discuss how clinical dashboards can support providers in checking assumptions, data collection customization, and contextualization of data based on social determinants of health.
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- Award ID(s):
- 2233738
- PAR ID:
- 10688402
- Publisher / Repository:
- ACM Transactions on Computing for Healthcare
- Date Published:
- Journal Name:
- ACM Transactions on Computing for Healthcare
- ISSN:
- 2637-8051
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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