BackgroundRobust technology infrastructure is needed to enable learning health care systems to improve quality, access, and cost. Such infrastructure relies on the trust and confidence of individuals to share their health data for healthcare and research. Few studies have addressed consumers’ views on electronic data sharing and fewer still have explored the dual purposes of healthcare and research together. The objective of the study is to explore factors that affect consumers’ willingness to share electronic health information for healthcare and research.MethodsThis study involved a random-digit dial telephone survey of 800 adult Californians conducted in English and Spanish. Logistic regression was performed using backward selection to test for significant (p-value ≤ 0.05) associations of each explanatory variable with the outcome variable.ResultsThe odds of consent for electronic data sharing for healthcare decreased as Likert scale ratings for EHR impact on privacy worsened, odds ratio (OR) = 0.74, 95% CI [0.60, 0.90]; security, OR = 0.80, 95% CI [0.66, 0.98]; and quality, OR = 0.59, 95% CI [0.46–0.75]. The odds of consent for sharing for research was greater for those who think EHR will improve research quality, OR = 11.26, 95% CI [4.13, 30.73]; those who value research benefit over privacy OR = 2.72, 95% CI [1.55, 4.78]; and those who value control over research benefit OR = 0.49, 95% CI [0.26, 0.94].ConclusionsConsumers’ choices about electronically sharing health information are affected by their attitudes toward EHRs as well as beliefs about research benefit and individual control. Design of person-centered interventions utilizing electronically collected health information, and policies regarding data sharing should address these values of importance to people. Understanding of these perspectives is critical for leveraging health data to support learning health care systems.

Background: During the COVID-19 pandemic, telemedicine use rapidly and dramatically increased for management of diabetes mellitus. It is unknown whether access to telemedicine care has been equitable during this time. This study aimed to identify patient-level factors associated with adoption of telemedicine for subspecialty diabetes care during the pandemic. Methods: We conducted an explanatory sequential mixed-methods study using data from a single academic medical center. We used multivariate logistic regression to explore associations between telemedicine use and demographic factors for patients receiving subspecialty diabetes care between March 19 and June 30, 2020. We then surveyed a sample of patients who received in-person care to understand why these patients did not use telemedicine. Results: Among 1292 patients who received subspecialty diabetes care during the study period, those over age 65 were less likely to use telemedicine (OR: 0.34, 95% CI: 0.22-0.52, P < .001), as were patients with a primary language other than English (OR: 0.53, 95% CI: 0.31-0.91, P = .02), and patients with public insurance (OR: 0.64, 95% CI: 0.49-0.84, P = .001). Perceived quality of care and technological barriers were the most common reasons cited for choosing in-person care during the pandemic. Conclusions: Our findings suggest that, amidst the COVID-19 pandemic, there have been disparities in telemedicine use by age, language, and insurance for patients with diabetes mellitus. We anticipate telemedicine will continue to be an important care modality for chronic conditions in the years ahead. Significant work must therefore be done to ensure that telemedicine services do not introduce or widen population health disparities.

BackgroundThere exists a challenge of understanding and integrating various types of data collected to support the health of individuals with multiple chronic conditions engaging in cancer care. Data visualization has the potential to address this challenge and support personalized cancer care.ObjectiveThe aim of the study was to assess the health care practitioners’ perceptions of and feedback regarding visualizations developed to support the care of individuals with multiple chronic conditions engaging in cancer care.MethodsMedical doctors (n=4) and registered nurses (n=4) providing cancer care at an academic medical center in the western United States provided feedback on visualization mock-ups. Mock-up designs were guided by current health informatics and visualization literature and the Munzner Nested Model for Visualization Design. User-centered design methods, a mock patient persona, and a scenario were used to elicit insights from participants. Directed content analysis was used to identify themes from session transcripts. Means and SDs were calculated for health care practitioners’ rankings of overview visualizations.ResultsThemes identified were data elements, supportive elements, confusing elements, interpretation, and use of visualization. Overall, participants found the visualizations useful and with the potential to provide personalized care. Use of color, reference lines, and familiar visual presentations (calendars, line graphs) were noted as helpful in interpreting data.ConclusionsVisualizations guided by a framework and literature can support health care practitioners’ understanding of data for individuals with multiple chronic conditions engaged in cancer care. This understanding has the potential to support the provision of personalized care.