Patient perspectives on the linkage of health data for research: Insights from an online patient community questionnaire.

OBJECTIVE: To examine the patient perspective on the risks and benefits of linking existing data sources for research. MATERIALS AND METHODS: Between December 2015 and February 2016, we fielded a questionnaire in PatientsLikeMe, an online patient community representing over 2500 health conditions. The questionnaire was developed using subject matter expertise and patient feedback from a concept elicitation phase (N = 57 patients). The final questionnaire consisted of 37 items. RESULTS: Of n = 5741 who opened the email invitation, n = 3516 respondents completed the questionnaire (61.2%). Of these, 73.8% were women, 86.4% were Caucasian, 14.5% were 65 or older, and 44.9% had completed college or post-graduate education. Questionnaire respondents indicated that the most important benefits of sharing data were "helping my doctor make better decisions about my health" (94%) and "helping make new therapies available faster" (94%). The most important data sharing risk identified was health data being "stolen by hackers" (87%). Of 693 patients who were not comfortable with researchers accessing their de-identified data, most reported that their comfort levels would increase if they were able to learn how their data was protected (84%). In general, responders felt more comfortable when unique identifiers such as social security number (90%) and insurance ID (82%) were removed from the data for linkage and research use. DISCUSSION: The majority of patients in a US-based online community are comfortable with researchers accessing their de-identified data for research purposes. CONCLUSIONS: Developing methods to link databases minimizing the exposure of unique identifiers may improve patient comfort levels with linking data for research purposes.

Duke Scholars

Author Emily O'Brien Population Health Sciences

Author Laura Eve Schanberg Pediatrics, Rheumatology

Author Sean Michael O'Brien Biostatistics & Bioinformatics, Division of Biostatistics