Abstract
BACKGROUND: Strengthened regulations concerning privacy of health information are affecting large-scale health outcomes research.
OBJECTIVE: To create a data collection system that would facilitate outcomes research, avoid selection bias, and fulfill obligations to protect privacy.
DESIGN: We created a web-based system that uses touch-screen computer technology for longitudinal collection of data. The system provides access to information in deidentified form, enables it to be linked to health services and outcomes data, and allows patients to join a research registry project (RRP) and be placed on a prospective subject list (PSL).
PARTICIPANTS, MEASUREMENTS, AND RESULTS: Pilot testing in 86 consecutive patients who were seen at a large, urban, university-based general medicine practice and had a mean age of 50 years showed that 81 patients had no difficulty, 5 had some difficulty, and none had considerable difficulty using the computer technology to complete a health survey. No patients refused to complete the survey and all patients completed the entire survey. Forty-seven (55%) joined the RRP and 42 of these 47 (89%) joined the PSL. RRP participants were less likely than RRP nonparticipants to be divorced or widowed (P=.03) and less likely to have hypertension (P=.03) but had no other significant differences in sociodemographic or clinical characteristics. PSL participants did not differ from PSL nonparticipants.
CONCLUSIONS: The new system ensures privacy and appears to facilitate research recruitment and avoid selection bias.
References
Health Insurance Portability and Acountability Act. 1996.
Department of Health and Human Services. Standards for privacy of individually identifiable health information; proposed rule. The Federal Register. 1999;64:59918–60065.
Woolf SHL, et al. Selection bias from requiring patients to give consent to examine data for health services research. Arch Fam Med. 2000;9:1111–8.
Kennedy L, Craig AM. Global registries for measuring pharmacoeconomic and quality-of-life outcomes: focus on design and data collection, analysis and interpretation. Pharmacoeconomics. 2004;22:551–68.
Hays RD, Morales LS. The RAND-36 measure of health-related quality of life. Ann Med. 2001;33:350–7.
Hays RD. RAND 36: Health Status Inventory. 1st ed. San Antonio, TX: The Psychological Corporation; 1998:126.
Quinn J, Durski K. A real-time tracking, notification, and web-based enrollment system for emergency department research. Acad Emerg Med. 2004;11:1245–8.
Matthews KA, Kelsey SF, Meilahn EN, Kuller LH, Wing RR. Educational attainment and behavioral and biologic risk factors for coronary heart disease in middle-aged women. Am J Epidemiol. 1989;129:1132–44.
Sowers M. SWAN: a multicenter, multiethnic, community-based cohort study of women and the menopausal transition. In: Lobo RA, Kelsey J, Marcus R, eds. Menopause: Biology and Pathobiology. San Diego: Academic Press; 2000:672.
Pradhan AD, Manson JE, Rossouw JE, et al. Inflammatory biomarkers, hormone replacement therapy, and incident coronary heart disease: prospective analysis from the women’s health initiative observational study. JAMA. 2002;288:980–7.
Bliven BD, Kaufman SE, Spertus JA. Electronic collection of health-related quality of life data: validity, time benefits, and patient preference. Qual Life Res. 2001;10:15–22.
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The authors have no conflicts of interest to declare for this article or this research.
During the time of this work, Dr. Hess was supported by a Veteran’s Administration Special Fellowship in Women’s Health.
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Hess, R., Matthews, K., McNeil, M. et al. Brief report: Health services research in the privacy age. J GEN INTERN MED 20, 1045–1049 (2005). https://doi.org/10.1111/j.1525-1497.2005.0227.x
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DOI: https://doi.org/10.1111/j.1525-1497.2005.0227.x