A Record Linkage Protocol for a Diabetes Registry at Ethnically Diverse Community Health Centers
- Correspondence and reprints to: Neil Maizlish, PhD, MPH, Community Health Center Network, 1320 Harbor Bay Parkway, Suite 250, Alameda, CA 94502; e-mail: <neilm{at}chcn-eb.org>
- Received 13 September 2004
- Accepted 30 December 2004
Abstract
Community health centers serve ethnically diverse populations that may pose challenges for record linkage based on name and date of birth. The objective was to identify an optimal deterministic algorithm to link patient encounters and laboratory results for hemoglobin A1c testing and examine its variability by health center site, patient ethnicity, and other variables. Based on data elements of last name, first name, date of birth, gender, and health center site, matches with ≥50% to < 100% of a maximum score were manually reviewed for true matches. Match keys based on combinations of name substrings, date of birth, gender, and health center were used to link encounter and laboratory files. The optimal match key was the first two letters of the last name and date of birth, which had a sensitivity of 92.7% and a positive predictive value of 99.5%. Sensitivity marginally varied by health center, age, gender, but not by ethnicity. An algorithm that was inexpensive, accurate, and easy to implement was found to be well suited for population-based measurement of clinical quality.
Footnotes
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Supported by the Agency for Healthcare Research and Quality (1 R21 HS013543-01).
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The CHCN Claims Department is acknowledged for their contribution of the F2 key and Ray Otake for bringing this information to the authors' attention. Khati Hendry provided insightful comments during the development of this project. Dr. Joseph Selby (Kaiser Permanente) is acknowledged for technical assistance in carrying out the literature review.
Protection of human subjects in research was approved for this project by the IRB of Kaiser Permanente-North.
Neil Maizlish was responsible for the design, analysis, and writing of this report. Linda Herrera contributed to the design, data collection, analysis, and revision of this report.
