Record linkage without patient identifiers: proof of concept using data from South Africa's national HIV program.

Background: Linkage between health databases typically requires identifiers such as patient names and personal identification numbers. We developed and validated a record linkage strategy to combine administrative health databases without the use of patient identifiers, with application to South Africa's public sector HIV treatment program. Methods: We linked CD4 counts and HIV viral loads from South Africa's HIV clinical monitoring database (TIER.Net) and the National Health Laboratory Service (NHLS) for patients receiving care between 2015-2019 in Ekurhuleni District (Gauteng Province). We used a combination of variables related to lab results contained in both databases (result value; specimen collection date; facility of collection; patient year and month of birth; and sex). Exact matching linked on exact linking variable values while caliper matching applied exact matching with linkage on approximate test dates (± 5 days). We then developed a sequential linkage approach utilising specimen barcode matching, then exact matching, and lastly caliper matching. Performance measures were sensitivity and positive predictive value (PPV); share of patients linked across databases; and percent increase in data points for each linkage approach. Results: We attempted to link 2,017,290 lab results from TIER.Net (representing 523,558 unique patients) and 2,414,059 lab results from the NHLS database. Linkage performance was evaluated using specimen barcodes (available for a minority of records in TIER.net) as a "gold standard". Exact matching achieved a sensitivity of 69.0% and PPV of 95.1%. Caliper-matching achieved a sensitivity of 75.7% and PPV of 94.5%. In sequential linkage, we matched 41.9% of TIER.Net labs by specimen barcodes, 51.3% by exact matching, and 6.8% by caliper matching, for a total of 71.9% of labs matched, with PPV=96.8% and Sensitivity = 85.9%. The sequential approach linked 86.0% of TIER.Net patients with at least one lab result to the NHLS database (N=1,450,087). Linkage to the NHLS Cohort increased the number of laboratory results associated with TIER.Net patients by 62.6%. Conclusions: Linkage of TIER.Net and NHLS without patient identifiers attained high accuracy and yield without compromising patient privacy. The integrated cohort provides a more complete view of patients' lab history and could yield more accurate estimates of HIV program indicators.