In: BMC Health Services Research, 17 (2017), Nr. 41. pp. 1-9. ISSN 1472-6963

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PDF, English Download (913kB) | Lizenz: Imputing HIV treatment start dates from routine laboratory data in South Africa: a validation study by Maskew, Mhairi ; Bor, Jacob ; Hendrickson, Cheryl ; MacLeod, William ; Bärnighausen, Till ; Pillay, Deenan ; Sanne, Ian ; Carmona, Sergio ; Stevens, Wendy ; Fox, Matthew P. underlies the terms of Creative Commons Attribution 3.0 Germany

Abstract

Background: Poor clinical record keeping hinders health systems monitoring and patient care in many low resource settings. We develop and validate a novel method to impute dates of antiretroviral treatment (ART) initiation from routine laboratory data in South Africa’s public sector HIV program. This method will enable monitoring of the national ART program using real-time laboratory data, avoiding the error potential of chart review. Methods: We developed an algorithm to impute ART start dates based on the date of a patient’s “ART workup”, i.e. the laboratory tests used to determine treatment readiness in national guidelines, and the time from ART workup to initiation based on clinical protocols (21 days). To validate the algorithm, we analyzed data from two large clinical HIV cohorts: Hlabisa HIV Treatment and Care Programme in rural KwaZulu-Natal; and Right to Care Cohort in urban Gauteng. Both cohorts contain known ART initiation dates and laboratory results imported directly from the National Health Laboratory Service. We assessed median time from ART workup to ART initiation and calculated sensitivity (SE), specificity (SP), positive predictive value (PPV), and negative predictive value (NPV) of our imputed start date vs. the true start date within a 6 month window. Heterogeneity was assessed across individual clinics and over time. Results: We analyzed data from over 80,000 HIV-positive adults. Among patients who had a workup and initiated ART, median time to initiation was 16 days (IQR 7,31) in Hlabisa and 21 (IQR 8,43) in RTC cohort. Among patients with known ART start dates, SE of the imputed start date was 83% in Hlabisa and 88% in RTC, indicating this method accurately predicts ART start dates for about 85% of all ART initiators. In Hlabisa, PPV was 95%, indicating that for patients with a lab workup, true start dates were predicted with high accuracy. SP (100%) and NPV (92%) were also very high. Conclusions: Routine laboratory data can be used to infer ART initiation dates in South Africa’s public sector. Where care is provided based on protocols, laboratory data can be used to monitor health systems performance and improve accuracy and completeness of clinical records.