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Open Access 01-12-2017 | Technical advance

Imputing HIV treatment start dates from routine laboratory data in South Africa: a validation study

Authors: Mhairi Maskew, Jacob Bor, Cheryl Hendrickson, William MacLeod, Till Bärnighausen, Deenan Pillay, Ian Sanne, Sergio Carmona, Wendy Stevens, Matthew P Fox

Published in: BMC Health Services Research | Issue 1/2017

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.

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This adjustment factor follows directly from Bayes Theorem, which says that PPV = sensitivity * Pr(ART)/Pr(workup). For example: if 100 patients have a lab work-up at a given clinic, then we expect that 95.4 of these patients will initiate ART within six months. However, those 95.4 patients represent only the 82.6% of ART initiators who also had a workup. Dividing by 82.6% yields an estimate of 115 total ART initiators at the clinic.

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Title: Imputing HIV treatment start dates from routine laboratory data in South Africa: a validation study
Authors: Mhairi Maskew
Jacob Bor
Cheryl Hendrickson
William MacLeod
Till Bärnighausen
Deenan Pillay
Ian Sanne
Sergio Carmona
Wendy Stevens
Matthew P Fox
Publication date: 01-12-2017
Publisher: BioMed Central
Published in: BMC Health Services Research / Issue 1/2017
Electronic ISSN: 1472-6963
DOI: https://doi.org/10.1186/s12913-016-1940-2

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Imputing HIV treatment start dates from routine laboratory data in South Africa: a validation study

Abstract

Background

Methods

Results

Conclusions

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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