title: Imputing HIV treatment start dates from routine laboratory data in South Africa: a validation study.
abstract: 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.
  
  
  
  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.
  
  
  
  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.
  
  
  
  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.
authors.affiliation: Heath Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
authors.forename: Mhairi
authors.initials: M
authors.lastname: Maskew
authors.affiliation: Heath Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa. jbor@bu.edu.|Department of Global Health, Boston University School of Public Health, Boston, MA, USA. jbor@bu.edu.|Africa Health Research Institute, Somkhele, South Africa. jbor@bu.edu.|Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA. jbor@bu.edu.
authors.forename: Jacob
authors.initials: J
authors.lastname: Bor
authors.affiliation: Heath Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
authors.forename: Cheryl
authors.initials: C
authors.lastname: Hendrickson
authors.affiliation: Heath Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.|Department of Global Health, Boston University School of Public Health, Boston, MA, USA.
authors.forename: William
authors.initials: W
authors.lastname: MacLeod
authors.affiliation: Africa Health Research Institute, Somkhele, South Africa.|Institute of Public Health, University of Heidelberg, Heidelberg, Germany.
authors.forename: Till
authors.initials: T
authors.lastname: Bärnighausen
authors.affiliation: Africa Health Research Institute, Somkhele, South Africa.|Division of Infection and Immunity, University College London, London, UK.
authors.forename: Deenan
authors.initials: D
authors.lastname: Pillay
authors.affiliation: Heath Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.|Department of Internal Medicine, Clinical HIV Research Unit, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.
authors.forename: Ian
authors.initials: I
authors.lastname: Sanne
authors.affiliation: National Health Laboratory Service, Johannesburg, South Africa.
authors.forename: Sergio
authors.initials: S
authors.lastname: Carmona
authors.affiliation: National Health Laboratory Service, Johannesburg, South Africa.|Department of Molecular Medicine and Hematology, University of the Witwatersrand, Johannesburg, South Africa.
authors.forename: Wendy
authors.initials: W
authors.lastname: Stevens
authors.affiliation: Heath Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa.|Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
authors.forename: Matthew P
authors.initials: MP
authors.lastname: Fox
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D019380:Anti-HIV Agents / Q000627:therapeutic use; D018791:CD4 Lymphocyte Count; D002985:Clinical Protocols; D003955:Diagnostic Tests, Routine; D005260:Female; D015658:HIV Infections / Q000188:drug therapy*; D006801:Humans; D008297:Male; D008485:Medical Audit; D008875:Middle Aged; D009313:National Health Programs; D013019:South Africa; D013997:Time Factors; D055815:Young Adult
chemical_list: D019380:Anti-HIV Agents
keywords: Antiretroviral therapy; Chronic disease management; HIV/AIDS; Health systems; Imputation; Laboratory; Missing data; Monitoring and evaluation; Resource-limited settings; South Africa; Validation