Using vital registration data to update mortality among patients lost to follow-up from ART programmes: evidence from the Themba Lethu Clinic, South Africa

Trop Med Int Health. 2010 Apr;15(4):405-13. doi: 10.1111/j.1365-3156.2010.02473.x. Epub 2010 Feb 17.

Abstract

Objective: To estimate the rates of mortality in patients lost to follow-up (LTFU) from a large urban public sector HIV clinic in South Africa.

Methods: We compared vital status using the clinic's database to vital status verified against the Vital Registration system at the South African Department of Home Affairs. We compared rates of mortality before and after updating mortality data. Predictors of mortality were estimated using Kaplan-Meier curves and proportional hazard regression.

Results: Of the 7097 total patients who initiated highly active antiretroviral therapy at Themba Lethu Clinic by October 1st, 2008 and had an ID number, 6205 were included. 2453 patients (21%) were LTFU, of whom 1037 (42.3%) could be included in the analysis. After matching to the vital registration system, mortality more than doubled from 4.2% (258/6205) to 10.9% (676/6205). Overall 37% of those LTFU died by life-table analysis the probability of survival amongst those LTFU was 69% (95% CI: 66-72%), 64% (95% CI: 61-67%) and 59% (95% CI: 55-62%) by years 1, 2 and 3 since being lost, respectively. Those at highest risk of death after being lost were patients with a history of tuberculosis, CD4 count < 100 cells/microl, BMI < 17.5, haemoglobin < 10 and on <6 months of treatment.

Conclusion: Mortality was substantially underestimated among patients lost from a South African HIV treatment programme despite limited active tracing. Linking to vital registration systems can provide more accurate assessments of programme effectiveness and target lost patients most at risk for mortality.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adult
  • Anti-Retroviral Agents / therapeutic use*
  • Cohort Studies
  • Data Collection / methods*
  • Female
  • HIV Infections / drug therapy
  • HIV Infections / mortality*
  • Humans
  • Kaplan-Meier Estimate
  • Male
  • Patient Dropouts / statistics & numerical data
  • Proportional Hazards Models
  • Registries*
  • Risk Factors
  • South Africa / epidemiology
  • Urban Population

Substances

  • Anti-Retroviral Agents