A comparison of HIV health services utilization measures in a marginalized population: self-report versus medical records.

BACKGROUND

In studies examining the use of human immunodeficiency virus (HIV) health services, researchers often use subjects' self-reported measures. Agreement between a subject's self-reports and medical records in marginalized populations is uncertain, yet important to understand, as this population is disproportionately affected by HIV.

METHODS

We sought to examine agreement between self-report and medical record health care utilization measures. Using a cross-sectional study, we studied 428 unstably housed HIV-infected adults in New York City. Self-reported data were collected from Audio Computer-Assisted Self-Interviews, and medical record data from health care providers' and facilities' ambulatory medical records. Agreement for a 6-month period was compared for ambulatory visits (0, 1, >or=2), HIV medications (antiretroviral therapy, opportunistic infection prophylaxis), whether CD4 counts and viral loads were performed and their values (CD4: <200, 200-500, >500 cells/mm; Viral load: undetectable, detected).

RESULTS

Agreement between self-report and medical records was 55.2% (kappa=0.12) for visits, and 68.2-79.1% (kappa=0.27-0.48) for medications. Agreement on whether laboratory tests were performed was 62.3-65.7% (kappa=0.11-0.14), whereas agreement on laboratory values was 77.6-79.3% (kappa=0.52-0.70). Most disagreement resulted in greater number of self-reported visits, use of medications, and laboratory tests compared with medical record data.

CONCLUSIONS

Among HIV-infected marginalized individuals, agreement between self-report and medical records was poor for ambulatory visits, poor to fair for medication use, and poor for laboratory tests performed. However, agreement for CD4 count value was substantially better. These findings have implications on health services research in marginalized populations that relies only on self-report or medical record data. This study underscores the importance of understanding how self-reported and medical record data are correlated in marginalized populations.