JMIR Publications

ABSTRACT

Background:

Children (aged 0-14 years) living with HIV (CLH) often have lower rates of HIV diagnosis, treatment, and viral load suppression. In Haiti only 63% of CLH know their HIV status (compared to 85% overall), 63% are on treatment (compared to 85% overall), and 48% are virally suppressed (compared to 73% overall). Electronic medical records (EMRs) can improve HIV care and patients, but these benefits are largely predicated on providers having access to high quality data.

Objective:

We hypothesize that data missingness will be associated with greater interruption in ART treatment (IIT) and that this relationship will be larger among CLH.

Methods:

We assessed associations between patient intake record data missingness and IIT status at 6- and 12-months post ART initiation using patient-level data drawn from iSante, the most widely used EMR in Haiti. Missingness was assessed for TB stage, WHO HIV stage, and weight using a composite score indicator (number of indicators missing). Effect estimates were marginal parameters from multilevel modified Poisson models with robust error variances and random intercepts for facility to account for clustering.

Results:

Data were drawn from 50 facilities and comprised 31,457 people living with HIV (PLH) patient records, of which 1,306 (4.2%) were pediatric. Pediatric patients were more likely than adult patients to experience IIT (33.0% vs. 23.4% at 6 months, P<.001) and their patient records had higher data missingness (55.5% of pediatric records had no indicators of interest missing, compared to 74.1% of adult records, P<0.001). Among pediatric patients, each one additional indicator missing was associated with 1.34 times greater likelihood of being IIT at 6 months (95% confidence interval [CI]=1.08–1.66, P=.008) and 1.24 times greater likelihood of being IIT at 12 months (95% CI=1.05–1.46, P=.010). These relationships were not statistically significant for adult patients. Compared to pediatric patients with zero missing indicators, pediatric patients with one, two, or three missing indicators were 1.59 (95% CI=1.26–2.01, P<.001), 1.74 (95% CI=1.02–2.97, P=.041), and 2.25 (95% CI=1.43–3.56, P=.001) times more likely to be IIT at 6 months, respectively. Among adult patients, compared to patients with zero indicators missing, having all three indicators missing was associated with being 1.32 times more likely to be IIT at 6 months (95% CI=1.03–1.70, P=.030), while there was not association with IIT status for the other levels of missingness.

Conclusions:

These findings suggest that improving EMR data quality may enable better quality of care and lead to greater care and treatment engagement. Efforts to improve data quality should consider prioritizing pediatric patients.