Assessment of facility-based tuberculosis data quality in an integrated HIV/TB database in three South African districts

Abstract

Background Assessment of data quality is essential to successful monitoring & evaluation of tuberculosis (TB) services. South Africa uses the Three Interlinked Electronic Register (TIER.Net) to monitor TB diagnoses and treatment outcomes. We assessed the quality of routine programmatic data as captured in TIER.Net. Methods We reviewed 277 records from routine data collected for adults who had started TB treatment for drug-sensitive (DS-) TB between 10/2018-12/2019 from 15 facilities across three South African districts using three sources and three approaches to link these (i.e., two approaches compared TIER.NET with the TB Treatment Record while the third approach compared all three sources of TB data: the TB treatment record or patient medical file; the TB Identification Register; and the TB module in TIER.Net). We report agreement and completeness of demographic information and key TB-related variables across all three data sources. Results In our first approach we selected 150 patient records from TIER.Net and found all but one corresponding TB Treatment Record (99%). In our second approach we were also able to find a corresponding TIER.Net record from a starting point of the paper-based, TB Treatment Record for 73/75 (97%) records. We found fewer records 55/75 (73%) in TIER.Net when we used as a starting point records from the TB Identification Register. Demographic information (name, surname, date of birth, and gender) was accurately reported across all three data sources (matching 90% or more). The reporting of key TB-related variables was similar across both the TB Treatment Record and the TB module in TIER.Net (p>0.05). We observed differences in completeness and moderate agreement (Kappa 0.41–0.60) for site of disease, TB treatment outcome and smear microscopy or X-ray as a diagnostic test (p<0.05). We observed more missing items for the TB Treatment record compared to TIER.Net; TB treatment outcome date and site of disease specifically. In comparison, TB treatment start dates as well as HIV-status recording had higher concordance. HIV status and lab results appeared to be more complete in the TB module in TIER.Net than in the TB Treatment Records, and there was “good/substantial” agreement (Kappa 0.61–0.80) for HIV status. Discussion and conclusion Our key finding was that the TB Module in TIER.Net was more complete in some key variables including TB treatment outcome. Most TB patient records we reviewed were found on TIER.Net but there was a noticeable gap of TB Identification patient records from the paper register as compared to TIER.Net, including those who tested TB-negative or HIV-negative. There is evidence of complete and “good/substantial” data quality for key TB-related variables, such as “First GeneXpert test result” and “HIV status.” Improvements in data completeness of TIER.Net compared to the TB Treatment Record are the most urgent area for improvement, especially recording of TB treatment outcomes.

Lessons from a systematic tracing process aimed to reduce initial loss to follow-up (ILTFU) among people diagnosed with tuberculosis (TB) in Cape Town, South Africa

“…We found discrepancies between paper-based and electronic TB registers, typically due to poor data capturing, and incorrect and outdated patient details on the electronic systems. Other studies done in South Africa have assessed the quality of TB data and found that the data on paper-based registers did not correspond with data in the electronic registers (patient-personal and TB information) [13,14]. Having an accurate electronic TB register, captured in 'real time' is vital, not only to truly re ect the work done within the TB program, but more importantly to reduce resources invested in tracing people at home, who are already in care.…”

Characterising patterns in routinely reported longitudinal HIV data in South Africa using a Bayesian multiplicative interaction model

“…Whereas, discrepancies may be due to human error when reporting or entering the data, rounding and poor reporting of missing data. 4 Approaches for evaluating these types of data may involve simple arithmetic operations such as absolute and proportional differences between subsequent data points to study trends over time, or calculation of differences between data source averages. These can be informative, but they do not offer a summary of the overall time-related fluctuations while taking into account facility differences.…”

“…The system is three tiered in that it is made up of the paper-based medical registers (tier 1), an electronic version of the paper-based registers (tier 2) and the full electronic medical record (tier 3) which contain information from tiers 1 and 2. 4 The lower tiers are used in low-resourced areas and the goal is that, ultimately, all facilities will transition to tier 3 as resources and skilled personnel improve.…”