Effect of an integrated intervention on the availability and completeness of Robson ten group classification system-related data in district hospitals in Bangladesh.

BACKGROUND

The Government of Bangladesh's routine data capturing system of health care facilities doesn't adequately capture Robson ten group classification system (TGCS)-related variables required to monitor caesarean section rates. To address this gap, we developed an integrated intervention and assessed its impact on the Robson TGCS-related variables availability and completeness.

METHODS

We conducted implementation research in eight district hospitals in Bangladesh from January 2021 to June 2023, where the primary population was mothers who gave birth within the implementing health care facilities. Our integrated intervention included the introduction of Robson TGCS; development and implementation of 'Robson TGCS Report Form'; capacity development training; a multi-level monitoring and supportive supervision system; and collaborative stakeholders' advisory workshops and review meetings. The primary outcome was the percentage of availability and completeness of TGCS-related data across study phases. The study was divided into five phases. Phase one focused on developing the data-capturing system, while data collection began in Phase two.

RESULTS

The average availability of six variables improved significantly (P < 0.001) from 76% (95% confidence interval (CI) = 75.7-76.8%) in phase two to 99% (95% CI = 98.8-99.1%) in Phase five. Similarly, data completeness for these variables increased significantly (P < 0.001) from 53% (95% CI = 52.2-54.2%) to 97% (95% CI = 96.2-97%). Consequently, the percentage of classified groups improved significantly (P < 0.001) from 55% (95% CI = 54.1-56.1%) to 97% (95% CI = 96.8-97.5%).

CONCLUSIONS

The integrated intervention significantly improved data availability and completeness. Active engagement of stakeholders, including governmental bodies and technical experts from local and central levels, is crucial to ensure data quality for identifying, planning and implementing targeted interventions.