Data completeness and consistency in individual medical records of institutional births: retrospective crossectional study from Northwest Ethiopia, 2022.

Background: Ensuring the data quality of Individual Medical Records becomes a crucial strategy in mitigating maternal and newborn morbidity and mortality during and around childbirth. However, previous research in Ethiopia primarily focused on studying data quality of institutional birth at the facility level, overlooking the data quality within Individual Medical Records. This study examined the data completeness and consistency within Individual Medical Records of the institutional birth service and associated factors.

Methods: An institution-based retrospective cross-sectional study was conducted in two districts of Northwest Ethiopia. Data were obtained by reviewing three sets of Individual Medical Records of 651 women: the delivery register, Integrated Individual Folder, and integrated card. The proportions of completeness and consistency were computed. A multilevel binary logistic regression was used to identify factors of completeness and consistency. An odds ratio with a 95% confidence interval was used to assess the level of significance.

Results: Overall, 74.0% of women's Individual Medical Records demonstrated good data completeness ( > = 70%), 95%CI (70.5, 77.3), while 26% exhibited good consistency, 95%CI (22.9, 29.7). The presence of trained providers in data quality (AOR = 2.9, 95%CI: (1.5, 5.7)) and supportive supervision (AOR = 11.5, 95%CI: (4.8, 27.2)) were found to be associated with completeness. Health facilities' practice of root cause analysis on data quality gaps (AOR = 8.7, 9%CI: (1.5, 50.9)) was statistically significantly associated with the consistency.

Conclusions: Most medical records were found to have good completeness, but nearly only a quarter of them found to contain consistent data. Completeness and consistency varied on the type of medical record. Health facility's root cause analysis of data quality gaps, the presence of trained providers in data quality, and supportive supervision from higher officials were identified as factors affecting data quality in institutional birth service. These results emphasize the importance of focused efforts to enhance data completeness and consistency within Individual Medical Records, particularly through consideration of Individual Medical Records in future provider training, supervision, and the implementation of root cause analysis practices.