The ESV-ICD-11 is a simplified disease classification standard intended to make disease coding consistent across time and geographic regions in Ethiopia, thereby improving the accuracy of medical records. Accurate coding underpins the country's health management information systems: when records are coded inconsistently, health authorities struggle to track disease trends and compare data between facilities and regions. Despite that intended purpose, implementation challenges have been reported, and there had been little evidence on how accurately the standard is actually applied in Ethiopian public facilities.

To measure accuracy, the researchers carried out a cross-sectional study from September 25 to October 10, 2023, spanning 19 healthcare facilities in the Central Gondar Zone. Medical records were selected by systematic random sampling and assessed with a checklist. In parallel, the team conducted 22 key informant interviews with healthcare providers, purposively selected and guided by a semi-structured interview guide, to explore the challenges providers face in applying the standard.

Quantitative data were entered in Epi-Info version 7 and analyzed descriptively in STATA version 14, while the qualitative material was examined through inductive thematic analysis using Open Code 4.02. The accuracy figures varied considerably by district. The lowest accuracy was observed in East Belesa, where 60.95 percent of records were correctly classified, while the highest was in West Dembia, at 80 percent.

That spread of roughly 19 percentage points between districts suggests that local conditions — rather than a uniform national shortfall — shape how well the coding standard performs on the ground, though the study reports the range without attributing the differences to specific causes. The qualitative interviews identified five broad clusters of implementation challenges. The first was gaps in knowledge and skill development among providers responsible for coding.

The second was poor attitude toward the classification standard, which the study lists among the main barriers explored. The third was low availability and usability of guidelines, meaning that even willing coders may lack accessible reference material to apply the standard correctly. The fourth was inadequate resource availability and utilization, and the fifth comprised external factors affecting implementation.

These challenges connect directly to the accuracy results. A coding standard can only yield consistent data if the people applying it understand the classification rules, have usable guidelines at hand, and work in facilities with the resources to support the task. The study's authors conclude that priority should be given to addressing these challenges through focused training, enhancing guideline availability, and availing financial resources to improve classification accuracy.

The study's scope is worth noting. It covered 19 healthcare facilities in a single zone of Ethiopia over a two-week data collection window, and the record review was cross-sectional, capturing accuracy at one point in time rather than tracking changes. The qualitative component involved 22 key informants, whose experiences illuminate the challenges explored in the analysis but do not by themselves establish which barriers cause the observed coding errors.

The accuracy measure reflects classification according to the ESV-ICD-11 standard as assessed with the study checklist. The Central Gondar Zone findings indicate that even a simplified standard leaves roughly one in three records misclassified in the facilities studied, and that the shortfall is unevenly distributed across districts. For health information systems, the implications are practical.

Where accuracy falls to around 61 percent, disease statistics derived from those records will carry substantial misclassification, weakening the trend-tracking and comparability functions that the standard exists to support. The study's identified levers — training, guideline availability, and financial resources — map onto the challenge clusters the interviews surfaced, giving program planners a starting point for interventions. The authors frame their conclusion around exactly those priorities, positioning the evidence as a guide for where investment in Ethiopia's health information infrastructure could yield the greatest improvement in record accuracy.

Subject of Research: Accuracy and implementation challenges of the Ethiopian Short Version of ICD-11 disease coding in Central Gondar Zone health facilities

Article Title: Accuracy and challenges of short version international classification of diseases-11 implementation in Ethiopian healthcare facilities: a mixed-methods study

Article References: Jemere, A. T., Yilma, T. M., Gezie, L. D., Mengiste, S. A., Gullslett, M. K., Kaasbøll, J. J., & Tilahun, B. (2026). Accuracy and challenges of short version international classification of diseases-11 implementation in Ethiopian healthcare facilities: a mixed-methods study. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15506-x

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15506-x

Keywords: ESV-ICD-11, ICD-11, Ethiopia, medical records, disease coding, health information systems, mixed-methods study, Central Gondar Zone, health facilities, coding accuracy, BMC Health Services Research, Accuracy