article · BMC Health Services Research
The Ethiopian Short Version of the International Classification of Diseases 11 (ESV-ICD-11) is a simplified standard designed to support consistent disease coding across healthcare facilities. An evaluation of 872 medical records from 19 public health facilities in the Central Gondar Zone found that 68.81 percent were accurately classified according to the standard. Accuracy varied regionally, ranging from 60.95 percent in East Belesa to 80 percent in West Dembia. Qualitative interviews with 22 key informants revealed that healthcare providers face several barriers during implementation, including gaps in knowledge and skills, unfavourable attitudes, limited guideline availability and usability, and inadequate resource allocation alongside external factors. Addressing these operational challenges through focused training, improved access to guidelines, and appropriate financial resourcing is necessary to improve diagnostic record quality and disease trend tracking.
Reliable disease classification is essential for tracking public health trends and making informed comparisons across different regions and time periods. When medical records lack accurate coding, health systems cannot clearly understand disease patterns. Pinpointing the exact operational hurdles staff encounter allows decision-makers to design targeted training and supply the necessary tools to improve clinical documentation and data reliability.
The study offers operational evidence for developers of health information management systems, clinical decision-support tools, and digital coding training programmes tailored to public healthcare settings. Rather than presenting a commercial product, this applied field evaluation highlights clear design requirements: technical tools and coding aids must account for low resource availability, usability constraints, and staff training deficits before successful deployment and adoption can occur.
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The Ethiopian Short Version of the International Classification of Diseases 11 (ESV-ICD-11) is a simplified disease classification standard designed to facilitate consistency in disease coding across time and geographic regions. Despite its intended purpose to enhance medical record accuracy, implementation challenges have been reported, resulting in challenges in tracking disease trends and data comparability. There is little evidence on the accuracy of ESV-ICD-11 and the implementation challenges healthcare providers face in Ethiopian public health facilities. This study aimed to identify the accuracy of medical records and explore implementation challenges of the ESV-ICD-11 standard among healthcare providers working in healthcare facilities of the Central Gondar Zone, Ethiopia. A cross-sectional mixed-methods study was conducted from September 25 to October 10, 2023, from 19 healthcare facilities in Central Gondar Zone. To assess the accuracy of ESV-ICD-11, data were collected from 872 medical records. The records were selected by a systematic random sampling technique using checklist. For the qualitative part, 22 key informants were purposively selected and interviewed using a semi-structured guide to explore the challenges of ESV-ICD-11 implementation. Data entry was done using Epi-Info version 7 and exported to STATA version 14 for descriptive statistical analysis. Moreover, we applied inductive thematic analysis to the qualitative data using Open Code 4.02. Among 872 medical records, 600 (68.81%, 95% CI: 65.73–71.89) were accurately classified according to the ESV-ICD-11 standard. The minimum and maximum accuracy percentages were observed 60.95% in East Belesa and 80% in West Dembia districts, respectively. Gaps in knowledge and skill development, poor attitude, low guideline availability and usability, inadequate resource availability and utilization, and external factors were explored as implementation challenges. About two-thirds of the medical records were accurately classified according to the ESV-ICD-11 standard. Provider knowledge and skill gaps, negative attitudes, inadequate guideline availability, resource constraints, and external factors were some of the main implementation challenges explored. Priority should be given to addressing these challenges through focused training, enhancing guideline availability, and availing financial resources to enhance classification accuracy.
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DOI: 10.1186/s12913-026-15506-x
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