A systematic review of the causes of morbidity data quality issues

• The root causes of data quality issues of morbidity data collection are ambiguous and constantly changing standards that are too complex • The standards do not provide sufficient granularity for precise condition identification and reporting. • The current sequential morbidity data collection structure defined by the standards are not capable of linking complete diagnostic, causal and procedural relationships. • Ambiguous and complex standards lead to more training resources required for staff worldwide to manage the issues associated with the standards. • More research is needed into the structure of data capture systems and the use of consistent approaches to standards writing. The quality of hospital morbidity data collected with the International Classification of Diseases is unknown. A systematic review of the causes of morbidity data quality issues is urgently needed. We aimed to systematically identify and investigate the root causes of issues associated with hospital morbidity data collected using the International Classification of Diseases 10th edition, Australian Modification (ICD-10-AM) and Australian Classification of Health Interventions (ACHI). This review included studies related to morbidity data collection issues arising from using ICD-10-AM and ACHI from Scopus, Embase, Medline and other data sources from 2017 to January 2025 in English. The quality of included studies was assessed using SQUIRE and STROBE checklists. A narrative synthesis was undertaken with themes and sub-categories of issues identified. The review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 Statement. Fifty-two studies were included, 37 from Australia, 3 from Canada, 2 each from Ireland and New Zealand, and 1 each from France, Germany, Turkey, US. Four themes were identified: 1) quality issues in standards, 2) technology, 3) education and training, and 4) issues related to clinical practice. There exists ambiguity in standards due to optional guidelines in data processing and jurisdictional differences. The standards do not provide sufficient granularity for precise disease identification. The standards are not capable of linking complex diagnostic, causal and procedural relationships and are leading to technical and other categories of issues. The complexity of issues associated with the standard leads to insufficient training resources for staff worldwide. Fragmented information structure and changes in clinical documentation rules lead to inconsistent coding. Interpretation. The root causes of the morbidity data collection errors are mainly associated with the quality of the standards. Further research is needed to address the root causes of morbidity data quality issues, including the structure of data capture systems and the use of more consistent approaches to standards writing, such as those applied by the International Organisation for Standardisation (ISO), which is not investigated by this research.