Identification of root causes of clinical coding problems in Iranian hospitals.

Health information management : journal of the Health Information Management Association of Australia(2021)

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摘要
BACKGROUND:Improving the quality of coded data requires the identification and evaluation of the root causes of clinical coding problems to inform appropriate solutions. OBJECTIVE:The objective of this study was to identify the root causes of clinical coding problems. METHOD:Twenty-one clinical coders from three cities in Iran were interviewed. The five formal categories in Ishikawa's cause-and-effect diagram were applied as pre-determined themes for the data analysis. RESULTS:The study indicated 16 root causes of clinical coding problems in the five main themes: (i) policies, protocols, and processes (lack of clinical documentation guidelines; lack of audit of clinical coding and feedback to clinical coders; the long interval between documentation and clinical coding; and not using coded data for reimbursement; (ii) individual factors (shortage of clinical coders; low-skilled clinical coders; clinical coders' insufficient communication with physicians; and the lack of continuing education; (iii) equipment and materials (incomplete medical records; lack of access to electronic medical records and electronic coding support tools; (iv) working environment (lack of an appropriate, dynamic, and motivational workspace; and (v) management factors (mangers' inattention to the importance of coding and clinical documentation; and to providing the required staff support. CONCLUSION:The study identified 16 root causes of clinical coding problems that stand in the way of clinical coding quality improvement. IMPLICATIONS:The quality of clinical coding could be improved by hospital managers and health policymakers taking these problems into account to develop strategies and implement solutions that target the root causes of clinical coding problems.
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关键词
cause-and-effect diagram,clinical coding,clinical documentation integrity,data quality,health classification,health information management,medical record,quality improvement,root cause analysis
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