Accuracy of clinician-clinical coder information handover following acute medical admissions: implication for using administrative datasets in clinical outcomes management
Autor: | Ara Darzi, Darren Parsons, Jagdeep Singh Virk, S.A.R. Nouraei, A. Hudovsky, Christopher Wathen |
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Rok vydání: | 2015 |
Předmět: |
medicine.medical_specialty
Health Information Exchange Quality Assurance Health Care Comorbidity Audit Medical classification 030204 cardiovascular system & hematology Health informatics State Medicine Clinical coder 03 medical and health sciences Patient safety 0302 clinical medicine Diagnosis Outcome Assessment Health Care Health care medicine Electronic Health Records Humans 030212 general & internal medicine Medical diagnosis Medical Audit business.industry Clinical Coding Patient Handoff Public Health Environmental and Occupational Health Reproducibility of Results General Medicine Hospitalization England Emergency medicine Emergency Service Hospital business Coding (social sciences) |
Zdroj: | Journal of Public Health. 38:352-362 |
ISSN: | 1741-3850 1741-3842 |
Popis: | Background We evaluated the accuracy, limitations and potential sources of improvement in the clinical utility of the administrative dataset for acute medicine admissions. Methods Accuracy of clinical coding in 8888 patient discharges following an emergency medical hospital admission to a teaching hospital and a district hospital over 3 years was ascertained by a coding accuracy audit team in respect of the primary and secondary diagnoses, morbidities and financial variance. Results There was at least one change to the original coding in 4889 admissions (55%) and to the primary diagnosis of at least one finished consultant episodes of 1496 spells (16.8%). There were significant changes in the number of secondary diagnoses and the Charlson morbidity index following the audit. Charlson score increased in 8.2% and decreased in 2.3% of patients. An income variance of £816 977 (+5.0%) or £91.92 per patient was observed. Conclusions The importance and applications of coded healthcare big data within the NHS is increasing. The accuracy of coding is dependent on high-fidelity information transfer between clinicians and coders, which is prone to subjectivity, variability and error. We recommend greater involvement of clinicians as part of multidisciplinary teams to improve data accuracy, and urgent action to improve abstraction and clarity of assignment of strategic diagnoses like pneumonia and renal failure. |
Databáze: | OpenAIRE |
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