Tsopra, R, Peckham, D orcid.org/0000-0001-7723-1868, Beirne, P et al. (8 more authors) (2018) The impact of three discharge coding methods on the accuracy of diagnostic coding and hospital reimbursement for inpatient medical care. International Journal of Medical Informatics, 115. pp. 35-42. ISSN 1386-5056
Abstract
Background: Coding of diagnoses is important for patient care, hospital management and research. However coding accuracy is often poor and may reflect methods of coding. This study investigates the impact of three alternative coding methods on the inaccuracy of diagnosis codes and hospital reimbursement.
Methods: Comparisons of coding inaccuracy were made between a list of coded diagnoses obtained by a coder using (i)the discharge summary alone, (ii)case notes and discharge summary, and (iii)discharge summary with the addition of medical input. For each method, inaccuracy was determined for the primary, secondary diagnoses, Healthcare Resource Group (HRG) and estimated hospital reimbursement. These data were then compared with a gold standard derived by a consultant and coder.
Results: 107 consecutive patient discharges were analysed. Inaccuracy of diagnosis codes was highest when a coder used the discharge summary alone, and decreased significantly when the coder used the case notes (70% vs 58% respectively, p < 0.0001) or coded from the discharge summary with medical support (70% vs 60% respectively, p < 0.0001). When compared with the gold standard, the percentage of incorrect HRGs was 42% for discharge summary alone, 31% for coding with case notes, and 35% for coding with medical support. The three coding methods resulted in an annual estimated loss of hospital remuneration of between £1.8 M and £16.5 M.
Conclusion: The accuracy of diagnosis codes and percentage of correct HRGs improved when coders used either case notes or medical support in addition to the discharge summary. Further emphasis needs to be placed on improving the standard of information recorded in discharge summaries.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | (c) 2018 Elsevier B.V. All rights reserved. This is an author produced version of a paper published in International Journal of Medical Informatics. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Diagnosis; Data accuracy; Clinical coding and quality of health care |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > Institute of Molecular Medicine (LIMM) (Leeds) > Section of Translational Medicine (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 03 Aug 2018 13:58 |
Last Modified: | 27 Mar 2019 01:41 |
Status: | Published |
Publisher: | Elsevier |
Identification Number: | 10.1016/j.ijmedinf.2018.03.015 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:134083 |