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Select Specialty Hospital
- Publisher
- Oxford University Press
- Copyright
- The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com
- ISSN
- 1067-5027
- eISSN
- 1527-974X
- DOI
- 10.1093/jamia/ocu028
- pmid
- 25665703
- Publisher site
- See Article on Publisher Site
Abstract
Objective The general equivalence mappings (GEMs) and reimbursement mappings (RMs) facilitate translation between ICD-9-CM and ICD-10-CM. This study compared prospectively dual-encoded diagnoses assigned by professional coders with the GEMs/RMs in a clinical setting.Materials and Methods Professional coders manually encoded diagnoses from 100 primary care notes into both ICD-9-CM and ICD-10-CM. The investigators evaluated whether manual mappings were reproducible using the GEMs/RMs. Reproducible mappings with one ICD-9-CM and one ICD-10-CM code (one-to-one) were classified as exact or approximate using GEMs flags. Mismatches were characterized manually.Results Manual encodings were reproducible from the forward GEMs, backward GEMs, and RMs in 85.2, 90.4, and 88.1 of diagnoses, respectively. For one-to-one, reproducible mappings, 61 (forward) and 63 (backward) were approximate mappings compared to 85 and 95 in the GEMs as a whole. Mismatches between manual and GEMs encodings were due to differences in coder interpretation (1113), subtle hierarchical differences (5255), or unknown reasons (3235).Discussion This study highlights inconsistencies between manual encoding and using the GEMs/RMs. The number of approximate mappings in our population compared to all one-to-one GEMs entries supports the notion that statistics describing the GEMs as a whole might not represent the most important mappings for each organization. The mismatch characteristics highlight the subtle differences between manual encoding and using the GEMs/RMs.Conclusion These results support the need for organizations to assess the GEMs and RMs in their own environment to avoid changes in reimbursement and longitudinal statistics.
Journal
Journal of the American Medical Informatics Association – Oxford University Press
Published: Mar 7, 2015