Literature DB >> 31043088

Importance of coding co-morbidities for APR-DRG assignment: Focus on cardiovascular and respiratory diseases.

Julio Souza1,2, João Vasco Santos1,2,3, Veronica Bolon Canedo4, Amparo Betanzos4, Domingos Alves2,5, Alberto Freitas1,2.   

Abstract

BACKGROUND: The All Patient-Refined Diagnosis-Related Groups (APR-DRGs) system has adjusted the basic DRG structure by incorporating four severity of illness (SOI) levels, which are used for determining hospital payment. A comprehensive report of all relevant diagnoses, namely the patient's underlying co-morbidities, is a key factor for ensuring that SOI determination will be adequate.
OBJECTIVE: In this study, we aimed to characterise the individual impact of co-morbidities on APR-DRG classification and hospital funding in the context of respiratory and cardiovascular diseases.
METHODS: Using 6 years of coded clinical data from a nationwide Portuguese inpatient database and support vector machine (SVM) models, we simulated and explored the APR-DRG classification to understand its response to individual removal of Charlson and Elixhauser co-morbidities. We also estimated the amount of hospital payments that could have been lost when co-morbidities are under-reported.
RESULTS: In our scenario, most Charlson and Elixhauser co-morbidities did considerably influence SOI determination but had little impact on base APR-DRG assignment. The degree of influence of each co-morbidity on SOI was, however, quite specific to the base APR-DRG. Under-coding of all studied co-morbidities led to losses in hospital payments. Furthermore, our results based on the SVM models were consistent with overall APR-DRG grouping logics. CONCLUSION AND IMPLICATIONS: Comprehensive reporting of pre-existing or newly acquired co-morbidities should be encouraged in hospitals as they have an important influence on SOI assignment and thus on hospital funding. Furthermore, we recommend that future guidelines to be used by medical coders should include specific rules concerning coding of co-morbidities.

Entities:  

Keywords:  Diagnosis-Related Groups; clinical coding; data accuracy; hospital administration; hospitals; machine learning; medical informatics; support vector machine

Mesh:

Year:  2019        PMID: 31043088     DOI: 10.1177/1833358319840575

Source DB:  PubMed          Journal:  Health Inf Manag        ISSN: 1833-3583            Impact factor:   3.185


  3 in total

1.  All Patient Refined-Diagnosis Related Groups' (APR-DRGs) Severity of Illness and Risk of Mortality as predictors of in-hospital mortality.

Authors:  João Vasco Santos; João Viana; Carla Pinto; Júlio Souza; Fernando Lopes; Alberto Freitas; Sílvia Lopes
Journal:  J Med Syst       Date:  2022-05-06       Impact factor: 4.460

2.  Findings from the Health Information Management Section of the 2020 International Medical Informatics Association Yearbook.

Authors:  Meryl Bloomrosen; Eta S Berner
Journal:  Yearb Med Inform       Date:  2020-08-21

3.  Robotic versus open pancreatic surgery: a propensity score-matched cost-effectiveness analysis.

Authors:  Christian Benzing; Lea Timmermann; Thomas Winklmann; Lena Marie Haiden; Karl Herbert Hillebrandt; Axel Winter; Max Magnus Maurer; Matthäus Felsenstein; Felix Krenzien; Moritz Schmelzle; Johann Pratschke; Thomas Malinka
Journal:  Langenbecks Arch Surg       Date:  2022-03-21       Impact factor: 2.895

  3 in total

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