Literature DB >> 19293434

The risk and consequences of clinical miscoding due to inadequate medical documentation: a case study of the impact on health services funding.

Ping Cheng1, Annette Gilchrist, Kerin M Robinson, Lindsay Paul.   

Abstract

As coded clinical data are used in a variety of areas (e.g. health services funding, epidemiology, health sciences research), coding errors have the potential to produce far-reaching consequences. In this study the causes and consequences of miscoding were reviewed. In particular, the impact of miscoding due to inadequate medical documentation on hospital funding was examined. Appropriate reimbursement of hospital revenue in the casemix-based (output-based) funding system in the state of Victoria, Australia relies upon accurate, comprehensive, and timely clinical coding. In order to assess the reliability of these data in a Melbourne tertiary hospital, this study aimed to: (a) measure discrepancies in clinical code assignment; (b) identify resultant Diagnosis Related Group (DRG) changes; (c) identify revenue shifts associated with the DRG changes; (d) identify the underlying causes of coding error and DRG change; and (e) recommend strategies to address the aforementioned. An internal audit was conducted on 752 surgical inpatient discharges from the hospital within a six-month period. In a blind audit, each episode was re-coded. Comparisons were made between the original codes and the auditor-assigned codes, and coding errors were grouped and statistically analysed by categories. Changes in DRGs and weighted inlier-equivalent separations (WIES) were compared and analysed, and underlying factors were identified. Approximately 16% of the 752 cases audited reflected a DRG change, equating to a significant revenue increase of nearly AU$575,300. Fifty-six percent of DRG change cases were due to documentation issues. Incorrect selection or coding of the principal diagnosis accounted for a further 13% of the DRG changes, and missing additional diagnosis codes for 29%. The most significant of the factors underlying coding error and DRG change was poor quality of documentation. It was concluded that the auditing process plays a critical role in the identification of causes of coding inaccuracy and, thence, in the improvement of coding accuracy in routine disease and procedure classification and in securing proper financial reimbursement.

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Year:  2009        PMID: 19293434     DOI: 10.1177/183335830903800105

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


  18 in total

1.  Computer-Assisted Diagnostic Coding: Effectiveness of an NLP-based approach using SNOMED CT to ICD-10 mappings.

Authors:  Anthony N Nguyen; Donna Truran; Madonna Kemp; Bevan Koopman; David Conlan; John O'Dwyer; Ming Zhang; Sarvnaz Karimi; Hamed Hassanzadeh; Michael J Lawley; Damian Green
Journal:  AMIA Annu Symp Proc       Date:  2018-12-05

2.  Emergency readmissions to paediatric surgery and urology: The impact of inappropriate coding.

Authors:  R Peeraully; K Henderson; B Davies
Journal:  Ann R Coll Surg Engl       Date:  2016-02-29       Impact factor: 1.891

3.  Problems and Barriers during the Process of Clinical Coding: a Focus Group Study of Coders' Perceptions.

Authors:  Vera Alonso; João Vasco Santos; Marta Pinto; Joana Ferreira; Isabel Lema; Fernando Lopes; Alberto Freitas
Journal:  J Med Syst       Date:  2020-02-08       Impact factor: 4.460

4.  The effect of direct admission to acute geriatric units compared to admission after an emergency department visit on length of stay, postacute care transfers and ED return visits.

Authors:  D Naouri; N Pelletier-Fleury; N Lapidus; Y Yordanov
Journal:  BMC Geriatr       Date:  2022-07-04       Impact factor: 4.070

5.  Resident integration with inpatient clinical documentation improvement: a quality improvement project.

Authors:  Michael Rouse; Matthew Jones; Brice Zogleman; Rebekah May; Tanya Ekilah; Cheryl Gibson
Journal:  BMJ Open Qual       Date:  2022-06

6.  Validation of Diagnostic Coding for Diabetes Mellitus in Hospitalized Patients.

Authors:  Clarissa C Ren; Mohammed S Abusamaan; Nestoras Mathioudakis
Journal:  Endocr Pract       Date:  2022-02-04       Impact factor: 3.701

7.  A retrospective cohort study assessing patient characteristics and the incidence of cardiovascular disease using linked routine primary and secondary care data.

Authors:  Rupert A Payne; Gary A Abel; Colin R Simpson
Journal:  BMJ Open       Date:  2012-04-13       Impact factor: 2.692

8.  Variation in Prosthetic Joint Infection and treatment strategies during 4.5 years of follow-up after primary joint arthroplasty using administrative data of 41397 patients across Australian, European and United States hospitals.

Authors:  Perla J Marang-van de Mheen; Ellie Bragan Turner; Susan Liew; Nora Mutalima; Ton Tran; Sten Rasmussen; Rob G H H Nelissen; Andrew Gordon
Journal:  BMC Musculoskelet Disord       Date:  2017-05-22       Impact factor: 2.362

Review 9.  A review of data quality assessment methods for public health information systems.

Authors:  Hong Chen; David Hailey; Ning Wang; Ping Yu
Journal:  Int J Environ Res Public Health       Date:  2014-05-14       Impact factor: 3.390

10.  Incidence and Variation of Discrepancies in Recording Chronic Conditions in Australian Hospital Administrative Data.

Authors:  Hassan Assareh; Helen M Achat; Joanne M Stubbs; Veth M Guevarra; Kim Hill
Journal:  PLoS One       Date:  2016-01-25       Impact factor: 3.240

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