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ORIGINAL ARTICLE
Year : 2020  |  Volume : 10  |  Issue : 5  |  Page : 39-42

A clinical investigation into the benefits of using charge codes in perioperative and critical care epidemiology: A retrospective cohort database study


1 Department of Anesthesiology, Duke University Medical Center, Durham, USA
2 Department of Social Work, North Carolina State University, Raleigh, NC, USA
3 Optistatim LLC, 25 Willow Circle, Longmeadow, MA 01106, USA
4 Department of Medicine, Institute for Healthcare Delivery and Population Science, University of Massachusetts Medical School, Baystate, Springfield, MA, USA
5 Department of Anesthesiology, Duke University Medical Center; Anesthesiology Service, Durham VA Medical Center, Durham, USA

Correspondence Address:
Dr. Karthik Raghunathan
Anesthesiology Service, Durham VA Medical Center, 508 Fulton St. Durham, NC 27705
USA
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/IJCIIS.IJCIIS_47_19

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Context: Epidemiologic studies in critical care routinely rely on the codes listed in International Classification of Diseases (ICD) manuals which are primarily intended for reimbursement of claims to payers. Standardized billing codes may minimize the measurement error when used in conjunction with ICD codes. Aims: The aim was to examine the impact of using charge codes in addition to ICD codes for ascertaining two common procedures in surgical intensive care unit (ICU) settings: hemodialysis (HD) and red blood cell (RBC) transfusions. Settings and Design: This was a retrospective cohort study of Premier Inc. Database. Subjects and Methods: Elective surgical patients aged >18 years treated in the ICU postoperatively were included in this study. This includes the ascertainment of HD and RBC transfusions in the population using a standard “ICD code” versus an “either ICD code or charge code” approach. Statistical Analysis Used: Descriptive analysis using t-tests, Chi-square tests as appropriate was used. Results: A total of 40,357 patients were identified as having undergone elective surgery, followed by admission to an ICU across 520 US hospitals. The use of “ICD codes only” uniformly underestimated rates of HD or RBC transfusions when compared to “Charge Codes only” and “ICD Codes or Charge Codes” (% increase of 15.4%–45.6% and 50.8%–93.1%, respectively). Differences varied with specific surgical populations studied. Patients identified using the “ICD code” approach had more comorbidities, were more likely to be female, and more likely to be Medicare beneficiaries. Conclusions: Epidemiologic studies in critical care should consider using multiple independent data sources to improve ascertainment of common critical care interventions.


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