Predicting adverse events, length of stay, and discharge disposition following shoulder arthroplasty: a comparison of the Elixhauser Comorbidity Measure and Charlson Comorbidity Index
Section snippets
Materials and methods
A retrospective review of the National Inpatient Sample (NIS) was conducted from 2002 to 2014. The NIS is the largest inpatient database in the United States, representing a sample of discharges from all hospitals participating in the Healthcare Cost and Utilization Project.14 This database was searched using International Classification of Diseases, Ninth Revision (ICD-9) procedure coding for individuals who had a primary procedure of total shoulder arthroplasty (81.80) or reverse total
Results
We identified a total of 90,491 patients who had undergone a total or reverse total shoulder arthroplasty between 2002 and 2014. The mean age of our cohort was 69 ± 11 years, and female patients accounted for 56.5% of the study sample (Table II). In our cohort, 89.9% of patients were white, and 68.7% of patients used Medicare as their primary form of insurance. When stratified into groups of 0, 1, 2, and 3 or more comorbidities, the ECM classified a larger number of patients as having 3 or more
Discussion
The continuing adoption of value-based reimbursement and bundled payment initiatives requires the orthopedic surgeon to accurately define perioperative clinical pathways. The purpose of this study was to determine whether the ECM and CCI are valid modalities to assess postoperative outcomes and whether one is superior in predicting inpatient adverse events, deaths, length of stay, and discharge disposition following shoulder arthroplasty.
Our results indicate that both the CCI and ECM are good
Conclusion
We demonstrate that the ECM, in combination with basic demographic variables, can be an excellent predictive model for adverse events and discharge disposition after shoulder arthroplasty. Our results may be used to anticipate resource utilization for shoulder arthroplasty, which could assist value-based reimbursement methods to promote quality of care and reduce health care expenditures.
Disclaimer
The authors, their immediate families, and any research foundations with which they are affiliated have not received any financial payments or other benefits from any commercial entity related to the subject of this article.
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Because the National Inpatient Sample database contains no identifying personal health information, our study was exempt from institutional review board approval.