This is the authors' abstract. We don't add key points for this paper.
BACKGROUND: National databases are increasingly used to research complication rates, risk factors, and the role of comorbidities. Three commonly used databases are the Healthcare Cost and Utilization Program's National Inpatient Sample (NIS), the National Hospital Discharge Survey (NHDS), and the American College of Surgeons National Surgical Quality Improvement Program (NSQIP). Despite many publications, the accuracy of results from these databases remains unclear. METHODS: We compared demographics and complication rates of primary total hip arthroplasty (THA) and primary total knee arthroplasty (TKA) across three national databases from 2006 to 2010. Using International Classification of Diseases, Ninth Revision, Clinical Modification and Current Procedural Terminology codes to identify cases, we calculated postoperative inpatient complication rates in all three databases and 30-day complication rates in the NSQIP. RESULTS: We identified a total of 607,322 TKAs and 279,428 THAs. Overall complication rates varied greatly between the databases. For TKA, the overall complication rates were the highest in the NIS (17.3% [16.6 to 18.0]), followed by the NHDS (14.9% [14.0 to 15.8]), and then the NSQIP 30 days (10.20% [9.73 to 10.70]) and the NSQIP until discharge (7.34% [6.95 to 7.75]). Similarly, for THA, the NIS was the highest (24.09% [23.05 to 25.16]), and then the NHDS (21.5% [19.8 to 23.2]), followed by the NSQIP 30 days (12.00% [11.31 to 12.72]), and the NSQIP until discharge (9.25% [8.64 to 9.90]). Breakdown and comparison of individual adverse events further revealed different complication rates. CONCLUSION: The estimated complication rates from THA and TKA depend on which data source is used because of differences in data collection and sampling methodology. Similar differences may exist in other publications that use such secondary data sources.
Answers are grounded in this paper and cite their sources.
No takes yet. Share an insight, caveat, or question.
Pierce et al. (2018) studied this question.
Synapse has enriched 10 related papers. Consider them for comparative context: