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Published on: December 3, 2017
[Quality in Revision Arthroplasty: A Comparison between Claims Data Analysis and External Quality Assurance]
M Wessling1, S Gravius2, C Gebert1
1Abteilung für Revisions- und Tumororthopädie, Orthopädische Klinik Volmarstein, Wetter.
Background:
External quality assurance for revisions of total knee arthroplasty (TKA) and total hip arthroplasty (THA) are carried out through the AQUA institute in Germany. Data are collected by the providers and are analyzed based on predefined quality indicators from the hospital stay in which the revision was performed. The present study explores the possibility to add routine data analysis to the existing external quality assurance (EQS). Differences between methods are displayed. The study aims to quantify the benefit of an additional analysis that allows patients to be followed up beyond the hospitalization itself.
Material And Methods:
All persons insured in an AOK sickness fund formed the population for analysis. Revisions were identified using the same algorithm as the existing external quality assurance. Adverse events were defined according to the AQUA indicators for the years 2008 to 2011.The hospital stay in which the revision took place and a follow-up of 30 days were included. For re-operation and dislocation we also defined a 365 days interval for additional follow-up. The results were compared to the external quality control reports.
Results:
Almost all indicators showed higher events in claims data analysis than in external quality control. Major differences are seen for dislocation (EQS SD: 1.87 vs. claims data [cd] SD: 2.06 %, cd+30 d: 2.91 %, cd+365 d: 7.27 %) and reoperation (hip revision: EQS SD: 5.88 % vs. claims data SD: 8.79 % cd+30 d: 9.82 %, cd+365 d: 15.0 %/knee revision: EQS SD: 3.21 % vs. claims data SD: 4.07 %, cd+30 d: 4.6 %, cd+365 d: 15.43 %). Claims data could show additional adverse events for all indicators after the initial hospital stay, rising to 77 % of all events.
Conclusions:
The number of adverse events differs between the existing external quality control and our claims data analysis. Claims data give the opportunity to complement existing methods of quality control though a longer follow-up, when many complications become evident.
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