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Discordance in Reported Rates of Technology Use in Total Knee Arthroplasty Between the American Joint Replacement
Ayushmita De1, Patrick Donnelly, Mahveen Jahan
1From the American Joint Replacement Registry, Rosemont, IL (De, Donnelly, and Jahan), and the Department of Orthopaedic Surgery, University of Virginia, Charlottesville, VA (McVey, Novicoff and Browne).
Background:
There has been an associated increase in researchers using large databases to try to study new technology use in performing total knee arthroplasty (TKA). Large administrative databases (such as Medicare) as well as clinical registries (such as the American Joint Replacement Registry [AJRR] have been recently employed for this purpose). However, due to the inherent limitations of these databases, it remains unclear whether or not use of these data sources is a valid and accurate way to study this topic.
Methods:
All primary TKA cases aged 65 and over from January 1st, 2017 to December 31st, 2022 submitted to AJRR as of March 2024 were included. Patients with AJRR data were matched to their record in the Medicare data set and queried using robotic or computer navigation ICD-10 and Current Procedural Terminology procedure codes. Concordance rates for technology use were determined, and estimates for specificity and sensitivity were calculated. Predictive factors of database concordance were also assessed. Cases with unidentifiable laterality in CMS were excluded.
Results:
A total of 330,270 patients were there in the AJRR data set who underwent a primary elective TKA and were Medicare eligible. The AJRR data set suggested greater use of technology than the Medicare data set (9.9% versus 2.7%, respectively). The overall percentage of cases where AJRR and CMS agreed on technology status was 90.69% (90.59, 90.79; n = 297,547). Cohen kappa coefficient was 0.23, suggesting only fair agreement between the two sources. Database concordance was positively associated with obesity, higher Charlson comorbidity scores, female sex, small hospital size, and minor teaching hospital status.
Conclusion:
There is substantial discordance between large data sets when looking at the use of new technologies in TKA. In a matched data set, AJRR reported a higher rate of technology use during TKA then Medicare. Care should be taken when using large data sets when attempting to analyze the use of technology in TKA, especially when assuming technology is used.
