Applying models of care for total hip and knee arthroplasty: External validation of a published predictive model to identify extended stay risk prior to lower-limb arthroplasty

Introduction/Aims Multiple predictive tools have been developed to identify patients requiring an extended hospital stay following lower limb arthroplasty. Use at new sites requires verification of appropriate data coverage and evidence of validity in a new population. The aim of this study was to externally validate a previously reported model for identifying patients requiring an extended (5+ day) stay following total hip or knee replacement in a medium-sized public hospital orthopaedic department. Methods Electronic medical records were accessed and retrospective data extracted from 200 randomly selected total hip or knee arthroplasty patients. Data fields were matched to the candidate model and organised for validation analysis. Model validation was assessed with model discrimination, calibration on both original (unadjusted) and adjusted forms of the candidate model. Decision curve analysis was conducted on the outputs of the adjusted model. Results The original model performed poorly in the validation dataset, grossly overestimating length of stay. Performance improved following adjustment of the model intercept and model coefficients, although the model remained poorly calibrated at low and medium risk threshold and net benefit of the adjusted model was modest. Conclusion Consideration of predictive models to improve resource allocation for postoperative management of arthroplasty patients should include practical assessment of discrimination, calibration and net benefit of intervention at a clinically acceptable threshold prior to implementation within their local setting. This forms a clinically meaningful assessment of the accuracy, as well as costs and benefits associated with the desired change in practice. The selection of an appropriate model for quality care improvement remains challenging. ### Competing Interest Statement The authors employed by EBM Analytics have been contracted by QEII Jubilee Hospital Orthopaedics for the purposes of data custodianship of a clinical outcomes registry, and assistance with running and documentation of this study. No other authors have any conflicts to disclose. ### Funding Statement This study was funded by the QEII Jubilee Hospital Orthopaedic Research Fund. EBM Analytics was contracted by the senior authors to assist with planning and execution of this study, including data analysis and manuscript preparation. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Metro South Human Research Ethics Committee approved this study (HREC/2019/QMS/57093). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes Data may be available from the corresponding author upon reasonable request.