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Patient-rated satisfaction and improvement following hip and knee replacements: Development of prediction models
Karen O B Appiah1,2, Kamlesh Khunti1,2,3, Benjamin M Kelly4
1Leicester Diabetes Centre, Leicester General Hospital, University of Leicester, Leicester, UK.
Rationale:
Effective preoperative assessments of determinants of health status and function may improve postoperative outcomes.
Aims And Objectives:
We developed risk scores of preoperative patient factors and patient-reported outcome measures (PROMs) as predictors of patient-rated satisfaction and improvement following hip and knee replacements.
Patients And Methods:
Prospectively collected National Health Service and independent sector patient data (n = 30,457), including patients' self-reported demographics, comorbidities, PROMs (Oxford Hip/Knee score (OHS/OKS) and European Quality of Life (EQ5D index and health-scale), were analysed. Outcomes were defined as patient-reported satisfaction and improvement following surgery at 7-month follow-up. Univariable and multivariable-adjusted logistic regressions were undertaken to build prediction models; model discrimination was evaluated with the concordance index (c-index) and nomograms were developed to allow the estimation of probabilities.
Results:
Of the 14,651 subjects with responses for satisfaction following hip replacements 564 (3.8%) reported dissatisfaction, and 1433 (9.2%) of the 15,560 following knee replacement reported dissatisfaction. A total of 14,662 had responses for perceived improvement following hip replacement (lack of improvement in 391; 2.7%) and 15,588 following knee replacement (lack of improvements in 1092; 7.0%). Patients reporting poor outcomes had worse preoperative PROMs. Several factors, including age, gender, patient comorbidities and EQ5D, were included in the final prediction models: C-indices of these models were 0.613 and 0.618 for dissatisfaction and lack of improvement, respectively, for hip replacement and 0.614 and 0.598, respectively, for knee replacement.
Conclusions:
Using easily accessible preoperative patient factors, including PROMs, we developed models which may help predict dissatisfaction and lack of improvement following hip and knee replacements and facilitate risk stratification and decision-making processes.
