Abstract
Introduction
A variety of patient reported outcome (PRO) surveys have been established and validated to evaluate the effectiveness of surgical interventions. The Hip Disability and Osteoarthritis Outcome Score (HOOS) has been validated as one method to evaluate the effectiveness of total hip arthroplasty patients. This PRO facilitates the assessment of factors that alter patient outcomes in hip arthroplasty. This retrospective study assesses the effect of psychological post-operative expectations on HOOS in total hip arthroplasty patients. In this pilot study, patient data was collected for 499 patients using the AAOS established Musculoskeletal Outcomes Data Evaluation and Management System (MODEMS) [1] and HOOS surveys.
Method
Patient data was matched using similar preoperative HOOS scores to allow for comparable room for improvement in HOOS score postoperatively. These patients were placed into groups of high performers and low performers. HOOS is based on a 0 to 100 scale, 100 as the best. High performers were defined as those with a ratio of change in HOOS score between preoperative and postoperative over the highest difference in score possible (reaching a postoperative HOOS of 100) of 1. Low performers were defined as those with the aforementioned ratio, but under the value of 0.3. Using these defined groups we were able to compare the summation of patient specific MODEMS scores using a univariate regression. The HOOS growth ratio is calculated based on the following.
HOOS growth ratio = (HOOS postop – HOOS preop)/(100-HOOS preop)
A principal component analysis (PCA) was conducted to identify the significant group of factors that could identify changes in the outcome of 41 patients (20 low performers and 21 high performers).
Results and analysis
PCA was conducted on 5 items with orthogonal rotation (varimax). The Kaiser–Meyer–Olkin measure verified the sampling adequacy for the analysis, KMO = .0.688, which is well above the acceptable limit of 0.5. Two components had eigenvalues over Kaiser's criterion of 1 and in combination explained 74.487% of the variance. The scree plot demonstrate the two components that were retained in the final analysis. Component 1 represents expected outcome measured on Household activity, sleep comfort, and expected relief; the second component was made of expected outcome based on recreation activity and expected time to return to job. The outcome of the logistic regression model indicated that the factors in the first component group could significantly identify the performance of the patients after surgery.
Conclusions
In this study we used MODEMS questionnaire to find the postoperative performance outcome of the patients with THA. MODEMS has shown potential in identifying these individuals however the major component in this questionnaire were expected outcome measured on Household activity, sleep comfort, and expected relief. THis questionnaire can be used for future studies.
