Association between patient factors and hospital completeness of a patient-reported outcome measures program in joint arthroplasty, a cohort study

Background The collection of patient-reported outcome measures (PROMs) following arthroplasty is common. PROMs data collection programs seek to maximise completeness in order to minimise selection bias and optimise representativeness of the sample attained. We aimed to determine if patient factors influence variation in PROMs program completeness between-hospitals. Methods Using data from a national arthroplasty registry PROMs program, we tested for associations between patient characteristics (age, sex, body mass index [BMI] and American Society of Anaesthesiologists [ASA] class) and both potential completeness (registration completeness: the proportion of arthroplasty patients that were registered in the PROMs electronic system) and actual completeness (response completeness: the proportion of arthroplasty patients who provided PROMs data) using linear regression. Results When using all elective primary total hip, knee or shoulder arthroplasty procedures (N = 31,801) from 43 hospitals as the denominator, overall registration completeness was 52%, varying from 5 to 87% between hospitals. Overall pre-operative response completeness was 46%, varying from 5 to 82% between hospitals. There were no significant associations between hospital-level registration completeness or response completeness and age, sex, BMI or ASA score. Conclusion Completeness rates of a PROMs program in arthroplasty varied widely between hospitals but in the absence of a relationship between measured patient factors and completeness rates, the observed variation likely relates to local site factors such as access to patients, local resources and clinician engagement with the program. Efforts to improve the rates of completeness of arthroplasty PROMs programs at individual hospitals may not improve the representativeness of the sample. Plain English summary Hospitals vary in how completely they include and follow up patients when measuring patient-reported health. It is important to know if the completeness of inclusion and follow up by hospitals is affected by patient characteristics. This study addresses that problem by using data from a national patient outcome survey involving over 30,000 patients from 43 hospitals to look at the correlation between certain patient characteristics (like age, sex, obesity and general health) and the rates of inclusion and follow up for each hospital. Rates of inclusion (registering patients in the program) and follow up rates varied widely between ho