Date Published: August 25, 2012
Publisher: Informa Healthcare
Author(s): Aksel Paulsen, Alma B Pedersen, Søren Overgaard, Ewa M Roos.
Feasibility is an important parameter when choosing which patient-reported outcomes (PRO) to use in a study. We assessed the feasibility of PROs in a hip registry setting.
Primary total hip arthroplasty (THA) patients (n = 5,747) who had been operated on 1–2, 5–6, or 10–11 years previously were randomly selected from the Danish Hip Arthroplasty Register and sent 2 PRO questionnaires: 1 generic (EuroQoL-5D or SF-12 health survey) and 1 disease-specific (hip dysfunction and osteoarthritis outcome score (HOOS) or Oxford 12-item hip score). We compared response rates, floor and ceiling effects, missing items, and the need for manual validation of forms.
4,784 patients (mean age 71 years, 57% females) were included (83%). The response rates ranged from 82–84%. Statistically significantly different floor and ceiling effects ranged from 0% to 0.5% and from 6.1% to 46%, respectively. Missing items ranged from 1.2% to 3.4%, and 0.8–4.3% required manual validation (p < 0.009). A hypothetical repeat study found that group sizes from 51 to 1,566 are needed for subgroup analysis, depending on descriptive factor and choice of PRO. All 4 PROs fulfilled a priori set criteria, with the exception of ceiling effects. The high ceiling effects were attributed to postoperative administration and good outcome for THA. We conclude that all 4 PROs are appropriate for administration in a hip registry.
The feasibility of a PRO is not absolute, but depends on the context in which it is being used. To our knowledge, this is the first feasibility study to compare commonly used disease-specific and generic PROs head-to-head in a hip registry setting. We found that all 4 PROs are feasible for use in a hip registry setting. Our feasibility criteria were response rate, floor and ceiling effects, missing items, and need for manual validation of the scanned PROs. A high response rate is important to ensure generalizability and to minimize selection bias. A response rate of 80% is usually considered to be sufficiently representative of the sample studied. We thus chose, a priori, this cut-off for the mailed patient-reported data used in the study. Much higher response rates are, however, achieved with regard to hard data entered into joint registries. For example, the DHR has a coverage of 96% (Overgaard 2012). These types of data collection differ with regard to the person providing the data (patient vs. health professional), ethics (patients are not legislated to provide data), and setting (in-hospital vs. home) and thus different response rates can be achieved.