Employing quality control and feedback to the EQ-5D-5L valuation protocol to improve the quality of data collection

Objectives: In valuing health states using generic questionnaires such as EQ-5D, there are unrevealed issues with the quality of the data collection. The aims were to describe the problems encountered during valuation and to evaluate a quality control report and subsequent retraining of interviewers in improving this valuation. Methods: Data from the first 266 respondents in an EQ-5D-5L valuation study were used. Interviewers were trained and answered questions regarding problems during these initial interviews. Thematic analysis was used, and individual feedback was provided. After completion of 98 interviews, a first quantitative quality control (QC) report was generated, followed by a 1-day retraining program. Subsequently individual feedback was also given on the basis of follow-up QCs. The Wilcoxon signed-rank test was used to assess improvements based on 7 indicators of quality as identified in the first QC and the QC conducted after a further 168 interviews. Results: Interviewers encountered problems in recruiting respondents. Solutions provided were: optimization of the time of interview, the use of broader networks and the use of different scripts to explain the project’s goals to respondents. For problems in interviewing process, solutions applied were: developing the technical and personal skills of the interviewers and stimulating the respondents’ thought processes. There were also technical problems related to hardware, software and internet connections. There was an improvement in all 7 indicators of quality after the second QC. Conclusion: Training before and during a study, and individual feedback on the basis of a quantitative QC, can increase the validity of values obtained from generic questionnaires

The Indonesian EQ-5D-5L Value Set

Background: The EQ-5D is one of the most used generic health-related quality-of-life (HRQOL) instruments worldwide. To make the EQ-5D suitable for use in economic evaluations, a societal-based value set is needed. Indonesia does not have such a value set. Objective: The aim of this study was to derive an EQ-5D-5L value set from the Indonesian general population. Methods: A representative sample aged 17 years and over was recruited from the Indonesian general population. A multi-stage stratified quota method with respect to residence, gender, age, level of education, religion and ethnicity was utilized. Two elicitation techniques, the composite time trade-off (C-TTO) and discrete choice experiments (DCE) were applied. Interviews were undertaken by trained interviewers using computer-assisted face-to-face interviews with the EuroQol Valuation Technology (EQ-VT) platform. To estimate the value set, a hybrid regression model combining C-TTO and DCE data was used. Results: A total of 1054 respondents who completed the interview formed the sample for the analysis. Their characteristics were similar to those of the Indonesian population. Most self-reported health problems were observed in the pain/discomfort dimension (39.66%) and least in the self-care dimension (1.89%). In the value set, the maximum value was 1.000 for full health (health state ‘11111’) followed by the health state ‘11112’ with value 0.921. The minimum value was −0.865 for the worst state (‘55555’). Preference values were most affected by mobility and least by pain/discomfort. Conclusions: We now have a representative EQ-5D-5L value set for Indonesia. We expect our results will promote and facilitate health economic evaluations and HRQOL research in Indonesia