Understanding the measurement relationship between EQ-5D-5L, PROMIS-29 and PROPr
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Brendan James Mulhern, Tianxin Pan, Richard Norman, An Tran‐Duy, Janel Hanmer, Rosalie C. Viney, Nancy J. Devlin
A health questionnaire can say you have no problems while another detects serious trouble with sleep or tiredness. This study explains why different checklists can produce different pictures of the same person.
Purpose Many generic patient-reported instruments are available for the measurement of health outcomes, including EQ5D-5L, and the Patient-Reported Outcome Measurement Information System (PROMIS). Assessing their measurement characteristics informs users about the consistency between, and limits of, evidence produced. The aim was to assess the measurement relationship between the EQ-5D-5L descriptive system and value sets, the PROMIS-29 and PROPr (PROMIS value set). Methods Data were extracted from a cross-sectional survey administering measures of quality of life online in Australia. Descriptive analysis, agreement and construct validity assessment methods were used to compare instruments at the item, domain and value set level. Results In total, 794 Australians completed the survey. Convergent validity analysis found that similar dimensions across instruments were highly correlated (> 0.50), but the PROMIS-29 assesses additional health concepts not explicitly covered by EQ-5D (sleep and fatigue). Known-group assessment found that EQ-5D-5L and PROPr were able to detect those with and without a condition (ES range 0.780.83) but PROPr could more precisely detect differing levels of self-reported health. Both instruments were sensitive to differences in levels of pain. Discussion There is some consistency in what the EQ-5D-5L, PROMIS-29 and PROPr measure. Differences between value set characteristics can be linked to differences what is measured and the valuation approaches used. This has implications for the use of each in assessing health outcomes, and the results can inform decisions about which instrument should be used in which context.
Transcript
A health questionnaire can say you have no problems while another detects serious trouble with sleep or tiredness. This study explains why different checklists can produce different pictures of the same person. Health-related quality of life information is used in clinical decision-making and also supports the allocation of funds in the health care system.
There are many different questionnaires used to measure health-related quality of life, but the most appropriate questionnaire is not known for different groups of people. Think of three maps of the same city: the EQ-5D-5L descriptive system and value sets, the PROMIS-29, and PROPr.
The study compares their measurement relationship. Assessing their measurement characteristics informs users about the consistency between, and limits of, the evidence produced. The data came from an online survey of patients with common conditions and the general population in Australia.
The common conditions targeted included diabetes, depression, pain and arthritis. The instruments were completed in a random order, so approximately half of the sample completed one before the other. Strong relationships were found between dimensions where the concepts measured were expected to be similar.
These results demonstrate overlap between the health-related quality-of-life concepts measured. Lower relationships with fatigue and sleep measures suggest that fatigue and sleep problems are measured indirectly, but not explicitly, by the shorter health measure.
Both measures have acceptable properties, particularly for detecting differences between people’s self-reported health levels. There is consistency between dimensions measuring similar concepts, but each measure also includes concepts not explicitly assessed by the other.
More respondents were likely to report no problems on the shorter health measure than on the broader health domains. This is expected because each broader health domain includes four questions rather than one and asks questions using both frequency and severity.
Similar dimensions across the measures were highly related, but the broader measure assesses additional health concepts not explicitly covered by the shorter measure, including sleep and fatigue. The shorter measure and its related scoring system could detect people with and without a condition, but the broader scoring system could more precisely detect differing levels of self-reported health.
Both instruments were sensitive to differences in levels of pain. The strength of the measurement relationship differs depending on which test is used and whether questions, dimensions, or scoring systems are compared. This has implications for using each measure to assess health and make subsequent decisions.
Further work is needed to understand the advantages and disadvantages of each measure in different populations. The questionnaires overlap, but they do not measure exactly the same parts of life or turn answers into scores in the same way. Choosing between them can change what clinicians and health systems notice.
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