Selection of key health domains from PROMIS® for a generic preference-based scoring system
We sought to select a parsimonious subset of domains from the patient-reported outcomes measurement information system (PROMIS®) that could be used for preference-based valuation. Domain selection criteria included face validity, comprehensiveness, and structural independence.
First, 9 health outcomes measurement experts selected domains appropriate for a general health measure using a modified Delphi procedure. Second, 50 adult community members assessed structural independence of domain pairs. For each pair, the participant was asked if it were possible to have simultaneously good functioning in domain 1 but poor functioning in domain 2, and vice versa. The community members also rated the relative importance of the domains. Finally, the experts selected domains, guided by community members’ judgments of structural independence and importance.
After 3 rounds of surveys, the experts agreed on 10 potential domains. The percent of pairs deemed structurally independent by community members ranged from 50 to 95 (mean = 78). Physical Function, Pain Interference, and Depression were retained because of their inclusion in existing preference-based measures and their importance to community members. Four other domains were added because they were important to community members and judged to be independent by at least 67% of respondents: Cognitive Function—Abilities; Fatigue; Ability to Participate in Social Roles and Activities; and Sleep Disturbance.
With input from measurement experts and community members, we selected 7 PROMIS domains that can be used to create a preference-based score.
KeywordsHealth-related quality of life Utility Multi-attribute utility instrument Health domains PROMIS® Health status
Janel Hanmer was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under Award Number KL2TR001856. Participant recruitment was completed by the Clinical and Translational Science Institute at the University of Pittsburgh, which is supported by the National Institutes of Health Clinical and Translational Science Award program, Grants UL1RR024153 and UL1TR000005. The funding agreements ensured the authors’ independence in designing the study, interpreting the data, writing, and publishing the report.
Compliance with ethical standards
Conflict of interest
The authors have no conflicts of interest to report.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. IRB approval for the project was obtained from the University of Pittsburgh (PRO14070021 and PRO14100533).
- 4.Cella, D., Riley, W., Reeve, B., Stone, A., Young, S., Rothrock, N., et al. (2010). Initial item banks and first wave testing of the patient-reported outcomes measurement information system (PROMIS) network: 2005–2008. Journal of Clinical Epidemiology, 63(11), 1179–1194.CrossRefPubMedPubMedCentralGoogle Scholar
- 5.Drummond, M. F., Sculpher, M. J., Torrance, G. W., O’Brien, B. J., & Stoddart, G. L. (2005). Methods for the economic evaluation of health care programmes (3rd ed.). Oxford: Oxford University Press.Google Scholar
- 7.Gold, M. R., Siegel, J. E., & Russell, L. B. (Eds.). (1996). Cost-effectiveness in health and medicine. New York: Oxford University Press.Google Scholar
- 8.Neumann, Peter J., Sanders, Gillian D., Russell, Louise B., Siegel, Joanna E., & Ganiats, Theodore G. (Eds.). (2016). Cost-Effectiveness in Health and Medicine (2nd ed.). New York: Oxford University Press.Google Scholar
- 10.Brazier, J., Ratcliff, J., Salomon, J. A., & Tsuchiya, A. (2007). Measuring and valuing health benefits for economic evaluation. Oxford: Oxford University Press.Google Scholar
- 12.Mittmann, N., Evans, W. K., Rocchi, A., Longo, C. J., Au, H.-J., Husereau, D., et al. (2009). Addendum to CADTH’s guidelines for the economic evaluation of health technologies: Specific guidance for oncology products. Ottawa: Canadian Agency for Drugs and Technologies. in HealthGoogle Scholar
- 13.National Institute for Health and Clinical Excellence. (2013). Guide to the methods of technology appraisal. London: NICE.Google Scholar
- 14.Johnson, F. R., Lancsar, E., Marshall, D., Kilambi, V., Mühlbacher, A., Regier, D. A., et al. (2013). Constructing experimental designs for discrete-choice experiments: Report of the ISPOR conjoint analysis experimental design good research practices task force. Value in Health, 16(1), 3–13.CrossRefGoogle Scholar
- 15.Riley, W. T., Rothrock, N., Bruce, B., Christodolou, C., Cook, K., Hahn, E. A., et al. (2010). Patient-reported outcomes measurement information system (PROMIS) domain names and definitions revisions: Further evaluation of content validity in IRT-derived item banks. Quality of Life Research, 19(9), 1311–1321.CrossRefPubMedPubMedCentralGoogle Scholar
- 19.Feeny, D., Torrance, G., & Furlong, W. (1996). Health Utilities Index. In B. Spilker (Ed.), Quality of life and pharmacoeconomics in clinical trials. Philadelphia, PA: Lippincott-Raven Press.Google Scholar
- 23.Collins, F. S., & Riley, W. T. (2016). NIH’s transformative opportunities for the behavioral and social sciences. Science Translational Medicine, 23(8), 366.Google Scholar
- 25.Hays, R.D., Revicki, D.A., Feeny, D., Fayers, P., Spritzer, K.L., Cella, D. (2016). Using linear equating to map PROMIS global health items and the PROMIS-29 V2.0-profile measure to the Health Utilities Index Mark 3. Pharmacoeconomics (ePub).Google Scholar
- 26.Revicki, D. A., Kawata, A. K., Harnam, N., Chen, W. H., Hays, R. D., & Cella, D. (2009). Predicting EuroQol (EQ-5D) scores from the patient-reported outcomes measurement information system (PROMIS) global items and domain item banks in a United States sample. Quality of Life Research, 18(6), 783–791.CrossRefPubMedPubMedCentralGoogle Scholar