Abstract
Objectives
We review the NCI/DIA conference, “Improving health outcomes assessment based on modern measurement theory and computerized adaptive testing,” and suggest next steps in use of item response theory (IRT) to assess health outcomes.
Background
In recent years the level of interest and use of IRT methods has increased dramatically among health outcomes researchers. The NCI/DIA conference on June 24–25, 2004, was one of the first systematic opportunities to examine many challenging issues in applying IRT to the health outcomes field.
Method
Based on the conference presentations, we identified five issues important to future applications of IRT to health outcomes.
Results
The five key issues are as follows: (1) collaboration between academia, government and industry; (2) common versus unique item banks; (3) educating and establishing standards for use and reporting of IRT; (4) demonstrating the value of IRT; and (5) continuing efforts to improve the user friendliness of IRT software.
Conclusions
Moving forward will require a collaborative effort between academia, government agencies, and industry to design and conduct IRT research. A common item bank developed with collaboration from investigators from multiple institutions could be very valuable to the field. The establishment of consensus standards for use and reporting of IRT results would help users and consumers of the methodology. Clear documentation of how IRT can lead to better patient-reported outcome measures and more accurate understanding of substantive issues is essential. Academia, government and industry should continue current work to enhance the user-friendliness of the IRT software.
Similar content being viewed by others
References
Bech, P., Allerup, P., & Rosenberg, R. (1978). The Marke-Nyman temperament scale: evaluation of transferability using the Rasch item analysis. Acta Psychiatrica Scandinavica, 57, 49–58.
Granger, C. V., Hamilton, B. B., & Keith, R. A. et al. (1986). Advances in functional assessment for medical rehabilitation. Top Geriatric Rehabilitation, 1, 59–74.
Heinemann, A. W., Linacre, J. M., & Wright, B. D. et al. (1993). Relationships between impairment and physical disability as measured by the Functional Independence Measure. Archives of Physical Medicine and Rehabilitation, 74, 566–573.
Haley, S. M., McHorney, C. A., & Ware, J. E. (1994). Evaluation of the MOS SF-36 physical functioning scale (PF-10), I: Unidimensionality and reproducibility of the Rasch item scale. Journal of Clinical Epidemiology, 47, 671–684.
Gonin, R., Lloyd, S., & Cella, D. (1996). Establishing equivalence between scaled measures of quality of life. Quality of Life Research, 5, 20–26.
Cella, D., & Chang, C. H. (2000). A discussion of item response theory and its applications in health status assessment. Medical Care, 38, II-66–II-72.
Hambleton, R. K. (2000). Emergence of item response modeling in instrument development and data analysis. Medical Care, 38, II-60–II-65.
Hays, R. D., Morales, L. S., & Reise, S. P. (2000). Item response theory and health outcomes measurement in the 21st Century. Medical Care, 38, II-29–II-42.
McHorney, C. A., & Cohen, A. S. (2000). Equating health status measures with item response theory: Illustrations with functional status items. Medical Care, 38, II-43–II-59.
Ware, J. E., Bjorner, J. B., & Kosinski, M. (2000). Practical implications of item response theory and computerized adaptive testing: A brief summary of ongoing studies of widely used headache impact scales. Medical Care, 38, II-73–II-82.
Chan, K. S., Orlando, M., & Ghosh-Dastidar, B. et al. (2004). The interview mode effect on the Center for Epidemiology Studies Depression (CES-D) scale: An item response theory analysis. Medical Care, 42, 281–289.
Scholle, S. H., Weisman, C. S., & Anderson, R. T. (2004). The development and validation of the primary care satisfaction survey for women. Women’s Health Issues, 14, 35–50.
Bjorner, J. B., Kosinski, M., & Ware, J. E. (2003). Calibration of an item pool for assessing the burden of headaches: An application of item response theory to the headache impact test (HIT). Quality of Life Research, 12, 913–933.
Quality of Life Newsletter. (2004). Item banking special issue. Lyon, France: MAPI Research Trust.
National Institutes of Health. Patient-Reported Outcomes Measurement Information System: Dynamic Tools to Measure Health Outcomes from the Patient’s Perspective. Available at http://www.nihpromis.org/. Last accessed January 5, 2007.
Bjorner, J. B., & Ware, J. E. (1998). Using modern psychometric methods to measure health outcomes. Medical Outcomes Trust Monitor. Boston, Massachusetts. Available at: http://www.outcomes-trust.org/monitor/0498mntr.pdf. Last accessed January 7, 2007.
Lohr, K. N., Aaronson, N. K., & Alonso, J. et al. (1996). Evaluating quality-of-life and health status instruments: Development of scientific review criteria. Clinical Therapeutics, 18, 979–992.
Scientific Advisory Committee of the Medical Outcomes Trust. (2002). Assessing health status and quality-of-life instruments: Attributes and review criteria. Quality of Life Research, 11, 193–205.
Christensen, K. B., & Bjorner, J. B. (2003). SAS macros for Rasch based latent variable modeling. Technical Report # 03/13. Copenhagen: Department of Biostatistics.
STATA. (2003). Version 8. Texas: STATA Press.
Elashoff, J. D. (2000). nQuery advisor (Version 4.0). Cork, Ireland: Statistical Solutions.
Rasch Measurement Transactions. Developing item response theory software for outcomes and behavioral measurement: Solicitation of the Public Health Service for Small Business Innovation Research contract proposals #211. Available at: http://www.rasch.org/rmt/rmt182h.htm. Last accessed on January 7, 2007.
Author information
Authors and Affiliations
Corresponding author
Additional information
Preparation of this paper was supported in part by the UCLA/DREW Project EXPORT, National Institutes of Health, National Center on Minority Health & Health Disparities, (P20-MD00148–01) and the UCLA Center for Health Improvement in Minority Elders/Resource Centers for Minority Aging Research, National Institutes of Health, National Institute of Aging (AG-02–004).
Rights and permissions
About this article
Cite this article
Hays, R.D., Lipscomb, J. Next steps for use of item response theory in the assessment of health outcomes. Qual Life Res 16 (Suppl 1), 195–199 (2007). https://doi.org/10.1007/s11136-007-9175-7
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11136-007-9175-7