Health Condition Impacts in a Nationally Representative Cross-Sectional Survey Vary Substantially by Preference-Based Health Index

Abstract

Importance: Many cost-utility analyses rely on generic utility measures for estimates of disease impact. Commonly used generic preference-based indexes may generate different absolute estimates of disease burden despite sharing anchors of dead at 0 and full health at 1.0. Objective: We compare the impact of 16 prevalent chronic health conditions using 6 utility-based indexes of health and a visual analog scale. Design: Data were from the National Health Measurement Study (NHMS), a cross-sectional telephone survey of 3844 adults aged 35 to 89 years in the United States. Main Outcome Measures: The NHMS included the EuroQol-5D-3L, Health and Activities Limitation Index (HALex), Health Utilities Index Mark 2 (HUI2) and Mark 3 (HUI3), preference-based scoring for the SF-36v2 (SF-6D), Quality of Well-Being Scale, and visual analog scale. Respondents self-reported 16 chronic conditions. Survey-weighted regression analyses for each index with all health conditions, age, and sex were used to estimate health condition impact estimates in terms of quality-adjusted life years (QALYs) lost over 10 years. All analyses were stratified by ages 35 to 69 and 70 to 89 years. Results: There were significant differences between the indexes for estimates of the absolute impact of most conditions. On average, condition impacts were the smallest with the SF-6D and EQ-5D-3L and the largest with the HALex and HUI3. Likewise, the estimated loss of QALYs varied across indexes. Condition impact estimates for EQ-5D-3L, HUI2, HUI3, and SF-6D generally had strong Spearman correlations across conditions (i.e., >0.69). Limitations: This analysis uses cross-sectional data and lacks health condition severity information. Conclusions: Health condition impact estimates vary substantially across the indexes. These results imply that it is difficult to standardize results across cost-utility analyses that use different utility measures.

Keywords

cost utility analysis utility inconsistencies quality of life utility measurement

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References

Gold

Russell

Weinstein

, ed. Cost-Effectiveness in Health and Medicine. New York: Oxford University Press; 1996.

Miller

Robinson

Lawrence

RS.

Valuing Health for Regulatory Analysis. Washington, DC: National Academies Press; 2006.

Brauer

Rosen

Greenberg

Neumann

PJ.

Trends in the measurement of health utilities in published cost-effectiveness analyses. Value Health. 2006;9(4):213–8.

Franks

Hanmer

Fryback

. Relative disutilities of 47 risk factors and conditions assessed with seven preference-based health status measures in a national U.S. sample: toward consistency in cost-effectiveness analyses. Med Care. 2006;44:478–85.

Fryback

Dunham

Palta

. The National Health Measurement Study: simultaneous U.S. norms for six generic health-related quality-of-life instruments. Med Care. 2007;45:1162–70.

National Archive of Computerized Data on Aging. United States National Health Measurement Study, 2005–2006. http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/23263?geography%5b0%5d=United+States&paging.startRow=226. Accessed 10 February 2015.

Rabin

de Charro

EQ-5D: a measure of health status from the EuroQol Group. Ann Med. 2001;33:337–43.

Shaw

Johnson

Coons

SJ.

US valuation of the EQ-5D health states: development and testing of the D1 valuation model. Med Care. 2005;43:203–20.

Erickson

. Evaluation of a population-based measure of quality of life: the Health and Activity Limitation Index (HALex). Qual Life Res. 1998;7:101–14.

10.

Feeny

Furlong

Torrance

. Multiattribute and singleattribute utility functions for the Health Utilities Index Mark 3 system. Med Care. 2002;40:113–28.

11.

Feeny

Torrance

Furlong

Health Utilities Index. In: Spilker

, ed. Quality of Life and Pharmacoeconomics in Clinical Trials. Philadelphia, PA: Lippincott-Raven Press; 1996.

12.

Torrance

Feeny

Furlong

Barr

Zhang

Wang

Multi-attribute preference functions for a comprehensive health status classification system: Health Utilities Index Mark 2. Med Care. 1996;34:702–22.

13.

Kaplan

Sieber

Ganiats

TG.

The Quality of Well-Being Scale: comparison of the interviewer-administered version with a self-administered questionnaire. Psychol Health. 1997;12:783–91.

14.

Andresen

Rothenberg

Kaplan

RM.

Performance of a self-administered mailed version of the Quality of Well-Being (QWB-SA) questionnaire among older adults. Med Care. 1998;36:1349–60.

15.

Brazier

Roberts

The estimation of a preference-based measure of health from the SF-12. Med Care. 2004;42:851–9.

16.

Feeny

Spritzer

Hays

. Agreement about identifying patients who change over time: cautionary results in cataract and heart failure patients. Med Decis Making. 2012;32:273–86.

17.

Revicki

Feeny

Hunt

Cole

Analyzing oncology clinical trials data using the Q-TWiST method: clinical importance and sources for health state preference data. Qual Life Res. 2006;15:411–23.

18.

Centers for Disease Control and Prevention. National Health Interview Survey. 2005 Data Release. http://www.cdc.gov/nchs/nhis/nhis_2005_data_release.htm. Accessed 10 February 2015.

19.

Fryback

Palta

Cherepanov

Bolt

Kim

JS.

Comparison of 5 health-related quality-of-life indexes using item response theory analysis. Med Decis Making. 2010;30:5–15.

20.

Laupacis

Inclusion of drugs in provincial drug benefit programs: who is making these decisions, and are they the right ones?

Can Med Assoc J. 2002;166:44–47.

21.

Laupacis

Incorporating economic evaluations into decision-making: the Ontario experience. Med Care. 2005;43(Suppl.):II-15–II-19.

22.

National Institute for Health and Clinical Excellence. Guide to the methods of technology appraisal. National Institute for Health and Clinical Excellence; 2013. http://publications.nice.org.uk/pmg9. Accessed July 2015.

23.

Kopec

Willison

KD.

A comparative review of four preference-weighted measure of health-related quality of life. J Clin Epidemiol. 2003;56:317–25.

24.

Feeny

Standardization and regulatory guidelines may inhibit science and reduce the usefulness of analyses based on the application of preference-based measures for policy decisions. Med Decis Making. 2013;33:316–19.

25.

Paz

Liu

Fongwa

Morales

Hays

RD.

Readability estimates for commonly used health-related quality of life surveys. Qual Life Res. 2009;18:889–900.

26.

Cherepanov

Palta

Fryback

DG.

Underlying dimensions of the five health-related quality-of-life measures used in utility assessment evidence from the National Health Measurement Study. Med Care. 2010;48:718–25.

27.

Palta

Chen

Kaplan

Feeny

Cherepanov

Fryback

DG.

Standard error of measurement of 5 health utility indexes across the range of health for use in estimating reliability and responsiveness. Med Decis Making. 2011;31:260–9.

28.

Raisch

Feeney

Goff

Jr . Baseline comparison of three health utility measures and the feeling thermometer among participants in the Action to Control Cardiovascular Risk in Diabetes Trial. Cardiovasc Diabetol. 2012;11:35.

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