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

Author

Listed:
  • Janel Hanmer
  • Dasha Cherepanov
  • Mari Palta
  • Robert M. Kaplan
  • David Feeny
  • Dennis G. Fryback

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.

Suggested Citation

  • Janel Hanmer & Dasha Cherepanov & Mari Palta & Robert M. Kaplan & David Feeny & Dennis G. Fryback, 2016. "Health Condition Impacts in a Nationally Representative Cross-Sectional Survey Vary Substantially by Preference-Based Health Index," Medical Decision Making, , vol. 36(2), pages 264-274, February.
    • Handle: RePEc:sae:medema:v:36:y:2016:i:2:p:264-274
    DOI: 10.1177/0272989X15599546
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    Cited by:

    1. Janel Hanmer & Barry Dewitt & Lan Yu & Joel Tsevat & Mark Roberts & Dennis Revicki & Paul A Pilkonis & Rachel Hess & Ron D Hays & Baruch Fischhoff & David Feeny & David Condon & David Cella, 2018. "Cross-sectional validation of the PROMIS-Preference scoring system," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-13, July.
    2. Guillem López-Casasnovas & José Luis Pinto Prades, 2022. "QALY Maximization and the Social Optimum," Hacienda Pública Española / Review of Public Economics, IEF, vol. 242(3), pages 111-127, September.

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