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  Meilssa M. Brown
  Published on: 29 November 2004
• Value-based medicine: Let's get it right
  Steven M. Kymes
  Published on: 2 November 2004

• Published on: 29 November 2004

  Authors' reply

  • Meilssa M. Brown, Director
  • Other Contributors:
    • Gary C. Brown

  Dear Editor

  We thank Drs. Kymes and Frick for their excellent letter regarding utility analysis as a health-related quality of life instrument. We agree that the use of primarily function-based quality of life instruments such as the NEI-VFQ-25 may result in missing many important variables in the quality of life arena, as well as limit applicability across all diseases.1 In contrast, preference-based quality of...

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  Dear Editor

  We thank Drs. Kymes and Frick for their excellent letter regarding utility analysis as a health-related quality of life instrument. We agree that the use of primarily function-based quality of life instruments such as the NEI-VFQ-25 may result in missing many important variables in the quality of life arena, as well as limit applicability across all diseases.1 In contrast, preference-based quality of life instruments such as utility analysis, are applicable across all diseases and encompass all variables that comprise quality of life, as well as the weighting of those variables. Of great additional importance is the fact that preference- based instruments can be used in healthcare economic analyses, especially utility analysis, while most function-based instruments have not been successfully used [1,2].

  Concerning the use of time trade-off and standard gamble utility analysis, we have found that the time trade-off methodology is easier for patients to comprehend and also is more sensitive to milder health states since there is risk aversion to the consequence of immediate death associated with the standard gamble variant [1,2]. Froberg and Kane3 have also shown that the time tradeoff method of utility has greater test- retest reliability, intra-rater reliability and inter-rater reliability than standard gamble methodology. In our experience, time trade-off utilities generally demonstrate better construct validity1 and a wider range between pre-intervention and post-intervention values than standard gamble utilities, thus resulting in more favourable cost-utility analysis, rather then less favourable analyses.

  In regard to quality of life respondents, we remain firm in our adherence to the fact that a basic pillar of value-based medicine is the use of utility values obtained from respondents with a health state in question [1,2]. We have found that utility value diminution in patients who actually have age-related macular degeneration ranges from 103% to 750% greater than the decrement estimated by treating ophthalmologists for the same condition [4,5]. This has been noted as well for non-ophthalmologic health states.6

  We respectfully disagree that community utility values generally overestimate the degree to which a disease decreases quality of life. In contrast, we and others [4-9] have noted that community and provider participants asked to evaluate the quality of life associated with a health state using utility value analysis generally underestimate the decrement in quality of life as compared to patients with that health state. In essence, patients who have lived with a health state are those best able to ascertain the quality of life associate with that health state. And it is usually worse than others imagine.

  In conclusion, we thank Drs. Kymes and Frick for their interest and fine comments and look forward to additional awareness in the arena of value-based medicine. As increasing numbers of those who allocate healthcare resources become aware that value-based medicine allows for higher quality care (by incorporating quality of life parameters that evidence-based primary clinical trials often ignore) and the most efficient use of resources, it will play a considerably greater role in the delivery of cost-effective, quality healthcare. When that takes place, all will benefit.

  References

  (1) Brown MM, Brown GC, Sharma, S. Evidence-Based to Value-Based Medicine. AMA Press (in press).

  (2) Brown MM, Brown GC, Sharma S, Landy J. Health care economic analyses and value-based medicine. Surv Ophthalmol 2003;48:204-223.

  (3) Froberg DG, Kane RL. Methodology for measuring health state preferences. II. Scaling methods. J Clin Epidemiol. 1989;42:459–471.

  (4) Brown GC, Brown MM, Sharma S. Difference between ophthalmologist and patient perceptions of quality-of-life associated with age-related macular degeneration. Can J Ophthalmol 2000;35:27-32.

  (5) Brown GC, Brown MM, Sharma S, Roth Z, Campanella J, Beauchamp G. The burden of age-related macular degeneration. A value-based analysis. Curr Opin Ophthalmol (in press).

  (6) Fryback DG, Dasbach EJ, Klein R, Klein BEK, Dorn N, Peterson K, Martin PA. The Beaver Dam Outcomes Study: initial catalog of health-state quality factors. Med Dec Making. 1993;13:89–102.

  (7) Stein JD, Brown MM, Brown GC, Sharma S, Hollands H. Quality of life with macular degeneration. Perceptions of patients, clinicians and community members. Brit J Ophthalmol 2003;87:8-12.

  (8) Landy J, Stein JD, Brown GC, Brown MM, Sharma S. Patient, community and clinician perceptions of the quality of life associated with diabetes mellitus. Medical Science Monitor 2002;8:543-548.

  (9) Sharma S, Brown GC, Brown MM, Hollands H, Robbins R, Shah G. Validity of the time trade-off and standard gamble methods of utility assessment in retinal patients. Br J Ophthalmol 2002;86:493-496.

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  Conflict of Interest:
  None declared.

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• Published on: 2 November 2004

  Value-based medicine: Let's get it right

  • Steven M. Kymes, Academic researcher
  • Other Contributors:
    • Kevin D. Frick

  Dear Editor

  In a fine recent editorial, Drs. Melissa and Gary Brown raised issues at the nexus of health policy and clinical science [1]. As utility assessment is relatively new to the visual sciences, understanding both the assumptions behind this work and the consequences of relaxing those assumptions is essential for high quality research and appropriate interpretation of the results.

  The use of com...

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  Dear Editor

  In a fine recent editorial, Drs. Melissa and Gary Brown raised issues at the nexus of health policy and clinical science [1]. As utility assessment is relatively new to the visual sciences, understanding both the assumptions behind this work and the consequences of relaxing those assumptions is essential for high quality research and appropriate interpretation of the results.

  The use of community-elicited utilities (i.e., including people not suffering the disease in the elicitation study) in economic evaluation should be given more than minimal consideration. Economic evaluations are intended to inform health policy makers by assessing the value society places on the cure or prevention of disease. Community-based utilities typically reflect larger estimates of utility loss than those elicited from patients and result in a more favourable analysis of the cost- effectiveness of preventive interventions than those relying on patient- elicited utilities [2]. At the same time, estimating community-elicited utilities requires the development of easily understood scenarios to assist community members in understanding life with the disease [3], thus, many investigators prefer to rely on patient-elicited utilities. Rather than dismiss this approach, economic evaluation in ophthalmology would be greatly facilitated by a catalogue of community-elicited utilities related to ocular diseases developed through the standard gamble or time trade-off methods or responses to health status questionnaires that include algorithms to estimate health utilities.

  While the Browns caution against the use of functionally based health -related quality of life instruments (e.g., the NEI-VFQ) in economic evaluation, we would like to offer an alternative explanation for this concern. Most disease specific instruments are based in psychometric theory and designed to measure change in the patients self-reported health status in investigator defined domains [4]. Domain scores do not reflect the importance the respondent assigns to the activities, but scoring algorithms developed by the instrument designer. The result is a metric that is often meaningful to clinicians, but does not reflect the value the patient or society places on the health state. This limits generalizability across disease groups, as well as investigators’ ability to comment on the most efficient way to screen for, or treat, an ophthalmic condition affecting multiple areas of physical, mental or emotional function.

  Finally, the standard gamble elicitation method should not be dismissed off-handedly. More frequent use of the time trade-off reflects the method’s intuitive appeal rather than theoretical superiority. As opposed to the time-tradeoff in which the anchor event (i.e., death, blindness, etc.) occurs in the future, in the standard gamble the event is immediate. This provides an estimate of the person’s risk preference unconfounded by time. The time trade-off consistently results in higher estimates of utility loss than the standard gamble [5,6] and resulting in less favourable cost-effectiveness results for preventing the condition.

  We hope that our comments will help future work to be pragmatic and as theoretically sound as possible. Understanding the theoretically optimal methods and the need to make practical accommodations are important if we are to avoid overstating the quality of our methods or the value of our findings.

  Steven M. Kymes, Ph.D. Washington University School of Medicine Department of Ophthalmology and Visual Sciences

  Kevin D. Frick, Ph.D. Johns Hopkins Bloomberg School of Public Health Department of Health Policy and Management

  References

  (1) Brown MM, Brown GC. Value based medicine: Let's get it right. British Journal of Ophthalmology 2004;88(8):979.

  (2) Krahn MD, Ritvo P, Irvine J, Tomlinson G, Bremmer KE, Bezjak A, et al. Patient and community preferences for outcomes in prostate cancer: Implications for clinical policy. Medical Care 2003;41(1):153-64.

  (3) Gold MR, Siegel JE, Russell LB, Weinstein MC. Cost-Effectiveness in Health and Medicine. 1 ed. New York: Oxford University Press, 1996.

  (4) Mangione CM, Lee PP, Gutierriez PR, Spritzer KL, Berry S, Hays RD. Development of the 25-Item National Eye Institute Visual Function Questionnaire. Archives of Ophthalmology 2001;119(7):1050-8.

  (5) Salomon JA, Murray CJL. A multi-method approach to measuring health-state valuations. Health Economics 2004;13:281-90.

  (6) Jampel HD. Glaucoma Patients' Assessment of Their Visual Function and Quality of Life. Transactions of the American Ophthamological Society 2001;99:301-17.

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  Conflict of Interest:
  None declared.

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