MEASURING HEALTH

Accountability is now a priority in health care. Measuring outcomes in a way that allows broader comparison of interventions has become the standard of care. The topic of HRQOL has become increasing popular not only because of extended survival from once terminal diseases, but because traditional measures of mortality and other biological outcomes don't adequately measure effectiveness of interventions designed to improve life quality. There is also a growing appreciation for the need to use such measures to assess which services produce the greatest amount of health for the money spent. Understanding how best to provide such documentation is the focus of the UCSD Health Outcomes Assessment Program.

Different methods of assessing HRQOL

There are two general classes of HRQOL measures - psychometrically-based and utility-based - and choices of whether to use a disease-specific or general measure.

Psychometrically-based measures

Strength of psychometric measures: multiple dimensions of health assessed      Limitations of psychometric measures: inability to integrate the information in economic analyses of treatment outcome, the subjectivity of reporting perceived ability, and that mortality cannot be incorporated into the data analysis SF-36

Utility-based measures

A panel convened in 1993 by the U.S. Department of Health and Human Services suggested that standardized outcomes analyses be conducted to evaluate the cost/effectiveness of medical care (Gold et al, 1996). One way to directly compare relative treatment effectiveness is to examine the impact of interventions on the utility gained. This requires certain characteristics of an assessment instrument possessed by utility-based and preference-based instruments. Namely, scores will reflect a person’s (or a community’s) judgment of relative desirability for different health states, with numerical values on a scale of 0 (anchored as death) to 1.0 ( anchored as optimum health). The resultant score thus allows morbidity and mortality to be combined into a single weighted measure, quality adjusted life years (QALYs). The benefits of health care can be expressed in terms of the years of life they produce, adjusted for reduced quality of life. The most popular term for this concept is Quality-Adjusted Life-Years (QALY's) (Weinstein & Stason, 1977), although other terms such as Well Years have also been used. For example, if a cigarette smoker died of heart disease at age 50 and we would have expected him to live to age 75, it might be concluded that the disease cost him 25 life-years. If 100 cigarette smokers died at age 50 (and also had life expectancies of 75 years), we might conclude that 2,500 (100 men x 25 years) life-years had been lost. However, we should not assume that these 25 years lost were disease-free or disability-free. That is, death is not the only outcome of concern; many cigarette smokers would be expected to suffer myocardial infarction or develop pulmonary diseases that would leave them somewhat disabled to varying degrees. Although they are still alive, the quality of their lives has diminished. The use of a concept such as QALYs permits all degrees of disability to be compared to one another. The QALY combines data on the total life years gained from an intervention with data on the utility (or value) of health states for those years, to give a single measure of achievement or output. By calculating the cost per QALY gained for different clinical procedures or even different social problems, available resources can be directed toward interventions that maximize health gain (Chisholm, Healey & Knapp,1997). That is, a disease that reduces the quality of life by one-half will take away .5 QALYs over the course of 1 year. If it affects two people, it will take away 1.0 QALY (equal to 2 X .5) over a 1-year period. A medical treatment that improves the quality of life by .2 for each of five individuals will result in a production of 1 QALY if the benefit is maintained over a 1-year period. Using this system, it is possible to express the benefits of various programs by showing how many QALYs they produce (Kaplan & Anderson, 1990). Using this common metric of QALYs also allows one to introduce cost into the direct comparison of programs. Thus, this approach provides a framework within which to make policy decisions that require selection between competing alternatives. The Health Utility Index (Torrance and Feeny, 1989) and the Quality of Well-being Scale (Kaplan and Bush , 1982) are two examples of utility-based measures.

QWB

The QWB assesses a patient’s objective level of functioning in three domains: mobility, physical activity, and social activity. A distinction is made between "functional ability" and "functional performance" (Anderson, Kaplan et al, 1989), namely a patient is asked to report activity performed rather than the patient’s perception of what could possibly have been performed. The QWB concentrates on functional performance (or what the individual actually did) on the past 6 completed days. In addition to these three domains, the QWB assesses the presence of a wide array of symptoms. On any particular day, nearly 80% of the general population is optimally functional, yet over an interval of six days, only 12% experience no symptoms (Kaplan, et al., 1976). Even if these symptoms do not affect a patient’s functioning, they do lower quality of life. Our experience has shown that the QWB instrument is, in its operation, sensitive to the health-related issues that are most important to people, and it is thus capable of capturing even small variations in health status.

QWB-SA

One of the criticisms of the QWB is that it is more expensive and difficult to administer than competing measures, such as the SF-36. The QWB is relatively long and complex because it has some branching and probe questions and requires a trained interviewer. We therefore developed a self-administered QWB &endash; referred to as the Quality of Well-Being scale, Self-Administered (QWB-SA) that addresses some of these issues (Kaplan, Ganiats, and Sieber, 1996). There are several strengths of the QWB-SA       Includes assessment of symptoms in addition to various areas of functioning       The expanded the list of symptoms now includes several mental health items       To reduce recall bias, the QWB-SA assesses only the 3 days prior to completion of the questionnaire       The scoring of the instrument utilizes population-derived preference weights Use of the QWB-SA is growing rapidly. The UCSD Health Outcomes Assessment Program is conducting a strong and diverse research program toward establishing the psychometric properties of this new measure. Current studies are addressing the ability of the QWB-SA to detect changes in samples of migraineurs, cataract surgery patients, mental health populations, arthritis patients, as well as validating the sensitivity of this measure translated in Spanish, French, and German

An extensive bibliography is available