Are We Practicing Evidence Based Medicine

The goal of using evidence in medicine is to come closest to practice that represents best practice and to produce optimal health outcomes. Thus, it is desirable to evaluate the impact of medical knowledge on actual practice, in terms of both the practices themselves and, ultimately, their public health impact. On one level, the impact of evidence-based guidelines can be assessed by measuring practitioners' beliefs and knowledge over a time period relevant to the introduction of new knowledge by means of surveys. However, such surveys may not fully reflect actual practice and are an indirect surrogate for health outcomes.

The translation of knowledge into practice is often measured using administrative datasets such as Medicare claims data, which are assumed to reflect some robust proportion of procedures performed on enrollees, for example, screening mammography examinations. Such data are more objective than physician self-report, but may not capture all procedures of interest, as enrollees may undergo procedures outside the Medicare reimbursement system. For example, Medicare analyses are usually restricted to procedures in the age 65+ population for which the U.S. government is billed.

Looking at effects of guidelines on health outcomes (such as cancer incidence and mortality) is of great interest. However, these endpoints are often the most difficult to evaluate with confidence in terms of their link to new knowledge, because so many other factors are likely to influence rates of disease. For the United States, the most comprehensive data on disease incidence and mortality are compiled by the SEER program (Surveillance, Epidemiology, and End Results). SEER is a national dataset that is designed to reflect the total cancer experience of the U.S. population. Despite these caveats, occasionally a breakthrough in cancer medicine results in clearly measurable improvements in outcomes. Feuer et al.17 reported on dramatic improvements in testicular cancer outcome statistics in SEER after the completion of a successful clinical trial of cisplatin, vinblastine, and bleomycin; improved survival rates then reached a plateau, apparently indicating the limits of diffusion of the results of the trial into medical practice.

Questions of impact of knowledge may be addressed by looking at rates of disease and mortality over a time frame relevant to the introduction of a given guideline, or to media coverage of, for example, a diagnosis of cancer in or a cancer screening or treatment procedure undergone by a celebrity. This approach is essentially an ecologic study design and is subject to the limitations described earlier. In one notable case, rates of breast-conserving surgery, which had been increasing (relative to mastectomies) in the 1980s, appeared to decline abruptly, albeit briefly, after widespread publicity about a mastectomy undergone by then First Lady Nancy Reagan. Nattinger et al.18 carefully documented this change by analyzing news reports and the appropriate time period of subsequent SEER data.

Despite this evidence, other unmeasured factors affecting these rates are undoubtedly still at play, and outside of the context of a controlled trial it is extremely difficult to establish a causal effect that an intervening factor may have had on population mortality rates.

Progress in fighting cancer is often measured in terms of SEER-derived statistics; again, however, it is difficult to ascribe changes to a single factor. Recent reductions in deaths from breast cancer could be related to more widespread mammography screening, but improvements in breast cancer therapy are also likely to have an effect on mortality, and it is impossible to tease apart their effects on population-based mortality rates.

Another example of the use of national data to assess the impact of evidence-based medicine is that of colorectal cancer. The U.S. Preventive Services Task Force recommends screening for colorectal cancer by any of four methods; however, the reported prevalence of screening is below 50% in many states. As for the rates of disease, long-term declines in colorectal cancer incidence have slowed. Although screening is thought to play a role in reducing incidence and mortality, risk factors for colorectal cancer—physical inactivity and obesity—have increased in the population.19 Although it is not possible to separate the effects of screening, improvements in therapy, and risk factors completely, they do act in different directions; the increase in physical obesity could conceivably explain the slowing of declines in incidence.

A common error in interpreting population cancer statistics is in the use of 5-year survival as a gauge of progress against a disease. Five-year survival is an appropriate outcome in a trial of a therapy, where all subjects in the numerator and denominator of the survival rate have the disease and a comparison is made between two groups randomly assigned to treatment after their diagnosis. In the general population, however, 5-year survival is much more likely to be a function of the date of diagnosis relative to the course of the disease. As a result, 5-year survival is unrelated to mortality and is ultimately a misleading statistic in this context.20 For example, changes in screening patterns can advance the date of diagnosis without changing risk of death, thus artifactually lengthening survival time.

Other relevant outcomes beyond physician practice but shy of hard health outcomes include smoking rates, which are known to be closely related to rates of lung and oral cancer as well as a number of other health outcomes and total mortality. The Behavioral Risk Factor Surveillance Survey and National Household Survey on Drug Abuse measure the prevalence of smoking in the United States and can be used to estimate the impact of smoking-cessation programs and tobacco-related policies.

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