Trust and confidence are critical to the success of health care models. There are two main methods for achieving this: transparency (people can see how the model is built) and validation (how well the model reproduces reality). This report describes recommendations for achieving transparency and validation developed by a taskforce appointed by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making. Recommendations were developed iteratively by the authors. A nontechnical description--including model type, intended applications, funding sources, structure, intended uses, inputs, outputs, other components that determine function, and their relationships, data sources, validation methods, results, and limitations--should be made available to anyone. Technical documentation, written in sufficient detail to enable a reader with necessary expertise to evaluate the model and potentially reproduce it, should be made available openly or under agreements that protect intellectual property, at the discretion of the modelers. Validation involves face validity (wherein experts evaluate model structure, data sources, assumptions, and results), verification or internal validity (check accuracy of coding), cross validity (comparison of results with other models analyzing the same problem), external validity (comparing model results with real-world results), and predictive validity (comparing model results with prospectively observed events). The last two are the strongest form of validation. Each section of this article contains a number of recommendations that were iterated among the authors, as well as among the wider modeling taskforce, jointly set up by the International Society for Pharmacoeconomics and Outcomes Research and the Society for Medical Decision Making.

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Lifestyle modification is likely to have important effects on the morbidity and mortality of diabetes and should be recommended to all high-risk people. The program used in the DPP study may be too expensive for health plans or a national program to implement. Less expensive methods are needed to achieve the degree of weight loss seen in the DPP.

Behind the wide acceptance of the idea of "evidence-based medicine" are two curious facts: There are two very different approaches to applying evidence to medicine, and the most commonly cited definition applies to only one of them. This paper describes the problem that we are asking "evidence" to solve and the different methods by which evidence can be used to help solve that problem, and recommends a unified approach.

Considerable indirect evidence, based on the natural history of colorectal cancer and the ability of tests to detect adenomas and invasive cancers, suggests that screening for colorectal cancer reduces mortality. Without screening, a 50-year-old person at average risk has approximately a 530-in-10,000 chance of developing invasive colorectal cancer in the rest of his or her life and approximately a 250-in-10,000 chance of dying from it. Analysis of indirect evidence with a mathematic model indicates that screening persons for 25 years, from the age of 50 to the age of 75 years should reduce the chance of developing or dying from colorectal cancer by 10% to 75%, depending on which screening tests are used and how often screening is done. Screening for colorectal cancer is optional. A possible recommendation is that annual fecal occult blood tests and 65-cm flexible sigmoidoscopy every 3 to 5 years be done for average-risk men and women who are between 50 and 75 years of age. In addition to having annual fecal occult blood tests, persons with first-degree relatives with colorectal cancer can be offered barium enemas instead of sigmoidoscopies every 3 to 5 years.

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Indirect evidence indicates that cervical cancer screening should reduce the incidence and mortality of invasive cervical cancer by about 90%. In the absence of screening, a 20-year-old average-risk woman has about a 250 in 10,000 chance of developing invasive cervical cancer during the rest of her life, and about a 118 in 10,000 chance of dying from it. Screening at least every 3 years from 20 to 75 years of age will decrease these probabilities by about 215 in 10,000 and 107 in 10,000, respectively, and will increase a 20-year-old woman's life expectancy by about 96 days. The particular age at which screening is begun (for example, 17 or 20 years), the requirement of several initial annual examinations before reducing the frequency, and screening every 1 or 2 years compared with every 3 years improves the effectiveness by less than 5%. Screening is recommended at least every 3 years from about age 20 to about age 65 years.