Many new resources are arriving to help the diagnostician. More diagnostic tests are becoming available, and more of the available tests are being subjected to rigorous evaluation of their accuracy, precision, and utility in practice.^{1} Parts of the clinical examination are also being studied rigorously for their characteristics as diagnostic tests.^{2,3} Frontline clinicians are gaining increasing access to high-quality evidence about diagnostic tests in textbooks^{4,5} and in systematic reviews.^{1,6,7} Using this evidence requires more than knowing a test's discriminatory power. Clinicians also need to estimate pretest probabilities for the disorders being considered.^{8,9} One would start with pretest probabilities for each disorder, combine them with the test's likelihood ratios or sensitivity and specificity, and then compare the resulting post-test probabilities to one's action thresholds to decide what to do next.^{10,11}

But where do these pretest probabilities come from? Some say clinicians can generate pretest probabilities on the basis of clinical experience, drawing on their memories of prior cases with the same clinical problem. Yet research has shown that clinicians' estimates of probability vary widely and are often inaccurate.^{12–15} This is because clinicians' memories are fallible and their thinking is subject to numerous biases.^{16–19} Clinicians tend to recall recent or striking numerator cases without the proper denominators, which leads to error in estimating probability. Therefore, by itself, clinical experience appears insufficient to guide accurate probability estimation.

Clinical care research represents another source of information about disease probability. In such research, investigators gather patients with a defined clinical problem, carry out a diagnostic evaluation, then record the diagnostic yield in terms of the frequency of underlying disorders found.^{20,21} Widely known examples include studies of patients with syncope^{22,23} and fever of unknown origin.^{24,25} If critical appraisal of this evidence suggests that it is valid, important, and applicable to their patients, clinicians can use the frequencies of disease from these studies as starting points for estimating pretest probabilities in their own patients. Clinicians would then need to adjust these probabilities up or down, depending on features of their patients or their practices.^{26,27}

But how often is this research evidence available to guide estimates of pretest probability? We knew of some examples, but we didn't know how often we could find it, and we found no published research of this question. Therefore, we surveyed our hospital medicine service to ascertain our patients' clinical problems, and then surveyed the medical literature for research evidence about the frequency of underlying diseases that cause these clinical problems. Our research aims were: 1) to measure the proportion of patients on our clinical service who presented with clinical problems for which research evidence was available to guide our estimates of pretest probability; and 2) to discern whether any of this evidence was of sufficient quality that we would want to use it for clinical decision making.