Probabilistic reasoning in which test results (not just laboratory investigations, but history, physical exam, or any aspect for the diagnostic process) are combined with prior beliefs about the probability of a particular disease. One way of recognizing the need for a Bayesian approach is to recognize the difference between the performance of a test in a population vs. in an individual. At the population level, we can say that a test has a sensitivity and specificity of, say, 90%—i.e., 90% of patients with the condition of interest have a positive result and 90% of patients without the condition have a negative result. In practice, however, a clinician needs to attempt to predict whether an individual patient with a positive or negative result does or does not have the condition of interest. This prediction requires combining the observed test result not just with the known sensitivity and specificity, but also with the chance the patient could have had the disease in the first place (based on demographic factors, findings on exam, or general clinical gestalt).
Beers criteria define medications that generally should be avoided in ambulatory elderly patients, doses or frequencies of administration that should not be exceeded, and medications that should be avoided in older persons known to have any of several common conditions. The criteria were originally developed using a formal consensus process for combining reviews of the evidence with expert input. The criteria for inappropriate use address commonly used categories of medications such as sedative-hypnotics, antidepressants, antipsychotics, antihypertensives, nonsteroidal anti-inflammatory agents, oral hypoglycemics, analgesics, dementia treatments, platelet inhibitors, histamine-2 blockers, antibiotics, decongestants, iron supplements, muscle relaxants, gastrointestinal antispasmodics, and antiemetics. The criteria were intended to guide clinical practice, but also to inform quality assurance review and health services research.
Most would agree that prescriptions for medications deemed inappropriate according to Beers criteria represent poor quality care. Unfortunately, harm does not only occur from receipt of these inappropriately prescribed medications. In one comprehensive national study of medication-related emergency department visits for elderly patients, most problems involved common and important medications not considered inappropriate according to the Beers criteria—principally, oral anticoagulants (e.g., warfarin), antidiabetic agents (e.g., insulin), and antiplatelet agents (aspirin and clopidogrel).
An attribute or achievement that serves as a standard for other providers or institutions to emulate. Benchmarks differ from other standard of care goals, in that they derive from empiric data—specifically, performance or outcomes data. For example, a statewide survey might produce risk-adjusted 30-day rates for death or other major adverse outcomes. After adjusting for relevant clinical factors, the top 10% of hospitals can be identified in terms of particular outcome measures. These institutions would then provide benchmark data on these outcomes. For instance, one might benchmark "door-to-balloon" time at 90 minutes, based on the observation that the top-performing hospitals all had door-to-balloon times in this range. In regard to infection control, benchmarks would typically be derived from national or regional data on the rates of relevant nosocomial infections. The lowest 10% of these rates might be regarded as benchmarks for other institutions to emulate.
The prominent warning labels (generally printed inside black boxes) on packages for certain prescription medications in the United States. These warnings typically arise from post-market surveillance or post-approval clinical trials that bring to light serious adverse reactions. The U.S. Food and Drug Administration (FDA) subsequently may require a pharmaceutical company to place a black box warning on the labeling or packaging of the drug. Although medications with black box warnings often enjoy widespread use and, with cautious use, typically do not result in harm, these warnings remain important sources of safety information for patients and health care providers. They also emphasize the importance of continued, post-market surveillance for adverse drug reactions for all medications, especially relatively new ones.
The blunt end refers to the many layers of the health care system not in direct contact with patients, but which influence the personnel and equipment at the sharp end who do contact patients. The blunt end thus consists of those who set policy, manage health care institutions, and design medical devices, and other people and forces, which, though removed in time and space from direct patient care, nonetheless affect how care is delivered. Thus, an error programming an intravenous pump would represent a problem at the sharp end, while the institution's decision to use multiple different types of infusion pumps, making programming errors more likely, would represent a problem at the blunt end. The terminology of "sharp" and "blunt" ends corresponds roughly to active failures and latent conditions.