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A J Moskowitz

Publications and source records attributed to A J Moskowitz.

6 recordsLinked to original sources
PubMed1989

A patient with new Q waves: methods for decision making in the individual patient.

Decision analysis, an analytic approach to making decisions when uncertainty is present, has its foundation in probability and utility theory. It provides insights into the trade-offs that are involved when a selection must be made among patient management strategies. In general, several broad steps are involved. The process begins by formulating the clinical problem as a well focused choice among a limited set of clinical etiologies. These strategies are then structured explicitly in a model that depicts the clinical events that may ensue from each option. By assigning probability values to each outcome, the weighted average outcome or expected utility can be calculated for each alternative strategy. The strategy with the highest expected utility is the optimal one. The methods of decision analysis offer a number of distinct advantages. These include: 1) providing a structure with which to simplify and focus clinical dilemmas; 2) providing a forum for discussing clinical reasoning; and 3) developing a consensus among groups of decision makers.

Aged↗
PubMed1988

Dealing with uncertainty, risks, and tradeoffs in clinical decisions. A cognitive science approach.

To generate hypotheses about how physicians make difficult clinical decisions, we analyzed transcripts of the "thinking aloud" behavior of expert clinicians making a testing or treatment decision with an uncertain diagnosis. We compared the clinicians' reasoning with a decision analysis of the same problem. The experts did not formulate a global outline of their decision, but chained together a sequence of decisions based on available and incomplete information. Despite effective and efficient problem solving, the clinicians used numeric terms only as symbolic representations of likelihood, used limited information in choosing among alternatives, and dismissed the possibility that a less conventional strategy, empiric therapy, might yield equivalent outcome. We describe cognitive problem-solving strategies and knowledge representations that permit persons to make successful decisions despite limited processing resources. The same cognitive procedures probably contribute to observed errors in decision-making under uncertainty.

Amphotericin B↗
PubMed1987

Decision analysis: a progress report.

Since its introduction into medicine 15 years ago, decision analysis has been applied to difficult clinical problems. Several important advances have made the process more practical and acceptable: computer programs that eliminate the need for burdensome calculations, improved techniques for designing analytic models, the ability to carry out sensitivity analyses over several dimensions simultaneously, and the elaboration of clinically relevant measures of utility. Using these techniques, analysts have addressed many important clinical issues including screening for and prevention of disease, tradeoffs among tests and treatments, and the interpretation of clinical data under conditions of uncertainty. Problems with the approach remain and applications have not been extensive, but decision analysis is evolving as a powerful clinical tool and gradually is gaining acceptance in medical practice.

Bayes Theorem↗
PubMed1986

Clinical decision analysis using microcomputers. A case of coexistent hepatocellular carcinoma and abdominal aortic aneurysm.

Many difficult medical decisions involve uncertainty. Decision analysis-an explicit, normative and analytic approach to making decisions under uncertainty-provides a probabilistic framework for exploring difficult problems in nondeterministic domains. As the methodology has advanced, clinical decision analysis has been applied to increasingly complex medical problems and disseminated widely in the medical literature. Unfortunately, this approach imposes a heavy computational burden on analysts. Microcomputer-based decision-support software can ease this burden.

Aged↗
PubMedDate not supplied

A peripartum neurologic event: shooting from the hip.

We have shown that a simplified model, generated quickly in response to an emergency consultation, may provide useful insights in certain situations. A more developed model was useful in verifying these insights. Because the more complex model considered a longer time horizon than the simple model, it allows us to consider questions regarding long-term benefits of aneurysm repair. When modeling any problem, the most important reason for performing decision analysis is to gain insight from analyzing the clinical setting and from constructing the model. The quantitative results are usually of only minor importance. However, our most important insights are sometimes gained by looking beyond the quantitative level to understand the interactions of various effects within the model. In this case, it was those insights that were of the greatest benefit to the patient in arriving at a decision to have cerebral arteriography.

Adult↗