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To measure the accuracy of automated tuberculosis case detection.

Develop the methodological foundation for interactive use of Markov process decision models by patients and physicians at the bedside.

Clinical decision making is driven by information in the form of patient data and clinical knowledge. Currently prevalent systems used to store and retrieve this information have high failure rates, which can be traced to well-established system constraints. The authors use an industrial process model of clinical decision making to expose the role of these constraints in increasing variability in the delivery of relevant clinical knowledge and patient data to [...]

In March of 1997, the National Research Council (NRC) of the National Academy of Sciences issued the report, "For the Record: Protecting Electronic Health Information." Concluding that the current practices at the majority of health care facilities in the United States are insufficient, the Council delineated both technical and organizational approaches to protecting electronic health information. The Beth Israel Deaconess Medical Center recently implemented a proof-of-concept, Web-based, cross-institutional medical record [...]

Errors of omission are a common cause of systems failures. Physicians often fail to order tests or treatments needed to monitor/ameliorate the effects of other tests or treatments. The authors hypothesized that automated, guideline-based reminders to physicians, provided as they wrote orders, could reduce these omissions.

To explore the informatic requirements in the home care of chronically ill patients.