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At least 703 records · Page 39Linked to original sources
PubMed1992

Evaluating drug prescribing in a large, ambulatory population: application of an embedded expert system.

DUR is a process of problem detection and intervention designed to improve the quality and economy of drug prescribing. Retrospective DUR attempts to detect and address patterns of prescribing that might be indicative of inappropriate therapy. When the process is extended to a largely ambulatory population such as Medicaid beneficiaries, a number of complications are introduced due to the large numbers of patients and sparsity of data. In order to examine the impact of implementing a Medicaid DUR program, we developed a system that would apply screening criteria to prescription claims. It has been used to screen prescribing of groups of two antihypertensive drugs in the 1990 Maryland Medicaid population for 177,409 Medicaid eligible individuals. Potentially significant problems were detected with respect to dosing, duplication of therapeutic agents and drug interactions. The system represents, we believe, a significant improvement in the ability to detect and report prescribing decisions by increasing the specificity of the detection system. By the application of this system to a set of real-world data, we have demonstrated that it is feasible to implement such a system and derive results that are potentially useful in reducing the incidence of inappropriate physician decision-making.

Ambulatory Care Information Systems↗
PubMed1999

Comparing expert systems for identifying chest x-ray reports that support pneumonia.

We compare the performance of four computerized methods in identifying chest x-ray reports that support acute bacterial pneumonia. Two of the computerized techniques are constructed from expert knowledge, and two learn rules and structure from data. The two machine learning systems perform as well as the expert constructed systems. All of the computerized techniques perform better than a baseline keyword search and a lay person, and perform as well as a physician. We conclude that machine learning can be used to identify chest x-ray reports that support pneumonia.

Algorithms↗