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In a radiology department, clinical audit implies multiple readings of selected images to identify those findings that should be recognized and to document any departure from this standard for each radiologist. The authors developed an alternate approach for an audit on the basis of clinical outcomes collected in a medical computing facility. Techniques borrowed from information theory were used to measure the clinical information contributed by radiologists as they interpreted chest radiographs. The reported findings were evaluated in light of the discharge diagnosis. The scores generated quantified the information contributed to the final diagnosis by the radiologist's description. This audit approach was tested in a group of 100 chest radiographs. Significant differences were found in the mean scores for information contributed by five different readers. These differences were similar to differences demonstrated in audits by means of multiple readings of chest radiographs. These results support use of a form of audit that is substantially less expensive and time consuming than that typically used in radiology departments.

A computerized data acquisition tool, the special purpose radiology understanding system (SPRUS), has been implemented as a module in the Health Evaluation through Logical Processing Hospital Information System. This tool uses semantic information from a diagnostic expert system to parse free-text radiology reports and to extract and encode both the findings and the radiologists' interpretations. These coded findings and interpretations are then stored in a clinical data base. The system recognizes both radiologic findings and diagnostic interpretations. Initial tests showed a true-positive rate of 87% for radiographic findings and a bad data rate of 5%. Diagnostic interpretations are recognized at a rate of 95% with a bad data rate of 6%. Testing suggests that these rates can be improved through enhancements to the system's thesaurus and the computerized medical knowledge that drives it. This system holds promise as a tool to obtain coded radiologic data for research, medical audit, and patient care.

We designed an automated system for managing large-scale screening and diagnostic mammography. The system collects coded mammographic findings from the radiologist and records a history directly from the patient. This information is stored in an integrated clinical data base to which the results of subsequent examinations or surgery are added. In addition, the system generates letters to the patient and her physician that describe mammographic findings and letters reminding them of routine screening visits. For patients who have positive results on examinations, it checks for records of biopsy or repeat mammography and generates follow-up letters if appropriate intervention is not found. While this system is part of a comprehensive computerized hospital information system, mammography management tools with most of the features described can be designed for relatively inexpensive microcomputers.