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In this paper, we describe our clinical evaluation of the diagnostic accuracy of the renal mass diagnostic system (RMDS) and of seven physicians. To investigate the value of intravenous urography (IVU) and/or retrograde urography (RU) in diagnosing renal parenchymal tumors and tumors of the renal pelvis, RMDS and the seven physicians were tested with and without the information regarding IVU/RU at two different times. From this study we believe that RMDS can help residents in making more accurate presurgical renal mass diagnosis, and may eliminate the need for IVU/RU in the diagnosing process for a specific group of patients.

Few diagnostic decision-support systems are in routine clinical use, mainly because these systems typically require time-consuming manual data entry. This research investigated the feasibility of reducing manual data entry by integrating a stand-alone diagnostic expert system with an existing comprehensive hospital information system (HIS). A knowledge-based intervocabulary mapping technique was developed to map disparate vocabularies. The results of a retrospective study indicate that transferring clinical data from the HIS to the diagnostic expert system at the beginning of workup significantly reduces the manual data entry required for generating the correct diagnoses for patients.

The Computerized Severity Index (CSI) is a commercially available scoring system for hospital inpatients. Trained abstractors review the patient's paper medical record and enter the diagnoses and relevant physiological attributes. The HELP (Health Evaluation through Logical Processing) System at LDS Hospital stores patient data in discrete codes. This paper describes the development of an automatic interface between the standalone, personal-computer-based severity system and the mainframe-based hospital information system. The interface scores patient severity without the need for manual chart review. Severity scores from the automated and manual methods were identical for 70% of 222 general medical patients scored retrospectively. An evaluation of the causes for differing scores between the two methods is presented.

Iliad is a large medical diagnostic system that covers more than 2000 diagnoses and 9000 findings. Due to the size and the complexity of this system, a robust knowledge representation is essential to consistently and efficiently model the medical knowledge involved. In this paper, we describe the knowledge representation currently used in Iliad and a probabilistic representation based on the Bayesian network formalism which can be derived using the information that the Iliad knowledge base contains.

A new client-server based system which is centered around a lifetime data repository (LDR) is under construction. The goal of the new system is to maintain the patient centered decision support aspects of the existing HELP* system while providing an open architecture that supports faster application development and allows execution of applications to be distributed across many computers. These goals are achieved by implementing the system with software components that are commercially available or by adhering to national and international standards for software integration. Keys to successful integration include the use of MS-DOS @, OS/2#, and UNIX Section as operating systems, Microsoft OLE 2.0 as a standard interface to the clinical database, the use of TUXEDO as a transaction/communication manager, and the use of ORACLE [symbol: see text] RDBMS as the underlying database management system.

In this paper we describe the evaluation of a probabilistic diagnostic system for patients with renal mass. Three inference models: Multi-membership Bayesian (MB), Minimal Diagnosis (MD) and Bayesian Network (BN), and 72 patients are used to illustrate three interrelated measures of system performance: accuracy, reliability and discriminating power. The inferencing strategies we tested demonstrated the kind of trade-offs in the performance measures that can be expected from imperfect systems. Ultimately, the purpose and expected use of a system should dictate the relative importance ascribed to different aspects of system performance.

The development and testing of computerized systems to assist in the diagnostic process is a time honored research activity in medical information science. The focus of the majority of the applications produced is on providing accurate diagnostic suggestions when appropriate clinical information is entered. We believe that diagnostic knowledge has a much wider range of uses than that of simply assigning diagnostic labels. Below we describe three applications which illustrate alternate uses for diagnostic systems. Applications that assist in data collection, assess the quality of medical reports, and extract relevant clinical data from natural language x-ray reports are discussed. We believe that more effort should be directed toward studying the use of diagnostic knowledge bases in processes that help plan diagnostic strategies, in quality assurance applications, and in processes that facilitate all aspects of medical communication.

Iliad is a diagnostic expert system for internal medicine. Iliad's "best information" mode is used to determine the most cost-effective findings to pursue next at any stage of a work-up. The "best information" algorithm combines an information content calculation together with a cost factor. The calculations then provide a rank-ordering of the alternative patient findings according to cost-effectiveness. The authors evaluated five information content models under two different strategies. The first, the single-frame strategy, considers findings only within the context of each individual disease frame. The second, the across-frame strategy, considers the information that a single finding could provide across several diseases. The study found that (1) a version of Shannon's information model performed the best under both strategies---this finding confirms the result of a previous independent study, (2) the across-frame strategy was preferred over the single-frame strategy.

Medical informatics could facilitate more effective analysis and use of clinical knowledge by means of expert systems. To be most effective, such systems should be constructed in a manner which is consistent with physicians' cognitive processes. Our past five years' work with a system called Iliad indicates that it provides effective medical training and education. The current research extends our previous work by using a wider array of training and test cases. We also evaluated whether training on specific cases could generalize to improved testing performance on related cases, which featured similar complaints and pathophysiologic mechanisms, but different final diagnoses. In their junior internal medicine clerkship, students (n = 100) completed 1300 Iliad training cases covering 48 diagnoses. The findings indicated improved problem solving on the specifically trained cases as well as the generalization cases. We discuss a possible training model for expert systems such as Iliad.

Information management is central to modern patient care. Computerization of information management has resulted in both departmental systems which serve information needs in locations such as the Radiology Department and in hospital-wide information systems which seek to integrate management of clinical data from many departments. For each of these systems to achieve the goal of maximizing both the effectiveness of health care workers and the quality of patient care, they need to share the data that they capture. Below we discuss a variety of applications, both currently available and in the realm of research protocols, that depend on a high level of communication between Radiology Information Systems and Hospital Information Systems. These examples suggest the benefits of integrating the medically relevant data collected by all of the computer-based information systems in the hospital setting.

The archival database of the HELP Hospital Information System at LDS Hospital is too large to be stored on line. The archival data are important for clinical and research applications. Demountable disk packs have been used to store the archival database. This method of storage has four significant disadvantages. A virtual database was developed to overcome the limitations of this data-management scheme. This virtual database enables the transparent use of appropriate low-cost network-based storage technology to provide on-line availability of the entire archive of clinical data. The virtual database successfully resolves the problems associated with disk packs, and opens the door to enhanced use of the data for clinical and research applications.

Quality assurance techniques provide an opportunity to identify sources of error and to provide the feedback necessary to prevent their repetition. The authors outline an effort to define the steps required for effective quality management procedures in a computerized medical information system (MIS). The computerized management of medical information can be used not only to enhance current quality management activities but also to extend the realm of quality assurance to areas that have heretofore resisted management. Quality-management techniques have the potential for measuring and improving medical decision making processes central to patient care.

The authors examined the proposition that the patient charge for a labor-and-delivery admission can be used as a crude index of pregnancy outcomes. They are developing models of the relationships of certain complications of pregnancy to this outcome variable. These models could be used to estimate potential cost benefits associated with specific prenatal interventions and assist in identifying the areas that should be included in the authors' expert system.

Manual graphing of the progress of labor is considered useful but is not often done. The early detection of some deviations requires special graphics aids. Our objective was to develop an easy-to-use computer program for the integrated visual presentation of information characterizing the progress of labor. Through the use of inexpensive personal computers equipped with graphics monitors, the program provides a combined graphics display of timed progressive cervical dilatation, fetal station, and stimulation of uterine activity (oxytocin infusion). For the early detection of abnormalities, phase-specific normal ranges (reference areas) are displayed. In addition, protraction/arrest as well as precipitate labor disorders are highlighted and computer messages are displayed. The program was evaluated through the assessment of 405 labors entered into a local area network of computers. On average, the program identified 1.5 abnormalities per recorded labor (2.0 for labors resulting in vaginal delivery). The graphic presentation of the labor curve, produced within 3 seconds, displayed 27% more information than the tabular format on the same screen area and provided a single-screen display of the labor curve even for patients with excessive data. The computer-generated display of labor curves facilitates visual presentation and interpretation of labor progress and can also help to translate quality assurance criteria into clinical practice.

NEONATE is a prototype of an expert system for the Newborn Intensive Care Unit developed at the Primary Children's Medical Center in Salt Lake City, Utah. A pilot study was undertaken to see if the addition of radiological frames to the NEONATE software could aid attending Neonatologists to interpret chest X-ray films. A set of radiological frames was created from rules generated by a radiologist. The performance of these radiological frames was compared to the performance of other radiologists using the Kappa statistic to measure agreement. There is a good agreement between the computer's decisions and the radiologists' decisions. The radiological frames were also tested to see if they help physicians who are not trained in radiology. A system that compares the residents' interpretation and the computer's interpretation to a gold standard interpretation was developed. It shows that the computer helps the first and second year residents, but not the third year residents. This article suggests that NEONATE's interpretation of chest X-ray findings are close to the radiologists' interpretations. While NEONATE's radiological frames help novice physicians in reaching better chest X-ray interpretation, the current study suggests that they are not likely to help a Neonatologist.

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.

Iliad is a computerized, expert system for internal medical diagnosis. The system is designed to teach diagnostic skills by means of simulated patient case presentations. We report the results of a controlled trial in which junior students were randomly assigned to received Iliad training on one of two different simulated case mixes. Each group was subsequently tested in both their "trained" and "untrained" case domain. The testing consisted of computerized, simulated patient cases for which no training feedback was provided. Outcome variables were designed to measure the students' performance on these test cases. The results indicate that students made fewer diagnostic errors and more conclusively confirmed their diagnostic hypotheses when they were tested in their trained domain. We conclude that expert systems such as Iliad can effectively teach diagnostic skills by supplementing trainees' actual case experience with computerized simulations.

Iliad is a diagnostic expert system for internal medicine. One important feature that Iliad offers is the ability to analyze a particular patient case and to determine the most cost-effective method for pursuing the work-up. Iliad's current "best information" algorithm has not been previously validated and compared to other potential algorithms. Therefore, this paper presents a comparison of four new algorithms to the current algorithm. The basis for this comparison was eighteen "vignette" cases derived from real patient cases from the University of Utah Medical Center. The results indicated that the current algorithm can be significantly improved. More promising algorithms are suggested for future investigation.

NEONATE is a prototype of an expert application for the HELP Hospital Information System. Its goal is to improve documentation in the Newborn Intensive Care Unit. The decision module of NEONATE is designed to produce an admission problem list. In this paper, the admission problem list that NEONATE generates was compared to the admission problem list of the current CETUS system for 30 patients. These were compared to a retrospectively constructed gold standard problem list. Of 101 problems in the gold standard list, 56 were on the current admission reports; 82 were found by NEONATE. NEONATE found 31 problems missed on the current admission reports; the current admission reports contained 5 problems missed by NEONATE. The current admission reports contained 9 false positives; whereas NEONATE's reports contained 27. Of the 27, 16 were caused by a single rule in NEONATE. We conclude that an expert system has great potential for improving the documentation of the patient problem list.

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 have developed a computer-administered history designed to directly interview hospitalized patients with pulmonary disease. A frame-based decision system is used to direct the history and to generate a one- to five-member differential diagnostic list based on this history. This system incorporates a cognitive model of question selection and a Bayesian scoring algorithm. Structures to control the choice of questions are embedded in the diagnostic frames and in a QUERY program that makes the final choice of questions. We have compared the behavior of this decision-driven approach with a history taken using a paper questionnaire. The paper-based history presents 182 questions to every patient and captured 75% of 85 pulmonary diseases in its differential lists. The decision-driven system asks 50.7 +/- 31.0 (mean +/- standard deviation) and captured 74% of 61 pulmonary diseases. Our experience suggests that the use of a computerized diagnostic knowledge base to direct the selection of pertinent questions can substantially reduce the number of questions necessary to collect a diagnostically useful patient history.

Ten patients with poorly controlled type I diabetes mellitus and a documented complication of their disease were observed during 6 months of conventional diabetic management followed by 6 months of insulin infusion pump treatment and home blood glucose monitoring. Median nerve conduction velocity (NCV) was inversely correlated with the glycosylated hemoglobin (HbA1c) level at entry into the study (r = 0.71; P less than 0.05). The mean HbA1c value at the end of the conventional treatment period was 14.3% and fell to 10.1% by completion of the pump treatment period (P less than 0.0001). The median NCV was significantly greater at the completion of the infusion treatment period than it was at the end of the conventional management portion of the study. However, the rate of increase in NCV during the infusion period was not greater than the rate established during the prior treatment period. In addition, change in HbA1c levels during the pump treatment period did not correlate with change in conduction velocity for any of the nerves studies. These results from a self-controlled study of continuous subcutaneous insulin infusion indicate that improved blood glucose control without normalization of metabolic parameters is not sufficient to reverse the functional deterioration of large, fast-conducting nerve fibers that occurs in type I diabetes.

Ten patients with insulin-dependent diabetes mellitus (IDDM) had fundus photographs and fluorescein angiograms obtained before and after a control period characterized by conventional insulin injections and a test period characterized by continuous subcutaneous insulin infusion (CSII). The mean glycosylated hemoglobin value at the end of the control period was 14.3% +/- 3.8% and decreased to 10.1% +/- 3.3% at the end of the test period. During the control period, none of the patients' eyes changed more than one grade in a modified Early Treatment Diabetic Retinopathy Study classification. All seven eyes without retinopathy at the start of the control period were still without retinopathy at its completion. One eye improved three grades during the test period, but four eyes, including two without retinopathy when CSII was initiated, progressed one grade. The data suggest that metabolic control that is improved but not normalized by CSII neither reverses retinopathy in IDDM nor prevents its development.

An association reported between certain dermatoglyphic features and myocardial infarction (MI) in Japanese males is investigated using a sample of Caucasian males. The frequencies in each of the four Galtonian pattern types (arch, ulnar loop, radial loop, whorl) defined on each of the ten primary digital pattern areas, as well as several synthetic fields for the MI and control groups, are compared. Total and absolute finger ridge count for the same pattern areas in the two samples are similarly studied. No differences in the distributions of these features significant at the 0.01 level or less could be demonstrated between the MI and control samples. A search for combinations of features to correctly classify the individuals into the two groups was similarly inconclusive. Differences in sample size and racial homogeneity that may account for this failure to reproduce the results of the study of Japanese males are discussed. Finally, statistics describing the distributions of the dermatoglyphic features in the test and control samples are presented for comparison with future investigations.

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.

In domains where the types of data which are to be interpreted are relatively constrained (as in the case of specific laboratory test results), our modular data-driven approach can be very productive and well received by the clinical recipient of the data. The computer rarely surpasses the knowledge of an experts result from lack of communication, imperfect memory, oversight or multiple decision-makers caring for the same patient. In such cases, most of the alerts are immediately recognized as valid, so the need for elaborate explanations is not a high priority. On the other hand, a non-specialist is alerted to the need for additional investigation, tests or collaborative support, by the fact that a reminder or diagnosis that s/he had not previously considered, appears. In other words, for the expert, a data-driven system provides unceasing oversight in high-volume low-yielded situations where a small number of mistakes may uncommonly occur for reasons which are not related to the lack of knowledge of the provider. For the non-specialist the system suggests that the patient may have problems in a domain for which the physician needs additional support. In the present state of the art, we do not think that total reliance on the computer-contained knowledge is the ultimate source of this additional support; providing the awareness of the need may be the most important contribution. Once you know that you need help, it is usually obtainable. In a discussion about how computer systems have failed, Friedman and Gustafson made the following observation.(ABSTRACT TRUNCATED AT 250 WORDS)

To investigate the effect of mobile paramedic units on outcome, we prospectively studied for two years all patients with myocardial infarction admitted to the LDS Hospital emergency department who sought aid prior to cardiac arrest. One hundred thirty-four patients who received prehospital care from a mobile paramedic unit were compared with 101 patients who selected another means of initial care. Mortality, occurrence of life-threatening arrhythmias, and change in Killip class at 24 and 48 hours were the outcome variables. Data analysis by multiple logistic regression revealed that outcome was not improved, but a 29-minute median delay in hospital arrival occurred in paramedic-treated patients. Defibrillation was the only beneficial treatment performed by paramedics that could be identified. Current mobile paramedic unit procedures may need to be streamlined to eliminate the delay in hospital arrival resulting from extensive prehospital care.