Biomedical subjects

S A Steib

Publications and source records attributed to S A Steib.

8 recordsLinked to original sources

PubMed1999

Impact of a Web-based clinical information system on cisapride drug interactions and patient safety.

BACKGROUND: Most commercially available drug-interaction screening systems have important limitations that fail to protect patients from dangerous drug combinations. We attempted to overcome the limitations of our commercial program by developing a Web-based clinical information system to serve as a safety net. This system identifies drug interactions with newly marketed medications not screened by our commercial program, and generates a second alert on dangerous interactions that were overridden during order processing. METHODS: The Web-based system uses patient-specific pharmacy, laboratory, and demographic data to generate detailed alerts on patients receiving potentially dangerous drug combinations. The system's impact on the use of dangerous drug combinations and related adverse events was evaluated by a retrospective analysis of patients receiving cisapride with contraindicated medications in the 2 years before and after implementation. RESULTS: The rate of dangerous drug combinations declined by 66% after implementing the system, from 9.0% of cisapride orders in 1994 and 1995 to 3.1% in 1996 and 1997 (P<.001). The mean [SD] duration of contraindicated therapy (4.1 [3.8] vs 1.6 [1.4] days, P<.001) and proportion of patients being discharged under treatment with a dangerous drug combination (36.2% vs 7.7%, P<.001) was also significantly reduced during the study period. Three patients (1.7%) during the control period experienced serious adverse events that may have been related to the targeted drug interactions. No symptomatic cardiac events were identified during the study period (P = .21). CONCLUSIONS: An automated system running as a safety net can be an efficient method of detecting contraindicated drug combinations and serves an important role in the avoidance of potentially serious adverse drug events.

Adverse Drug Reaction Reporting Systems↗

PubMed1999

Notification of real-time clinical alerts generated by pharmacy expert systems.

We developed and implemented a strategy for notifying clinical pharmacists of alerts generated in real-time by two pharmacy expert systems: one for drug dosing and the other for adverse drug event prevention. Display pagers were selected as the preferred notification method and a concise, yet readable, format for displaying alert data was developed. This combination of real-time alert generation and notification via display pagers was shown to be efficient and effective in a 30-day trial.

Clinical Pharmacy Information Systems↗

PubMed1995

Supporting ad-hoc queries in an integrated clinical database.

Whether caring for patients or conducting research, medical decision-makers need access to clinical data. To fulfill that need, commercial software developers have produced a wide range of database query tools that differ greatly in functionality and cost. Generally, tools that have a greater ability to conceal database complexity from the user also require more effort for administrative setup. We describe a cost-effective, commercially-available query tool that requires no special setup to perform most simple queries, yet can be customized to satisfy users' more complex querying requirements.

Clinical Pharmacy Information Systems↗

PubMed1995

Improvement in user performance following development and routine use of an expert system.

Hospital-acquired (nosocomial) infections represent a significant cause of prolonged inpatient days and additional hospital charges. In many hospitals, infection control nurses manually review positive microbiology culture results to monitor the incidence and prevalence of potential nosocomial infections. We have developed an expert system called GermWatcherTM, which uses the United States Centers for Disease Control and Prevention National Nosocomial Infection Surveillance criteria to classify microbiology results as potential nosocomial infections. In February 1993, we deployed GermWatcher at a large tertiary-care teaching hospital. In July 1993, we implemented a revised version of GermWatcher. With each version, we performed an evaluation of the program by comparing its electronic classification of positive culture results to the paper-based manual classification performed by three infection control nurses and one Infectious Disease specialist (gold standard). In the present study, we focus not on changes in the performance of the expert system, but on changes in performance among the infection control nurses. We found significant improvement in agreement and accuracy in the manual classification of cultures by the infection control nurses in the second evaluation compared to the first evaluation. We attribute this improved manual performance to the development of the expert system's rule base throughout the two evaluation phases and to the use of the expert system in the nurses' daily activities.

Cross Infection↗

PubMed1993

An expert system for culture-based infection control surveillance.

Hospital-acquired infections represent a significant cause of prolonged inpatient days and additional hospital charges. We describe an expert system, called GERMWATCHER, which applies the Centers for Disease Control's National Nosocomial Infection Surveillance culture-based criteria for detecting nosocomial infections. GERMWATCHER has been deployed at Barnes Hospital, a large tertiary-care teaching hospital, since February 1993. We describe the Barnes Hospital infection control environment, the expert system design, and a predeployment performance evaluation. We then compare our system to other efforts in computer-based infection control.

Cells, Cultured↗

PubMed1993

Unifying heterogeneous distributed clinical data in a relational database.

Access to clinical data which are distributed among multiple satellite information systems is crucial to delivering better care and reducing costs in many hospitals and medical centers. An integrated view of these data is needed to reduce the effort of users requiring data from multiple systems. We have addressed the issue of distributed data integration while developing both production and research decision-support applications. We describe an ideal integration solution, obstacles to realizing this solution, and our integration requirements and architecture. Our focus is a description of our specific schema and data integration techniques. We conclude with an analysis of our approach.

Computer Communication Networks↗

PubMedDate not supplied

Monitoring expert system performance using continuous user feedback.

OBJECTIVE: To evaluate the applicability of metrics collected during routine use to monitor the performance of a deployed expert system. METHODS: Two extensive formal evaluations of the GermWatcher (Washington University School of Medicine) expert system were performed approximately six months apart. Deficiencies noted during the first evaluation were corrected via a series of interim changes to the expert system rules, even though the expert system was in routine use. As part of their daily work routine, infection control nurses reviewed expert system output and changed the output results with which they disagreed. The rate of nurse disagreement with expert system output was used as an indirect or surrogate metric of expert system performance between formal evaluations. The results of the second evaluation were used to validate the disagreement rate as an indirect performance measure. Based on continued monitoring of user feedback, expert system changes incorporated after the second formal evaluation have resulted in additional improvements in performance. RESULTS: The rate of nurse disagreement with GermWatcher output decreased consistently after each change to the program. The second formal evaluation confirmed a marked improvement in the program's performance, justifying the use of the nurses' disagreement rate as an indirect performance metric. CONCLUSIONS: Metrics collected during the routine use of the GermWatcher expert system can be used to monitor the performance of the expert system. The impact of improvements to the program can be followed using continuous user feedback without requiring extensive formal evaluations after each modification. When possible, the design of an expert system should incorporate measures of system performance that can be collected and monitored during the routine use of the system.

Expert Systems↗

PubMedDate not supplied

Statistical process control methods for expert system performance monitoring.

The literature on the performance evaluation of medical expert system is extensive, yet most of the techniques used in the early stages of system development are inappropriate for deployed expert systems. Because extensive clinical and informatics expertise and resources are required to perform evaluations, efficient yet effective methods of monitoring performance during the long-term maintenance phase of the expert system life cycle must be devised. Statistical process control techniques provide a well-established methodology that can be used to define policies and procedures for continuous, concurrent performance evaluation. Although the field of statistical process control has been developed for monitoring industrial processes, its tools, techniques, and theory are easily transferred to the evaluation of expert systems. Statistical process tools provide convenient visual methods and heuristic guidelines for detecting meaningful changes in expert system performance. The underlying statistical theory provides estimates of the detection capabilities of alternative evaluation strategies. This paper describes a set of statistical process control tools that can be used to monitor the performance of a number of deployed medical expert systems. It describes how p-charts are used in practice to monitor the GermWatcher expert system. The case volume and error rate of GermWatcher are then used to demonstrate how different inspection strategies would perform.

Evaluation Studies as Topic↗