AI systems in clinical practice

Laboratory systems
DoseChecker
Expert system that screens prescriptions for correct medication dosages - monitors potentially toxic drugs orders which must be carefully dosed.

developed by clinical domains keywords
Barnes-Jewish Hospital Pharmacy Department and Medical Informatics researchers, Washington University, St. Louis Renal, liver, therapy, monitoring drug orders Expert systems, knowledge-based systems
location commissioned status
Washington University Medical Center; Barnes-Jewish Hospital, St. Louis Children's Hospital and other BJC Healthcare hospitals, St. Louis, Missouri Barnes-Jewish Hospital in September 1994; Christian Hospital, St. Louis in spring 2000; Missouri Baptist Medical Center in November 2001. In routine use
description
DoseChecker is an expert system that automatically evaluates prescriptions for a defined set of drugs for dosing inaccuracy and the possible need for a dosage adjustment, based on patient-specific information.

DoseChecker assists staff pharmacists at Barnes and Jewish Hospitals in St. Louis (teaching hospitals affiliated with Washington University) in monitoring drug orders for a set of drugs which must be carefully dosed for patients with possible renal impairment.

Certain types of drugs require careful quantitative dosing, particularly in patients with renal impairment. In these patients, drug concentrations can build to toxic levels. Drug dosing decisions should focus, then, on maintaining concentrations which maximize therapeutic effects while controlling the risk of toxicity.

Renal function varies over time and can be estimated as a function of calculated creatinine clearance. DoseChecker monitors patients with active orders for drugs known to require careful dosing. Using parameters such as patient weight and serum creatinine, DoseChecker calculates creatinine clearance and applies a set of dosing guidelines developed by pharmacokinetic experts to determine if the dosing is appropriate. If it does not fall within established guidelines, an alert is generated for a pharmacist, who then consults the patient's attending physician to determine whether the dosage should be adjusted.

DoseChecker is made up of a set of dosing guidelines developed by local experts, a relational database containing patient demographic information and clinical data such as serum creatinine measurements and drug orders. Suspected dosing violations are stored so that trends can be detected.

Technologies employed: CLIPS (expert system tool from NASA), Sybase ISQL scripts, Bourne shell scripts.

DoseChecker and PharmADE (another system developed by clinical and medical informatics groups in St. Louis), received a National Hospital Pharmacy Quality Award, presented by Abbott Laboratories in 1998, and were recognized by the Smithsonian Institution in 1999.

references

Miller JE, Reichley RM, McNamee LA, Steib SA, Bailey TC. Notification of real-time clinical alerts generated by pharmacy expert systems. Proc AMIA Symp. 1999;:325-9.

[PubMed]   [AMIA]

" 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. "

McMullin ST, Reichley RM, Kahn MG, Dunagan WC, Bailey TC. Automated system for identifying potential dosage problems at a large university hospital. Am J Health Syst Pharm. 1997 Mar 1;54(5):545-9.

[PubMed]   []
" A hospital's experience with an automated system for screening drug orders for potential dosage problems is described. DoseChecker was developed by the hospital pharmacy department in collaboration with a local university. Pharmacy, laboratory, and patient demographic data are transferred nightly from the hospital's mainframe system to a database server; DoseChecker uses these data and user-defined rules to (1) identify patients receiving any of 35 targeted medications, (2) evaluate the appropriateness of current dosages, and (3) generate alerts for patients potentially needing dosage adjustments. The alert reports are distributed to satellite pharmacists, who evaluate each patient's condition and make recommendations to physicians as needed. One of the system's primary purposes is to calculate creatinine clearance and verify that dosages are properly adjusted for renal function. Between May and October 1995, the system electronically screened 28,528 drug orders and detected potential dosage problems in 2859 (10%). The system recommended a lower daily dose in 1992 cases (70%) and a higher daily dose in 867 (30%). Pharmacists contacted physicians concerning 1163 (41%) of the 2859 alerts; in 868 cases (75%), the physicians agreed to adjust the dosage. The most common dosage problem identified was failure to adjust dosages on the basis of declining renal function. An automated system provided an efficient method of identifying inappropriate dosages at a large university hospital. "

contact links
Washington University School of Medicine
Department of Internal Medicine
Division of Medical Informatics
660 South Euclid Campus
Box 8005 St. Louis
Missouri 63110 USA.

 bullet  Medical Informatics at Washington University in St. Louis  bullet  Barnes and Jewish Hospitals, St. Louis  bullet  BJC Healthcare  bullet  St. Louis Children's Hospital - BJC HealthCare Quality Initiatives
acknowledgements

Archive of AI systems in clinical practice previously administered by Enrico Coiera. Used with permission. Maintained and extended since 2001 by OpenClinical.

Entry on archive: October 27 1995
Last main update: July 19 2004
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