2005-2006 Grant Awards
James S. Todd Memorial Research Award
Automated Maintenance of Problem-Drug Matches in the Electronic Medical Record to Promote Patient Safety
Chiang S. Jao, PhD, University of Illinois College of Medicine
The advent of electronic medical records (EMRs) with computerized physician order entry (CPOE) makes real time clinical decision support systems (CDSSs) feasible. We had tested the hypothesis that a CDSS that automates the matching of ordered drugs to problems on the problem list can enhance the maintenance of both the drug list and the problem list. Enhanced maintenance of both the drug and problem lists can permit the exploitation of advanced decision support strategies that will yield higher patient safety. We designed a standalone decision support tool whose rules are automatically fired to match drugs ordered to problems on the problem list. We tested this tool on 100 preliminary cases and then assessed the performance of this decision support tool on 140 additional cases. The rules developed in this research have been successfully transplanted into an embedded decision support system plugged into the EMR-CPOE system of the University of Illinois Hospital.
The support from NPSF assisted the fulfillment of a practical decision support tool in the maintenance of medication-problem reconciliation with the EMR system. I am currently visiting the National Library of Medicine to extend the work related to this research project. My current focus is to build a useful reference table that associates medications and their indications. This reference table will be represented by unique conceptual
codes from standard terminology systems
Post-Surgical Patients Receiving Patient Controlled Analgesia (PCA)
Frank J. Overdyk, MD, Medical University of South Carolina
This study investigates the incidence and etiology of respiratory compromise in post-surgical patients receiving patient-controlled analgesia (PCA). It seeks to quantify and stratify the risks of this therapy, and develop prognostic algorithms that may be incorporated into PCA pump alarm systems. Respiratory compromise during PCA may be transient or progress to respiratory arrest unless diagnosed and treated in a timely manner. This study will use a new technology, PCA pumps with integrated, telemetric, oximetry and capnometry modtiles, to continuously measure respiratory parameters of post-surgical patients. The only clinical site worldwide that has this equipment currently implemented is the venue for this study. Although well described in the operating room and procedural suites, this monitoring combination has never been applied to patients receiving PCA. The respiratory data collected, synchronized with postoperative clinical events, will allow the incidence of respiratory compromise to be measured and characterize the respiratory and heart rate patterns that precede these events. Analysis of pilot study data suggests that heuristic pattern recognition algorithms may be developed that will predict impending respiratory compromise and aid in the determination of its causes. A multidisciplinary research team with expertise in pain management, pharmacology, statistics, respiratory therapy, medical informatics, biomedical engineering and anesthesiology has been assembled to accomplish the objectives of the study. This study will quantify the risk and improve the safety of PCA, and provide new insights into the respiratory athophysiology associated with acute post-surgical pain and its treatment.
