Article

Overcoming limitations of data entry for the semi-automated detection of drug orphans in the EMR.

Department of Neurology and Rehabilitation, University of Illinois at Chicago, Chicago, IL, USA.
AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium 02/2006; pp.967
Source: PubMed

ABSTRACT Sophisticated decision support systems (DSS) can reduce preventable medical errors. A standalone DSS prototype was built to identify drug-disease mismatches in the electronic medical record (EMR). When drugs fail to match a known problem on the problem list (drug orphans), either the problem list is deficient or the drug was ordered in error. We tested the performance of an integrated DSS prototype by improving the data exchange with the standalone DSS prototype. By implementing a screen capture tool, we were able to accelerate data entry into the DSS prototype through the semi-automated operation. Preliminary results revealed a marked increase in the rate of data entry during testing the DSS prototype.The accelerated data entry streamlines workflow and promotes physician's acceptance of the DSS.

0 0
 · 
0 Bookmarks
 · 
29 Views
  • Source
    Article: Computerized physician order entry of medications and clinical decision support can improve problem list documentation compliance.
    William L Galanter, Daniel B Hier, Chiang Jao, David Sarne
    [show abstract] [hide abstract]
    ABSTRACT: The problem list is a key and required element of the electronic medical record (EMR). Problem lists may contribute substantially to patient safety and quality of care. Physician documentation of the problem list is often lower than desired. Methods are needed to improve accuracy and completeness of the problem list. An automated clinical decision support (CDS) intervention was designed utilizing a commercially available EMR with computerized physician order entry (CPOE) and CDS. The system was based on alerts delivered during inpatient medication CPOE that prompted clinicians to add a diagnosis to the problem list. Each alert was studied for a 2-month period after implementation. Measures included alert validity, alert yield, and accuracy of problem list additions. At a 450 bed teaching hospital, the number of medication orders which triggered alerts during all 2-month study periods was 1011. For all the alerts, the likelihood of a valid alert (an alert that occurred in patients with one of the predefined diagnoses) was 96+/-1%. The alert yield, defined as occuring when an alert led to addition of a problem to the problem list, was 76+/-2%. Accurate problem list additions, defined as additions of problems when the problem was determined to be present by expert review, was 95+/-1%. The CDS problem list mechanism was integrated into the process of medication order placement and promoted relatively accurate addition of problems to the EMR problem list.
    International Journal of Medical Informatics 08/2008; 79(5):332-8. · 2.41 Impact Factor
Data provided are for informational purposes only. Although carefully collected, accuracy cannot be guaranteed. The impact factor represents a rough estimation of the journal's impact factor and does not reflect the actual current impact factor. Publisher conditions are provided by RoMEO. Differing provisions from the publisher's actual policy or licence agreement may be applicable.

Keywords

data exchange
 
drug-disease mismatches
 
DSS
 
DSS prototype
 
DSS prototype.The
 
electronic medical record
 
EMR
 
integrated DSS prototype
 
known problem
 
marked increase
 
Preliminary results
 
preventable medical errors
 
problem list
 
promotes physician's acceptance
 
semi-automated operation
 
Sophisticated decision support systems
 
standalone DSS prototype