Computerized Clinical Decision Support During Medication Ordering for Long-term Care Residents with Renal Insufficiency

Meyers Primary Care Institute, Worcester, MA 01605, USA.
Journal of the American Medical Informatics Association (Impact Factor: 3.5). 05/2009; 16(4):480-5. DOI: 10.1197/jamia.M2981
Source: PubMed


Objective: To determine whether a computerized clinical decision support system providing patient-specific recommendations in real-time improves the quality of prescribing for long-term care residents with renal insufficiency.
Design: Randomized trial within the long-stay units of a large long-term care facility. Randomization was within blocks by unit type. Alerts related to medication prescribing for residents with renal insufficiency were displayed to prescribers in the intervention units and hidden but tracked in control units.
Measurement: The proportions of final drug orders that were appropriate were compared between intervention and control units within alert categories: (1) recommended medication doses; (2) recommended administration frequencies; (3) recommendations to avoid the drug; (4) warnings of missing information.
Results: The rates of alerts were nearly equal in the intervention and control units: 2.5 per 1,000 resident days in the intervention units and 2.4 in the control units. The proportions of dose alerts for which the final drug orders were appropriate were similar between the intervention and control units (relative risk 0.95, 95% confidence interval 0.83, 1.1) for the remaining alert categories significantly higher proportions of final drug orders were appropriate in the intervention units: relative risk 2.4 for maximum frequency (1.4, 4.4); 2.6 for drugs that should be avoided (1.4, 5.0); and 1.8 for alerts to acquire missing information (1.1, 3.4). Overall, final drug orders were appropriate significantly more often in the intervention units—relative risk 1.2 (1.0, 1.4).
Conclusions: Clinical decision support for physicians prescribing medications for long-term care residents with renal insufficiency can improve the quality of prescribing decisions.
Trial Registration: Identifier: NCT00599209

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Available from: Monica Lee, Feb 13, 2014
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