@article{12599, author = {Terry Field and Paula Rochon and Monica Lee and Linda Gavendo and Joann L. Baril and Jerry H. Gurwitz}, title = {Computerized clinical decision support during medication ordering for long-term care residents with renal insufficiency.}, abstract = {

UNLABELLED: 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: http://clinicaltrials.gov Identifier: NCT00599209.

}, year = {2009}, journal = {J Am Med Inform Assoc}, volume = {16}, pages = {480-5}, month = {12/2009}, issn = {1067-5027}, doi = {10.1197/jamia.M2981}, language = {eng}, }