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dc.contributor.authorField, Terry S.
dc.contributor.authorRochon, Paula A.
dc.contributor.authorLee, Monica
dc.contributor.authorGavendo, Linda
dc.contributor.authorBaril, Joann L.
dc.contributor.authorGurwitz, Jerry H.
dc.date2022-08-11T08:09:21.000
dc.date.accessioned2022-08-23T16:27:38Z
dc.date.available2022-08-23T16:27:38Z
dc.date.issued2009-07-01
dc.date.submitted2009-07-08
dc.identifier.citationJ Am Med Inform Assoc. 2009 Jul-Aug;16(4):480-5. Epub 2009 Apr 23. <a href="http://dx.doi.org/10.1197/jamia.M2981">Link to article on publisher's website</a>
dc.identifier.issn1067-5027
dc.identifier.doi10.1197/jamia.M2981
dc.identifier.pmid19390107
dc.identifier.pmid19390107
dc.identifier.urihttp://hdl.handle.net/20.500.14038/36833
dc.description.abstractOBJECTIVE: 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.
dc.language.isoen_US
dc.publisherHanley & Belfus
dc.relation<a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=19390107&dopt=Abstract">Link to article in PubMed</a>
dc.relation.urlhttp://dx.doi.org/10.1197/jamia.M2981
dc.subjectLong-Term Care
dc.subjectDecision Support Systems, Clinical
dc.subjectMedication Systems
dc.subjectRenal Insufficiency
dc.subjectRandomized Controlled Trial
dc.subjectHealth Services Research
dc.subjectMedicine and Health Sciences
dc.titleComputerized Clinical Decision Support During Medication Ordering for Long-term Care Residents with Renal Insufficiency.
dc.typeJournal Article
dc.source.journaltitleJournal of the American Medical Informatics Association : JAMIA
dc.source.volume16
dc.source.issue4
dc.identifier.legacycoverpagehttps://escholarship.umassmed.edu/meyers_pp/2
dc.identifier.contextkey891729
html.description.abstract<p>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.</p> <p>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.</p> <p>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).</p> <p>CONCLUSIONS: Clinical decision support for physicians prescribing medications for long-term care residents with renal insufficiency can improve the quality of prescribing decisions.</p>
dc.identifier.submissionpathmeyers_pp/2
dc.contributor.departmentDepartment of Medicine, Division of Geriatric Medicine
dc.contributor.departmentMeyers Primary Care Institute


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