rss
J Am Med Inform Assoc 16:480-485 doi:10.1197/M2981
  • Original Investigation
  • Research Paper

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

  1. Terry S Field, DScaffa,affb,affc,affd,
  2. Paula Rochon, MD, MPHaffe,
  3. Monica Lee, RPhaffe,
  4. Linda Gavendo, RPhaffe,
  5. Joann L Baril, BSaffa,affb,affc,affd,
  6. Jerry H Gurwitz, MDaffa,affb,affc,affd
  1. aMeyers Primary Care Institute, Worcester, MA
  2. bFallon Clinic, Worcester, MA
  3. cFallon Community Health Plan, Worcester, MA
  4. dUniversity of Massachusetts Medical School, Worcester, MA
  5. eKunin-Lunenfeld Applied Research Unit, Baycrest Centre for Geriatric Care, Toronto, Ontario, Canada
  1. Correspondence: Terry S. Field, DSc, Meyers Primary Care Institute, 630 Plantation Street, Worcester, MA 01605; e-mail: <terry.field{at}umassmed.edu>
  • Received 26 August 2008
  • Accepted 23 March 2009

Abstract

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

Footnotes

  • Supported by grants from the Agency for Healthcare Research and Quality (HS010481 and HS15430).

Free Sample

This recent issue is free to all users to allow everyone the opportunity to see the full scope and typical content of JAMIA.
View free sample issue >>

Access policy for JAMIA

All content published in JAMIA is deposited with PubMed Central by the publisher with a 12 month embargo. Authors/funders may pay an Open Access fee of $2,000 to make the article free on the JAMIA website and PMC immediately on publication.

All content older than 12 months is freely available on this website.

AMIA members can log in with their JAMIA user name (email address) and password or via the AMIA website.

Navigate This Article