Literature DB >> 15851383

Reducing excessive medication administration in hospitalized adults with renal dysfunction.

Ira S Nash1, Mary Rojas, Paul Hebert, Stephen R Marrone, Claudia Colgan, Lori A Fisher, Gina Caliendo, Mark R Chassin.   

Abstract

Medication errors are common and harm hospitalized patients. The authors designed and implemented an automated system to complement an existing computerized order entry system by detecting the administration of excessive doses of medication to adult in-patients with renal insufficiency. Its impact, in combination with feedback to prescribers, was evaluated in 3 participating nursing units and compared with the remainder of a tertiary care academic medical center. The baseline rate of excessive dosing was 23.2% of administered medications requiring adjustment for renal insufficiency given to patients with renal impairment on the participating units and 23.6% in the rest of the hospital. The rate fell to 17.3% with nurse feedback and 16.8% with pharmacist feedback in the participating units (P<.05 for each, relative to baseline). The rates of excessive dosing for the same time periods were 26.1% and 24.8% in the rest of the hospital. Automated detection and routine feedback can reduce the rate of excessive administration of medication in hospitalized adults with renal insufficiency.

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Year:  2005        PMID: 15851383     DOI: 10.1177/1062860604273752

Source DB:  PubMed          Journal:  Am J Med Qual        ISSN: 1062-8606            Impact factor:   1.852


  11 in total

1.  Computerized clinical decision support during medication ordering for long-term care residents with renal insufficiency.

Authors:  Terry S Field; Paula Rochon; Monica Lee; Linda Gavendo; Joann L Baril; Jerry H Gurwitz
Journal:  J Am Med Inform Assoc       Date:  2009-04-23       Impact factor: 4.497

Review 2.  Utility of Electronic Medical Record Alerts to Prevent Drug Nephrotoxicity.

Authors:  Melissa Martin; F Perry Wilson
Journal:  Clin J Am Soc Nephrol       Date:  2018-04-05       Impact factor: 8.237

Review 3.  Computerized decision support systems: improving patient safety in nephrology.

Authors:  Jamison Chang; Claudio Ronco; Mitchell H Rosner
Journal:  Nat Rev Nephrol       Date:  2011-04-19       Impact factor: 28.314

4.  Recommendations for a clinical decision support for the management of individuals with chronic kidney disease.

Authors:  Meenal B Patwardhan; Kensaku Kawamoto; David Lobach; Uptal D Patel; David B Matchar
Journal:  Clin J Am Soc Nephrol       Date:  2009-01-28       Impact factor: 8.237

5.  Medication dosing and renal insufficiency in a pediatric cardiac intensive care unit: impact of pharmacist consultation.

Authors:  Brady S Moffett; Antonio R Mott; David P Nelson; Karen D Gurwitch
Journal:  Pediatr Cardiol       Date:  2007-12-14       Impact factor: 1.655

6.  Designing and evaluating an automated system for real-time medication administration error detection in a neonatal intensive care unit.

Authors:  Yizhao Ni; Todd Lingren; Eric S Hall; Matthew Leonard; Kristin Melton; Eric S Kirkendall
Journal:  J Am Med Inform Assoc       Date:  2018-05-01       Impact factor: 4.497

Review 7.  Scoping review exploring the impact of digital systems on processes and outcomes in the care management of acute kidney injury and progress towards establishing learning healthcare systems.

Authors:  Clair Ka Tze Chew; Helen Hogan; Yogini Jani
Journal:  BMJ Health Care Inform       Date:  2021-07

8.  Optimising drug prescribing and dispensing in subjects at risk for drug errors due to renal impairment: improving drug safety in primary healthcare by low eGFR alerts.

Authors:  Hanneke Joosten; Iefke Drion; Kees J Boogerd; Emiel V van der Pijl; Robbert J Slingerland; Joris P J Slaets; Tiele J Jansen; Olof Schwantje; Reinold O B Gans; Henk J G Bilo
Journal:  BMJ Open       Date:  2013-01-24       Impact factor: 2.692

Review 9.  Systematic review of clinical decision support interventions with potential for inpatient cost reduction.

Authors:  Christopher L Fillmore; Bruce E Bray; Kensaku Kawamoto
Journal:  BMC Med Inform Decis Mak       Date:  2013-12-17       Impact factor: 2.796

10.  Using the diffusion of innovations theory to assess socio-technical factors in planning the implementation of an electronic health record alert across multiple primary care clinics.

Authors:  Ching-Pin Lin; Janelle Guirguis-Blake; Gina A Keppel; Sharon Dobie; Justin Osborn; Allison M Cole; Laura-Mae Baldwin
Journal:  J Innov Health Inform       Date:  2016-04-15
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