Literature DB >> 24421497

Preventing large-scale controlled substance diversion from within the pharmacy.

Emory S Martin1, Steven H Dzierba2, David M Jones3.   

Abstract

Large-scale diversion of controlled substances (CS) from within a hospital or heath system pharmacy is a rare but growing problem. It is the responsibility of pharmacy leadership to scrutinize control processes to expose weaknesses. This article reviews examples of large-scale diversion incidents and diversion techniques and provides practical strategies to stimulate enhanced CS security within the pharmacy staff. Large-scale diversion from within a pharmacy department can be averted by a pharmacist-in-charge who is informed and proactive in taking effective countermeasures.

Keywords:  controlled substances; diversion; narcotics; pharmacy management

Year:  2013        PMID: 24421497      PMCID: PMC3839459          DOI: 10.1310/hpj4805-406

Source DB:  PubMed          Journal:  Hosp Pharm        ISSN: 0018-5787


  3 in total

1.  Employee pilferage in the pharmacy: preventive measures.

Authors:  E N Okolo
Journal:  Top Hosp Pharm Manage       Date:  1989-08

2.  Ideas for action: hospital pharmacy security.

Authors:  D Tribble
Journal:  Top Hosp Pharm Manage       Date:  1984-08

3.  Special report. Drug theft from hospital pharmacies: lessons from the 'Syracuse scam'.

Authors: 
Journal:  Hosp Secur Saf Manage       Date:  1996-10
  3 in total
  3 in total

1.  Controlled substance diversion in health systems: A failure modes and effects analysis for prevention.

Authors:  Karen Nolan; Andrew R Zullo; Elliott Bosco; Christine Marchese; Christine Berard-Collins
Journal:  Am J Health Syst Pharm       Date:  2019-07-18       Impact factor: 2.637

2.  Clinical observations and a ealthcare ailure ode and ffect nalysis to identify vulnerabilities in the security and accounting of medications in Ontario hospitals: a study protocol.

Authors:  Maaike de Vries; Mark Fan; Dorothy Tscheng; Michael Hamilton; Patricia Trbovich
Journal:  BMJ Open       Date:  2019-06-29       Impact factor: 2.692

3.  Detecting drug diversion in health-system data using machine learning and advanced analytics.

Authors:  Tom Knight; Bernie May; Don Tyson; Scott McAuley; Pam Letzkus; Sharon Murphy Enright
Journal:  Am J Health Syst Pharm       Date:  2022-08-05       Impact factor: 2.980

  3 in total

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