Cited by 40Pharmacy and Medical PracticesSupply Chain and Inventory ManagementHealthcare Operations and Scheduling Optimization

Implementation and optimization of automated dispensing cabinet technology

McCarthy, Bryan C., Ferker, Michael·2016·American Journal of Health-System Pharmacy

Abstract

PURPOSE: A multifaceted automated dispensing cabinet (ADC) optimization initiative at a large hospital is described. SUMMARY: The ADC optimization project, which was launched approximately six weeks after activation of ADCs in 30 patient care unit medication rooms of a newly established adult hospital, included (1) adjustment of par inventory levels (desired on-hand quantities of medications) and par reorder quantities to reduce the risk of ADC supply exhaustion and improve restocking efficiency, (2) expansion of ADC "common stock" (medications assigned to ADC inventories) to increase medication availability at the point of care, and (3) removal of some infrequently prescribed medications from ADCs to reduce the likelihood of product expiration. The purpose of the project was to address organizational concerns regarding widespread ADC medication stockouts, growing reliance on cart-fill medication delivery systems, and suboptimal medication order turnaround times. Leveraging of the ADC technology platform's reporting functionalities for enhanced inventory control yielded a number of benefits, including cost savings resulting from reduced pharmacy technician labor requirements (estimated at $2,728 annually), a substantial reduction in the overall weekly stockout percentage (from 3.2% before optimization to 0.5% eight months after optimization), an improvement in the average medication turnaround time, and estimated cost avoidance of $19,660 attributed to the reduced potential for product expiration. CONCLUSION: Efforts to optimize ADCs through par level optimization, expansion of common stock, and removal of infrequently used medications reduced pharmacy technician labor, decreased stockout percentages, generated opportunities for cost avoidance, and improved medication turnaround times.

Integrity signals

Registry

Crossref · 10.2146/ajhp150531

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Cited by

Sorted by citations

Authors
McCarthy, B. C., & Ferker, M.
Affiliations
  • University of Chicago (US)
  • Northwestern Memorial Hospital (US)
Corresponding author
McCarthy, Bryan C.
Venue
American Journal of Health-System Pharmacy
Published
2016-10-01
Volume
73
Issue
19
Pages
1531-1536
ISSN
  • 1079-2082 (ISSN-L)
  • 1535-2900
OpenAlex
W2523492928
Cited by
40
References
0
Citations by year
2026: 4 · 2025: 4 · 2024: 5 · 2023: 8 · 2022: 4 · 2021: 6 · 2020: 4 · 2019: 4 · 2018: 1
FWCI
2.11
Type
journal article
Language
en
Open access
closed
Locations
  • American Journal of Health-System Pharmacy (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacy and Medical Practices
  • Social Sciences › Business, Management and Accounting › Management Information Systems › Supply Chain and Inventory Management
  • Health Sciences › Health Professions › Emergency Medical Services › Healthcare Operations and Scheduling Optimization
Keywords
automated dispensing cabinets, hospital pharmacy, drug inventory management, medication stockouts, common stock, drug expiration
MeSH terms
Pharmaceutical Preparations, Humans, Medication Errors, Medication Systems, Hospital, Pharmacy Service, Hospital, Technology, Pharmaceutical, Point-of-Care Systems

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review