Evidence map›Paper›PMID 39311121›Full record

ArticlePharmacy (Basel, Switzerland)2024

Enhancing Operational Efficiency and Service Delivery through a Robotic Dispensing System: A Case Study from a Retail Pharmacy in Brazil.

Karen Basile, Monserrat Martínez, Julia D Lucaci, Claudia Goldblatt, Idal Beer

Abstract read
In one paragraph

Article in Pharmacy (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Karen BasileMedical Affairs MMS, Becton Dickinson, Sao Paulo 04717, SP, Brazil.ORCID 0000-0003-1949-1789
Monserrat MartínezMedical Affairs MMS, Becton Dickinson, Ciudad de Mexico 11000, Mexico.
Julia D LucaciHealth Economics and Outcomes Research, Becton Dickinson, Franklin Lakes, NJ 07417, USA.ORCID 0009-0004-9002-4600
Claudia GoldblattHealth Economics and Outcomes Research, Becton Dickinson, Franklin Lakes, NJ 07417, USA.ORCID 0000-0001-6075-3088
Idal BeerMedical & Scientific Affairs, Becton Dickinson, San Diego, CA 92121, USA.ORCID 0000-0001-6140-1017

Funding

Becton Dickinson LATAM Not applicable
6 · The paper itself

Abstract

Drug dispensing in retail pharmacies typically involves several manual tasks that often lead to inefficiencies and errors. This is the first published quality improvement study in Latin America, specifically in Brazil, investigating the operational impacts of implementing a robotic dispensing system in a retail pharmacy. Through observational techniques, we measured the time required for the following pharmacy workflows before and after implementing the robotic dispensing system: customer service, receiving stock, stocking inventory, separation, invoicing, and packaging of online orders for delivery. Time savings were observed across all workflows within the pharmacy, notably in receiving stock and online order separation, which experienced 70% and 75% reductions in total time, respectively. Furthermore, customer service, stocking, invoicing, and packaging of online orders, also saw total time reductions from 36% to 53% after implementation of the robotic dispensing system. This study demonstrates an improvement in the pharmacy's operational efficiency post-implementation of the robotic dispensing system. These findings highlight the potential for such automated systems to streamline pharmacy operations, improve staff time efficiency, and enhance service delivery.

Indexed as

automated dispensing systemautomationdispensing robotpharmacy automationpharmacy workflowrobotic dispensing system

Identifiers

PMID39311121
PMCPMC11417772

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.