Evidence map›Paper›PMID 40127952›Full record

ArticleBMJ open quality2025

Optimising pharmacy processes in medication delivery service through digitalisation and automation.

Kian Hong Hong Ng, Wen Jun Tiew, Yook Ting Amanda Woo, Wei Xiong Nathaniel Lim, Tou Teik George Lim, Arleen Susan Baskaran

Abstract read
In one paragraph

Article in BMJ open quality, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Review
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

6 authors.

Kian Hong Hong NgPharmacy, Changi General Hospital, Singapore ngkianhong1991@gmail.com.ORCID http://orcid.org/0009-0008-3102-2954
Wen Jun TiewPharmacy, Changi General Hospital, Singapore.
Yook Ting Amanda WooPharmacy, Changi General Hospital, Singapore.
Wei Xiong Nathaniel LimPharmacy, Changi General Hospital, Singapore.
Tou Teik George LimPharmacy, Changi General Hospital, Singapore.
Arleen Susan BaskaranPharmacy, Changi General Hospital, Singapore.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid expansion of medication delivery service (MDS) during COVID-19 created many new roles in the pharmacy which are manpower intensive and not sustainable as pharmacy resumes counter collection services. To keep MDS operations sustainable, we identified the need to streamline and automate processes which are manual and repetitive. We seek to determine if the Plan, Do, Study, Act (PDSA) cycles would effectively reduce the man-hours required for the MDS over two phases in 1 year. Phase 1 involved digitalisation of order taking and automation of the data entry process. Phase 2 involved automating the order generation and accounting process to replicate the patient information matching task which was performed manually during bagging and dispatch of delivery orders. The baseline period for this study was from December 2020 to January 2021. The results following implementation of PDSA cycles in the respective phases were collected between January 2021 to June 2021 and July 2021 to December 2021. The average time taken for data entry per delivery order reduced from a range of 0.5 to 2.15 min to 0.08 to 0.1 min depending on the ordering method (p<0.05). The average time taken for bagging and dispatch per delivery order shortened from 2.7 min to 0.28 min (p<0.05). The improvements were sustained and cumulatively contributed to 11.8-man-hour savings. The impact of the interventions was discussed. As MDS gains prominence as an important alternative for medication collection due to its rapid expansion due to COVID-19, it is crucial for the pharmacy to expand its capacity and information technology capabilities to cope with higher workload from both MDS and walk-in patients.

Indexed as

AutomationPharmacy Service, HospitalCOVID-19HumansMedication Systems, HospitalSARS-CoV-2Healthcare quality improvementInformation technologyPDSAQuality improvementTelemedicine

Identifiers

PMID40127952
PMCPMC11934400

What OpenQuestion holds

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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.