Evidence map›Paper›PMID 34304149›Full record

ArticleJMIR human factors2021

Robotic Pharmacy Implementation and Outcomes in Saudi Arabia: A 21-Month Usability Study.

Hisham Momattin, Shokry Arafa, Shahad Momattin, Rayan Rahal, James Waterson

Open access · goldAbstract read
In one paragraph

Article in JMIR human factors, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.9field-weighted citation impact, top 15% of its field
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

15 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
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  4. Review
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  8. Improving Inpatient Medication Dispensing with an Automated System.Global journal on quality and safety in healthcare · 2023
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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 at 2 institutions in 1 country.

Hisham Momattin *Mouwasat Medical Services, Dammam, Saudi Arabia.ORCID https://orcid.org/0000-0003-2331-9180
Shokry Arafa *Mouwasat Medical Services, Dammam, Saudi Arabia.ORCID https://orcid.org/0000-0003-4547-6865
Shahad Momattin *King Faisal University, Al Hassa, Dammam, Saudi Arabia.ORCID https://orcid.org/0000-0002-9854-5847
Rayan Rahal *Medication Management Solutions, Becton Dickinson Limited, Dubai, United Arab Emirates.ORCID https://orcid.org/0000-0002-8338-5334
James Waterson *Medical Affairs, Medication Management Solutions, Becton Dickinson Limited, Dubai, United Arab Emirates.ORCID https://orcid.org/0000-0002-4100-5970
Dammam Central Hospital · SAKing Faisal University · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe describe the introduction, use, and evaluation of an automation and integration pharmacy development program in a private facility in Saudi Arabia. The project was specifically undertaken to increase throughput, reduce medication dispensing error rates, improve patient satisfaction, and free up pharmacists' time to allow for increased face-to-face consultations with patients.

objectiveWe forecasted growth of our outpatient service at 25% per annum over 5- and 10-year horizons and set out to prepare our outpatient pharmacy service to meet this demand. Initial project goals were set as a 50% reduction in the average patient wait time, a 15% increase in patient satisfaction regarding pharmacy wait time and pharmacy services, a 25% increase in pharmacist productivity, and zero dispensing errors. This was expected to be achieved within 10 months of go-live. Realignment of pharmacist activity toward counseling and medication review with patients was a secondary goal, along with the rapid development of a reputation in the served community for patient-centered care.

methodsPreimplementation data for patient wait time for dispensing of prescribed medications as a specific measure of patient satisfaction was gathered as part of wider ongoing data collection in this field. Pharmacist activity and productivity in terms of patient interaction time were gathered. Reported and discovered dispensing errors per 1000 prescriptions were also aggregated. All preimplementation data was gathered over an 11-month period.

resultsFrom go-live, data were gathered on the above metrics in 1-month increments. At the 10-month point, there had been a 53% reduction in the average wait time, a 20% increase in patient satisfaction regarding pharmacy wait time, with a 22% increase in overall patient satisfaction regarding pharmacy services, and a 33% increase in pharmacist productivity. A zero dispensing error rate was reported.

conclusionsThe robotic pharmacy solution studied was highly effective, but a robust upstream supply chain is vital to ensure stock levels, particularly when automated filling is planned. The automation solution must also be seamlessly and completely integrated into the facility's software systems for appointments, medication records, and prescription generation in order to garner its full benefits. Overall patient satisfaction with pharmacy services is strongly influenced by wait time and follow-up studies are required to identify how to use this positive effect and make optimal use of freed-up pharmacist time. The extra time spent by pharmacists with patients and the opportunity for complete overview of the patient's medication history, which full integration provides, may allow us to address challenging issues such as medication nonadherence. Reduced wait times may also allow for smaller prescription fill volumes, and more frequent outpatient department visits, allowing patients to have increased contact time with pharmacists.

Indexed as

automationerrorimplementationintegrationmedication dispensingmedication errormedication managementmedication recordsoutcomeoutpatientpatient satisfactionpharmacyrecordroboticsusability

Identifiers

PMID34304149
PMCPMC8444036
OpenAlexW3183605385

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.