Evidence map›Paper›PMID 35276480›Full record

ArticleGeriatric nursing (New York, N.Y.)

Post-acute long-term care COVID-19 medication optimization survey: Informing medication management initiatives.

Catherine Kim, Emily Francis, Woo Ree Kim, Nicole Brandt

Open access · greenAbstract read
In one paragraph

Article in Geriatric nursing (New York, N.Y.). The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.3field-weighted citation impact, top 48% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 1 institution in 1 country.

Catherine KimUniversity of Maryland School of Pharmacy, 20 N Pine St, Baltimore, MD 21201, Untied States. Electronic address: Catherinekim@umaryland.edu.
Emily FrancisUniversity of Maryland School of Pharmacy, 20 N Pine St, Baltimore, MD 21201, Untied States.
Woo Ree KimUniversity of Maryland School of Pharmacy, 20 N Pine St, Baltimore, MD 21201, Untied States.
Nicole BrandtUniversity of Maryland School of Pharmacy, 20 N Pine St, Baltimore, MD 21201, Untied States; Peter Lamy Center on Drug Therapy and Aging, 220 Arch Street, 12th Floor, Baltimore, MD 21201, Untied States.
University of Maryland, Baltimore · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Medication Management Guide (MMG) provides guidance on strategies to optimize medication management in PA-LTC and simplify administration to reduce the transmission risk of COVID-19. The objectives of this study were to evaluate the utility of the MMG, determine the barriers and facilitators of the MMG implementation in PALTC sites to help inform future research and initiatives. Individuals who accessed MMG during the pandemic (April 2020-March 2021) were contacted to elicit feedback on this tool via an online survey. The survey response rate was 7.7% (156/2,018) after three rounds of emails. Respondents consisted of 31% (n=49) pharmacists, 27% (n=42) physicians, 11% (n=18) nurses, and 12% (n=19) nurse practitioners. The "Other" respondents (11%, n=17) included dieticians (n=4), physician assistants (n=3), pharmacy technicians (n=3), students (n=1), consultants (n=1), and educators (n=2). From these respondents, 77% (n=122) took tactics to optimize medications at their facilities during COVID-19.

Indexed as

COVID-19Long-Term CareHumansMedication Therapy ManagementPharmaceutical PreparationsPharmacistsPharmaceutical PreparationsImplementationMedication optimizationPandemic

Identifiers

PMID35276480
PMCPMC8841217
OpenAlexW4213304603

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.