Evidence map›Paper›PMID 36066928›Full record

ArticleJournal of medical Internet research2022

Decision Support Tools in Adult Long-term Care Facilities: Scoping Review.

Linda Lapp, Kieren Egan, Lisa McCann, Moira Mackenzie, Ann Wales, Roma Maguire

Open access · goldAbstract readScoping Review
In one paragraph

Article in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
4.2field-weighted citation impact, top 6% 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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 17 citations in OpenAlex.

  1. Pooled it
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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

6 authors at 1 institution in 1 country.

Linda LappDepartment of Computer and Information Sciences, University of Strathclyde, Glasgow, United Kingdom.ORCID 0000-0003-3743-434X
Kieren EganDepartment of Computer and Information Sciences, University of Strathclyde, Glasgow, United Kingdom.ORCID 0000-0002-1639-4281
Lisa McCannDepartment of Computer and Information Sciences, University of Strathclyde, Glasgow, United Kingdom.ORCID 0000-0002-5322-5778
Moira MackenzieDigital Health & Care Innovation Centre, Glasgow, United Kingdom.ORCID 0000-0003-4044-4442
Ann WalesDigital Health & Care Innovation Centre, Glasgow, United Kingdom.ORCID 0000-0003-1379-9379
Roma MaguireDepartment of Computer and Information Sciences, University of Strathclyde, Glasgow, United Kingdom.ORCID 0000-0001-7935-3447
University of Strathclyde · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital innovations are yet to make real impacts in the care home sector despite the considerable potential of digital health approaches to help with continued staff shortages and to improve quality of care. To understand the current landscape of digital innovation in long-term care facilities such as nursing and care homes, it is important to find out which clinical decision support tools are currently used in long-term care facilities, what their purpose is, how they were developed, and what types of data they use.

objectiveThe aim of this review was to analyze studies that evaluated clinical decision support tools in long-term care facilities based on the purpose and intended users of the tools, the evidence base used to develop the tools, how the tools are used and their effectiveness, and the types of data the tools use to contribute to the existing scientific evidence to inform a roadmap for digital innovation, specifically for clinical decision support tools, in long-term care facilities.

methodsA review of the literature published between January 1, 2010, and July 21, 2021, was conducted, using key search terms in 3 scientific journal databases: PubMed, Cochrane Library, and the British Nursing Index. Only studies evaluating clinical decision support tools in long-term care facilities were included in the review.

resultsIn total, 17 papers were included in the final review. The clinical decision support tools described in these papers were evaluated for medication management, pressure ulcer prevention, dementia management, falls prevention, hospitalization, malnutrition prevention, urinary tract infection, and COVID-19 infection. In general, the included studies show that decision support tools can show improvements in delivery of care and in health outcomes.

conclusionsAlthough the studies demonstrate the potential of positive impact of clinical decision support tools, there is variability in results, in part because of the diversity of types of decision support tools, users, and contexts as well as limited validation of the tools in use and in part because of the lack of clarity in defining the whole intervention.

Indexed as

COVID-19Long-Term CareAdultHospitalizationHumansNursing Homescare homedecision supportdigital healthnursing home

Identifiers

PMID36066928
PMCPMC9490521
OpenAlexW4291012207

What OpenQuestion 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 OpenQuestion graph.