Evidence map›Paper›PMID 42098745›Full record

ArticleBMC medical informatics and decision making2026

Strategies to support implementation of infectious disease decision support systems: a scoping review.

Kaia M Nielsen, Sara R Packull-McCormick, Lauren E Grant

Abstract readScoping Review
In one paragraph

Article in BMC medical informatics and decision making, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Kaia M NielsenDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada.
Sara R Packull-McCormickDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada.
Lauren E GrantDepartment of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada. laugrant@uoguelph.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDecision support systems (DSSs) are computerized tools that analyse data to guide actions and inform decision-making. Although DSSs are increasingly used in infectious disease contexts, their adoption remains inconsistent. Effective implementation is essential for integration of these tools into practice. Implementation strategies that promote sustainable uptake have not been comprehensively mapped for infectious disease DSSs. This scoping review aimed to identify and describe implementation strategies, associated outcomes, and use of theories, models, and frameworks (TMFs) in the implementation of infectious disease DSSs designed for early warning, detection, or prevention.

methodsA scoping review was conducted following the Joanna Briggs Institute methodology and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. A limited search in MEDLINE was used to develop the search strategy based on relevant publications. The final search was applied across MEDLINE, CAB Direct, AGRICOLA, and Web of Science using a time limiter (2000-2025). Studies were screened against eligibility criteria by two independent reviewers. Data were charted on implementation strategies, outcomes, and TMFs. Strategies were mapped to the Expert Recommendations for Implementing Change (ERIC) taxonomy, and outcomes were mapped to Proctor's implementation outcomes taxonomy. Data were synthesized by grouping DSSs according to their primary level of public health action: clinical/individual, population/program, or system/governance. Reported or codable strategies, outcomes, and TMFs were summarized within each level of action.

resultsOf the 18,708 records identified, 26 studies reported in 27 publications met the inclusion criteria. In total, 20 unique implementation strategies were identified through reviewer coding of narrative descriptions, 7 implementation outcomes were inferred from descriptive indicators, and 3 TMFs were reported in the literature. Clinical/individual-level DSSs included 13 strategies, 7 outcomes, and 2 TMFs; population/program-level DSSs included 13 strategies, 7 outcomes, and 1 TMF; and system/governance-level DSSs included 7 strategies, 3 outcomes, and no TMFs.

conclusionsImplementation of infectious disease DSSs most often involved activities that mapped to educational and stakeholder engagement strategies, with limited reported use of guiding theories or frameworks. Although outcome reporting was relatively common, outcome definitions and depth of outcome reporting varied widely. More deliberate use of TMFs and systematic outcome evaluation could strengthen the evidence base for DSS implementation. In policy and management contexts, better alignment between strategy selection, system design, and public health objectives may enhance sustainable DSS adoption and impact. REGISTRATION: Not applicable.

Indexed as

Communicable DiseasesDecision Support Systems, ClinicalHumansAcceptabilityAdoptionDecision support systemsFeasibilityFidelityImplementation scienceImplementation strategiesInfectious diseaseScoping review

Identifiers

PMID42098745
PMCPMC13330443

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.