Evidence map›Paper›PMID 31619388›Full record

ArticleBMJ health & care informatics2019

LAGOS: learning health systems and how they can integrate with patient care.

Scott McLachlan, Kudakwashe Dube, Evangelia Kyrimi, Norman Fenton, HiKER (Health informatics and Knowledge Engineering Research) Group

Abstract read
In one paragraph

Article in BMJ health & care informatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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.

Scott McLachlanEECS, Queen Mary University of London, London, UK s.mclachlan@qmul.ac.uk.ORCID http://orcid.org/0000-0002-2528-8050
Kudakwashe DubeSchool of Fundamental Sciences, Massey University, Palmerston North, New Zealand.ORCID http://orcid.org/0000-0002-2829-8481
Evangelia KyrimiEECS, Queen Mary University of London, London, UK.
Norman FentonEECS, Queen Mary University of London, London, UK.ORCID http://orcid.org/0000-0003-2924-0510
HiKER (Health informatics and Knowledge Engineering Research) Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

problemLearning health systems (LHS) are an underexplored concept. How LHS will operate in clinical practice is not well understood. This paper investigates the relationships between LHS, clinical care process specifications (CCPS) and the established levels of medical practice to enable LHS integration into daily healthcare practice.

methodsConcept analysis and thematic analysis were used to develop an LHS characterisation. Pathway theory was used to create a framework by relating LHS, CCPS, health information systems and the levels of medical practice. A case study approach evaluates the framework in an established health informatics project.

resultsFive concepts were identified and used to define the LHS learning cycle. A framework was developed with five pathways, each having three levels of practice specificity spanning population to precision medicine. The framework was evaluated through application to case studies not previously understood to be LHS. DISCUSSION: Clinicians show limited understanding of LHS, increasing resistance and limiting adoption and integration into care routine. Evaluation of the presented framework demonstrates that its use enables: (1) correct analysis and characterisation of LHS; (2) alignment and integration into the healthcare conceptual setting; (3) identification of the degree and level of patient application; and (4) impact on the overall healthcare system.

conclusionThis paper contributes a theoretical framework for analysis, characterisation and use of LHS. The framework allows clinicians and informaticians to correctly identify, characterise and integrate LHS within their daily routine. The overall contribution improves understanding, practice and evaluation of the LHS application in healthcare.

Indexed as

Attitude of Health PersonnelSystems IntegrationCritical PathwaysHumansKnowledgeLearning Health SystemOutcome and Process Assessment, Health CarePatient CareBMJ Health Informaticsinformation scienceinformation systemsmedical informaticspublic health

Identifiers

PMID31619388
PMCPMC7062338

What OpenQuestion holds

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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.