Evidence map›Paper›PMID 29941004›Full record

ArticleBMC medical informatics and decision making2018

CogStack - experiences of deploying integrated information retrieval and extraction services in a large National Health Service Foundation Trust hospital.

Richard Jackson, Ismail Kartoglu, Clive Stringer, Genevieve Gorrell, Angus Roberts, Xingyi Song, Honghan Wu, Asha Agrawal, Kenneth Lui, Tudor Groza and 5 more

Registry-linked trialOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical informatics and decision making, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04792268 (Implementation of an Electronic Clinical Decision Support System), which is not on this map. Cited by 66 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed, 1 pooled it
6.2field-weighted citation impact, top 3% 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.

NCT04792268 nacompletednot on this mapstarted 2022, after this paper: background citation

Implementation of an Electronic Clinical Decision Support System (eCDSS) for the Early Recognition and Management of Diabetes and Dysglycaemia in Secondary Mental Healthcare : Feasibility Study

TypeinterventionalSponsorKing's College LondonRan2022 to 2023Enrolled4ConditionsSevere Mental Disorder, Diabetes Mellitus, Dysglycemia, Staff AttitudeArmsAccess to eCDSS on wards
3 · Its place in the literature

Who cites it

66 citing papers in PubMed, 1 synthesis or guideline pooled it, 133 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Observational
  5. Article
  6. Article
  7. Article
  8. VIEWER: an extensible visual analytics framework for enhancing mental healthcare.Journal of the American Medical Informatics Association : JAMIA · 2026
    Article
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  16. Review
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  18. Natural language processing data services for healthcare providers.BMC medical informatics and decision making · 2024
    Review
  19. Article
  20. Article

6 more citing papers are in PubMed but not listed here.

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

15 authors at 6 institutions in 2 countries.

Richard JacksonInstitute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigne Park, London, SE5 8AF, UK. richgjackson@gmail.com.ORCID 0000-0002-3278-8547
Ismail KartogluInterDigital Communications, 64 Great Eastern Street, 1st Floor, London, EC2A 3QR, UK.
Clive StringerKing's College Hospital, Denmark Hill, London, SE5 9RS, UK.
Genevieve GorrellUniversity of Sheffield, Western Bank, Sheffield, S10 2TN, UK.
Angus RobertsUniversity of Sheffield, Western Bank, Sheffield, S10 2TN, UK.
Xingyi SongUniversity of Sheffield, Western Bank, Sheffield, S10 2TN, UK.
Honghan WuInstitute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigne Park, London, SE5 8AF, UK.
Asha AgrawalKing's College Hospital, Denmark Hill, London, SE5 9RS, UK.
Kenneth LuiFarr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College London, London, WC1E 6BT, UK.
Tudor GrozaGarvan Institute of Medical Research, Sydney, NSW 2010, Australia.
Damian LewsleyKing's College Hospital, Denmark Hill, London, SE5 9RS, UK.
Doug NorthwoodKing's College Hospital, Denmark Hill, London, SE5 9RS, UK.
Amos FolarinInstitute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigne Park, London, SE5 8AF, UK.
Robert StewartInstitute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigne Park, London, SE5 8AF, UK.
Richard DobsonInstitute of Psychiatry, Psychology and Neuroscience, King's College London, 16 De Crespigne Park, London, SE5 8AF, UK.
King's College London · GBKing's College Hospital · GBUniversity of Sheffield · GBFarr Institute · GBGarvan Institute of Medical Research · AUInterDigital (United Kingdom) · GB

Funding

Arthritis Research UKBritish Heart FoundationCancer Research UKChief Scientist OfficeDepartment of HealthMedical Research Council MC_PC_14089Medical Research Council MC_PC_17214Wellcome Trust MR/K006584/1
6 · The paper itself

Abstract

backgroundTraditional health information systems are generally devised to support clinical data collection at the point of care. However, as the significance of the modern information economy expands in scope and permeates the healthcare domain, there is an increasing urgency for healthcare organisations to offer information systems that address the expectations of clinicians, researchers and the business intelligence community alike. Amongst other emergent requirements, the principal unmet need might be defined as the 3R principle (right data, right place, right time) to address deficiencies in organisational data flow while retaining the strict information governance policies that apply within the UK National Health Service (NHS). Here, we describe our work on creating and deploying a low cost structured and unstructured information retrieval and extraction architecture within King's College Hospital, the management of governance concerns and the associated use cases and cost saving opportunities that such components present.

resultsTo date, our CogStack architecture has processed over 300 million lines of clinical data, making it available for internal service improvement projects at King's College London. On generated data designed to simulate real world clinical text, our de-identification algorithm achieved up to 94% precision and up to 96% recall.

conclusionWe describe a toolkit which we feel is of huge value to the UK (and beyond) healthcare community. It is the only open source, easily deployable solution designed for the UK healthcare environment, in a landscape populated by expensive proprietary systems. Solutions such as these provide a crucial foundation for the genomic revolution in medicine.

Indexed as

Electronic Health RecordsHospitalsNational Health ProgramsNatural Language ProcessingHumansInformation Storage and RetrievalUnited KingdomClinical informaticsElasticsearchElectronic health recordsInformation extractionNatural language processing

Identifiers

PMID29941004
PMCPMC6020175
OpenAlexW2949308662

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.