Evidence map›Paper›PMID 28905658›Full record

ArticleJournal of diabetes science and technology2018

Decision Support for Diabetes in Scotland: Implementation and Evaluation of a Clinical Decision Support System.

Nicholas Conway, Karen A Adamson, Scott G Cunningham, Alistair Emslie Smith, Peter Nyberg, Blair H Smith, Ann Wales, Deborah J Wake

Open access · bronzeAbstract read
In one paragraph

Article in Journal of diabetes science and technology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
0.7field-weighted citation impact, top 27% 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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it, 27 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Review
  6. Review
  7. [Ontologies Applied in Clinical Decision Support Systems for Diabetes].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2023
    Review
  8. [Chronic kidney disease in community: Current state for screening and management].Beijing da xue xue bao. Yi xue ban = Journal of Peking University. Health sciences · 2022
    Article
  9. Review
  10. Article
  11. Emergency Department Clinician Perspectives on the Data Availability to Implement Clinical Decision Support Tools for Five Clinical Practice Guidelines.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2018
    Article
  12. 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

8 authors at 6 institutions in 2 countries.

Nicholas Conway1 NHS Tayside, Ninewells Hospital Dundee, Dundee, UK.
Karen A Adamson3 NHS Lothian, St John's Hospital, Howden Road West, Howden, Livingston, UK.
Scott G Cunningham2 University of Dundee, Ninewells Hospital Dundee, Dundee, UK.
Alistair Emslie Smith2 University of Dundee, Ninewells Hospital Dundee, Dundee, UK.
Peter Nyberg4 Duodecim Medical Publications, Helsinki, Finland.
Blair H Smith2 University of Dundee, Ninewells Hospital Dundee, Dundee, UK.
Ann Wales5 NHS Education for Scotland, Glasgow, UK.
Deborah J Wake1 NHS Tayside, Ninewells Hospital Dundee, Dundee, UK.
Ninewells Hospital · GBFinnish Medical Society Duodecim · FIHowden (United Kingdom) · GBNHS Education for Scotland · GBNHS Tayside · GBUniversity of Dundee · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAutomated clinical decision support systems (CDSS) are associated with improvements in health care delivery to those with long-term conditions, including diabetes. A CDSS was introduced to two Scottish regions (combined diabetes population ~30 000) via a national diabetes electronic health record. This study aims to describe users' reactions to the CDSS and to quantify impact on clinical processes and outcomes over two improvement cycles: December 2013 to February 2014 and August 2014 to November 2014.

methodsFeedback was sought via patient questionnaires, health care professional (HCP) focus groups, and questionnaires. Multivariable regression was used to analyze HCP SCI-Diabetes usage (with respect to CDSS message presence/absence) and case-control comparison of clinical processes/outcomes. Cases were patients whose HCP received a CDSS messages during the study period. Closely matched controls were selected from regions outside the study, following similar clinical practice (without CDSS). Clinical process measures were screening rates for diabetes-related complications. Clinical outcomes included HbA1c at 1 year.

resultsThe CDSS had no adverse impact on consultations. HCPs were generally positive toward CDSS and used it within normal clinical workflow. CDSS messages were generated for 5692 cases, matched to 10 667 controls. Following clinic, the probability of patients being appropriately screened for complications more than doubled for most measures. Mean HbA1c improved in cases and controls but more so in cases (-2.3 mmol/mol [-0.2%] versus -1.1 [-0.1%], P = .003). DISCUSSION AND

conclusionsThe CDSS was well received; associated with improved efficiencies in working practices; and large improvements in guideline adherence. These evidence-based, early interventions can significantly reduce costly and devastating complications.

Indexed as

Decision Support Systems, ClinicalDiabetes MellitusGuideline AdherenceHumansScotlandclinicaldecision support systemsdiabetes mellitusguideline adherenceprocess assessment (health care)

Identifiers

PMID28905658
PMCPMC5851216
OpenAlexW2756218509

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.