Evidence map›Paper›PMID 23616881›Full record

ArticleApplied clinical informatics2011

Opportunities to Increase the Effectiveness of EHR-Based Diabetes Clinical Decision Support.

P O'Connor

Registry-linked trialAbstract read
In one paragraph

Article in Applied clinical informatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01420016 (Prioritized Clinical Decision Support), which is not on this map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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.

NCT01420016 nacompletednot on this mapstarted 2012, after this paper: background citation

Prioritized Clinical Decision Support (CDS) to Reduce Cardiovascular Risk

TypeinterventionalSponsorHealthPartners InstituteRan2012 to 2014Enrolled7,914ConditionsHypertension, Hyperlipidemia, Diabetes, SmokingArmsPrioritized Clinical Decision Support
3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Trial
  2. Clinical Decision Support with or without Shared Decision Making to Improve Preventive Cancer Care: A Cluster-Randomized Trial.Medical decision making : an international journal of the Society for Medical Decision Making · 2022
    Trial
  3. Trial
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. 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

1 author.

P O'ConnorHealthPartners - Research Foundation, Minneapolis Minnesota , United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There are many opportunities to improve diabetes care through more effective use of EHR-based CDS. The report of Kantor et al. [16] is encouraging because it demonstrates sustained efforts by leading health care organizations to implement diabetes-related EHR-based CDS. However, lack of sophisticated treatment-specific CDS and lack of prioritized recommendations are a cause for concern. Even more disturbing is the substantive heterogeneity in content of diabetes CDS recommendations now in the field. Some of CDS recommendations described by Kantor et al. [16] are clearly not evidence-based and could increase costs while not improving clinical benefits. The timely identification of these problems is an awkward but necessary first step towards improvement. The health care organizations that are pioneers in the field should be congratulated and encouraged to continue their collaborative efforts to increase the efficiency and effectiveness of EHR-based CDS. Attending to the modest proposals put forward here and by others may help translate the massive investments that we have made in EHR technology into clinical benefits for our patients.

Indexed as

CDSclinical decision supportclinical guidelinesconflict of interestdiabetesElectronic medical recordsevidence-based medicine

Identifiers

PMID23616881
PMCPMC3631926

What OpenQuestion holds

Textmetadata
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.