Evidence map›Paper›PMID 33489625›Full record

ArticleCureus2020

Implementation of Electronic Decision Support for Diabetic Care in a Student-Run Clinic.

Ankur Srivastava, Delia Shen, Maxim I Maron, Howard S Herman, Brandon S Cohen, Avigdor Nosrati, Amarilys R Cortijo, Sarah Nosal, Ellie Schoenbaum

Abstract read
In one paragraph

Article in Cureus, 2020. 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

9 authors.

Ankur SrivastavaInternal Medicine, Albert Einstein College of Medicine, Bronx, USA.
Delia ShenInternal Medicine, Albert Einstein College of Medicine, Bronx, USA.
Maxim I MaronInternal Medicine, Albert Einstein College of Medicine, Bronx, USA.
Howard S HermanInternal Medicine, Albert Einstein College of Medicine, Bronx, USA.
Brandon S CohenInternal Medicine, Albert Einstein College of Medicine, Bronx, USA.
Avigdor NosratiInternal Medicine, Albert Einstein College of Medicine, Bronx, USA.
Amarilys R CortijoFamily Medicine, The Institute for Family Health, Bronx, USA.
Sarah NosalFamily Medicine, The Institute for Family Health, Bronx, USA.
Ellie SchoenbaumInternal Medicine, Albert Einstein College of Medicine, Bronx, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objectives Type 2 diabetes mellitus (T2DM) is a complex disease that can lead to complications. Electronic decision support in the electronic medical record (EMR) aids management. There is no study demonstrating the effectiveness of electronic decision support in assisting medical student providers in student-run free clinics. Methods There were 71 T2DM patients seen by medical students. Twenty-three encounters used a Diabetes Progress Note (DPN) that was created from consensus, opinion-based guidelines. Each note received a total composite score based on an eight-point scale for adherence to guidelines. Statistical comparisons between mean composite scores were performed using independent t-tests. Results The mean total composite score of DPN users was significantly greater than DPN non-users (5.35 vs. 4.23, p = 0.008), with a significant difference in the physical exam component (1.70 vs. 1.31, p = 0.002). Conclusions In this exploratory study, medical student providers at an attending-supervised, student-run free clinic that used electronic decision support during T2DM patient visits improved adherence to screening for diabetic complications and standard of care.

Indexed as

clinical decision supportdiabeteselectronic medical record

Identifiers

PMID33489625
PMCPMC7815305

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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.