Evidence map›Paper›PMID 28620094›Full record

ArticleDiabetes care2017

An Interrupted Time Series Analysis to Determine the Effect of an Electronic Health Record-Based Intervention on Appropriate Screening for Type 2 Diabetes in Urban Primary Care Clinics in New York City.

Jeanine B Albu, Nancy Sohler, Rui Li, Xuan Li, Edwin Young, Edward W Gregg, Dennis Ross-Degnan

Open access · bronzeAbstract read
In one paragraph

Article in Diabetes care, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 11% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Observational
  4. Improving Diabetes Screening in the Primary Care Clinic.Joint Commission journal on quality and patient safety · 2023
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  14. Observational
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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

7 authors at 5 institutions in 1 country.

Jeanine B AlbuDivision of Endocrinology, Diabetes and Bone Disease and Division of General Medicine, Department of Medicine, Mount Sinai St. Luke's and Mount Sinai West Hospitals, Icahn School of Medicine at Mount Sinai, New York, NY jalbu@chpnet.org.ORCID 0000-0003-1365-3417
Nancy SohlerSophie Davis School of Biomedical Education/CUNY Medical School of the City College of New York, New York, NY.
Rui LiDivision of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA.
Xuan LiResearch Foundation of the City University of New York, New York, NY.
Edwin YoungDivision of Endocrinology, Diabetes and Bone Disease and Division of General Medicine, Department of Medicine, Mount Sinai St. Luke's and Mount Sinai West Hospitals, Icahn School of Medicine at Mount Sinai, New York, NY.
Edward W GreggDivision of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, GA.
Dennis Ross-DegnanHarvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA.
Centers for Disease Control and Prevention · USIcahn School of Medicine at Mount Sinai · USCity College of New York · USHarvard University · USResearch Foundation of The City University of New York · US

Funding

Translational Research Core - Health Engagement & Action Translational (HEAT)P30DK092924 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI Alyce Sophia Adams, HILARY Kessler SELIGMAN · 2011 to 2026
$9.2M
Management and Education for Diabetes in New York City (MED-NYC)U58DP002717 · DP · ST. LUKE'S-ROOSEVELT INST FOR HLTH SCIS · PI ALBU, JEANINE B · 2010 to 2014
$2.4M
The Impact of Emerging Health Insurance Designs on Diabetes Outcomes and DisparitU58DP002719 · DP · HARVARD PILGRIM HEALTH CARE, INC. · PI ROSS-DEGNAN, DENNIS · 2010 to 2014
$2.2M
NCCDPHP CDC HHS U58 DP002717NCCDPHP CDC HHS U58 DP002719NIDDK NIH HHS P30 DK092924
6 · The paper itself

Abstract

objectiveTo determine the impact of a health system-wide primary care diabetes management system, which included targeted guidelines for type 2 diabetes (T2DM) and prediabetes (dysglycemia) screening, on detection of previously undiagnosed dysglycemia cases. RESEARCH DESIGN AND

methodsIntervention included electronic health record (EHR)-based decision support and standardized providers and staff training for using the American Diabetes Association guidelines for dysglycemia screening. Using EHR data, we identified 40,456 adults without T2DM or recent screening with a face-to-face visit (March 2011-December 2013) in five urban clinics. Interrupted time series analyses examined the impact of the intervention on trends in three outcomes:

resultsBaseline monthly proportion of eligible patients receiving testing was 7.4-10.4%. After the intervention, screening doubled (mean increase + 11.0% [95% CI 9.0, 13.0], proportion range 18.6-25.3%). The proportion of ineligible patients tested also increased (+5.0% [95% CI 3.0, 8.0]) with no concurrent change in cholesterol testing (+0% [95% CI -0.02, 0.05]). About 59% of test results in eligible patients showed dysglycemia both before and after the intervention.

conclusionsImplementation of a policy for systematic dysglycemia screening including formal training and EHR templates in urban academic primary care clinics resulted in a doubling of appropriate testing and the number of patients who could be targeted for treatment to prevent or delay T2DM.

Indexed as

Electronic Health RecordsMass ScreeningAgedAmbulatory Care FacilitiesBody Mass IndexDiabetes Mellitus, Type 2FemaleFollow-Up StudiesHumansInterrupted Time Series AnalysisMaleMiddle AgedNew York CityPrediabetic StatePrimary Health CareSurveys and Questionnaires

Identifiers

PMID28620094
PMCPMC5521966
OpenAlexW2625945292

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.