Evidence map›Paper›PMID 30680840›Full record

ArticlePharmacoepidemiology and drug safety2019

Performance of a computable phenotype for identification of patients with diabetes within PCORnet: The Patient-Centered Clinical Research Network.

Andrew D Wiese, Christianne L Roumie, John B Buse, Herodes Guzman, Robert Bradford, Emily Zalimeni, Patricia Knoepp, Heather L Morris, William T Donahoo, Nada Fanous and 9 more

Open access · greenAbstract read
In one paragraph

Article in Pharmacoepidemiology and drug safety, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% 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

27 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Automated Type 2 Diabetes Case and Control Identification from the MIMIC-IV Database.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2023
    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

19 authors at 6 institutions in 1 country.

Andrew D WieseDepartment of Health Policy, Vanderbilt University Medical Center, Nashville, TN, USA.ORCID 0000-0002-0699-4224
Christianne L RoumieDepartment of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
John B BuseDepartment of Medicine, University of North Carolina, Chapel Hill, NC, USA.
Herodes GuzmanDepartment of Medicine, University of North Carolina, Chapel Hill, NC, USA.
Robert BradfordDepartment of Medicine, University of North Carolina, Chapel Hill, NC, USA.
Emily ZalimeniDepartment of Medicine, University of North Carolina, Chapel Hill, NC, USA.
Patricia KnoeppDepartment of Medicine, University of North Carolina, Chapel Hill, NC, USA.
Heather L MorrisDepartment of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, USA.
William T DonahooDepartment of Medicine, University of Florida, Gainesville, FL, USA.
Nada FanousDepartment of Medicine, University of Florida, Gainesville, FL, USA.
Britany F EpsteinDepartment of Medicine, University of Florida, Gainesville, FL, USA.
Bonnie L KatalenichLA CaTS Clinical Translational Unit, Tulane University School of Medicine, Tulane, LA, USA.
Sujata G AyalaInstitute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.
Megan M CookInstitute for Medicine and Public Health, Vanderbilt University Medical Center, Nashville, TN, USA.
Katherine J WorleyVanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN, USA.
Katherine N BachmannVeterans Health Administration-Tennessee Valley Healthcare System, CSR&D, Nashville, TN, USA.
Carlos G GrijalvaDepartment of Health Policy, Vanderbilt University Medical Center, Nashville, TN, USA.
Russell L RothmanDepartment of Health Policy, Vanderbilt University Medical Center, Nashville, TN, USA.
Rosette J ChakkalakalDepartment of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
Vanderbilt University Medical Center · USUniversity of North Carolina at Chapel Hill · USUniversity of Florida · USVA Tennessee Valley Healthcare System · USTulane University · USUniversity of Florida Health · US

Funding

Re-Entry Supplement: Investigation of Oral Microbial Enzymes for the Detection and Treatment of Periodontal DiseaseUL1TR002489 · NCATS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BUSE, JOHN BERNARD, SHAHEEN, NICHOLAS J · 2018 to 2022
$48.6M
Metabolic Effects of Natriuretic Peptide HormonesIK2CX001678 · VA · VETERANS HEALTH ADMINISTRATION · PI BACHMANN, KATHERINE NEUBECKER · 2018 to 2022
–
CSRD VA IK2 CX001678NCATS NIH HHS UL1 TR002489NIH HHS UL1TR002489Patient-Centered Outcomes Research Institute CDRN-1306-04869
6 · The paper itself

Abstract

purposePCORnet, the National Patient-Centered Clinical Research Network, represents an innovative system for the conduct of observational and pragmatic studies. We describe the identification and validation of a retrospective cohort of patients with type 2 diabetes (T2DM) from four PCORnet sites.

methodsWe adapted existing computable phenotypes (CP) for the identification of patients with T2DM and evaluated their performance across four PCORnet sites (2012-2016). Patients entered the cohort on the earliest date they met one of three CP categories: (CP1) coded T2DM diagnosis (ICD-9/ICD-10) and an antidiabetic prescription, (CP2) diagnosis and glycosylated hemoglobin (HbA1c) ≥6.5%, or (CP3) an antidiabetic prescription and HbA1c ≥6.5%. We required evidence of health care utilization in each of the 2 prior years for each patient, as we also developed an incident T2DM CP to identify the subset of patients without documentation of T2DM in the 365 days before t

resultsThe CP identified 50 657 patients with T2DM. The PPV of patients randomly selected for validation was 96.2% (n = 1572; CI:95.1-97.0) and was consistently high across sites. The PPV for the incident-T2DM CP was 5.8% (CI:4.5-7.5).

conclusionsThe T2DM CP accurately and efficiently identified patients with T2DM across multiple sites that participate in PCORnet, although the incident T2DM CP requires further study. PCORnet is a valuable data source for future epidemiological and comparative effectiveness research among patients with T2DM.

Indexed as

Computer Communication NetworksPatient-Centered CareAdolescentAdultAgedAged, 80 and overAlgorithmsCohort StudiesComparative Effectiveness ResearchDiabetes Mellitus, Type 2Electronic Health RecordsFemaleHumansIncidenceInformation Storage and RetrievalInternational Classification of Diseasesdistributed research networkelectronic health recordsPCORIpharmacoepidemiologytype 2 diabetes

Identifiers

PMID30680840
PMCPMC6615719
OpenAlexW2912206808

What OpenQuestion holds

Textmetadata
LicenceTDM
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.