Evidence map›Paper›PMID 34976636›Full record

ArticlePreventive medicine reports2021

Developing a synthetic control group using electronic health records: Application to a single-arm lifestyle intervention study.

Yi-An Ko, Zhenchao Chen, Chang Liu, Yingtian Hu, Arshed A Quyyumi, Lance A Waller, Melinda Higgins, Thomas R Ziegler, Kenneth L Brigham, Greg S Martin

Open access · goldAbstract read
In one paragraph

Article in Preventive medicine reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 33% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. 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

10 authors at 1 institution in 1 country.

Yi-An KoDepartment of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health, Atlanta, GA, United States.
Zhenchao ChenDepartment of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health, Atlanta, GA, United States.
Chang LiuDepartment of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, United States.
Yingtian HuDepartment of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health, Atlanta, GA, United States.
Arshed A QuyyumiDivision of Cardiology, Department of Medicine, Emory University School of Medicine, Atlanta, GA, United States.
Lance A WallerDepartment of Biostatistics and Bioinformatics, Emory University Rollins School of Public Health, Atlanta, GA, United States.
Melinda HigginsEmory University School of Nursing, Atlanta, GA, United States.
Thomas R ZieglerDivision of Endocrinology, Metabolism and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA, United States.
Kenneth L BrighamDivision of Pulmonary, Critical Care and Allergy, Department of Medicine, Emory University School of Medicine, Atlanta, GA, United States.
Greg S MartinDivision of Pulmonary, Critical Care and Allergy, Department of Medicine, Emory University School of Medicine, Atlanta, GA, United States.
Emory University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The electronic health records (EHR) infrastructure offers a tremendous resource for identifying controls who match the characteristics of study participants in a single-arm trial. The objectives are to (1) demonstrate the feasibility of curating a synthetic control group for an existing study cohort through EHR data extraction and (2) evaluate the effect of a lifestyle intervention on selected cardiovascular health metrics. A total of 711 university employees were recruited between 2008 and 2012 to participate in a health partner intervention to improve cardiovascular health and were followed for five years. Data of nearly 8000 eligible subjects were extracted from the EHR to create a synthetic control cohort during the same study period. To minimize confounding, crude comparison, exact matching, propensity score matching, and doubly robust estimation were used to compare the selected cardiovascular health metrics at 1 and 5 years of follow-up. Blood pressure and body mass index improved in the intervention group compared to the EHR synthetic controls. The findings of changes in lipid measurements were somewhat unexpected. When analyzing the subgroup without lipid-lowering medications, the intervention group exhibited better control of cholesterol levels over time than did our synthetic controls. Some measurements in the EHR system may be more robust for synthetic selection than others. EHR synthetic controls can provide an alternative to estimate intervention effects appropriately in single-arm studies for these measurements.

Indexed as

Controlled trialsDoubly robustElectronic medical recordPseudo control

Identifiers

PMID34976636
PMCPMC8683890
OpenAlexW3207702618

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.