Evidence map›Paper›PMID 37128433›Full record

ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2022

Tailoring Rule-Based Data Quality Assessment to the Patient-Centered Outcomes Research Network (PCORnet) Common Data Model (CDM).

Yahia Mohamed, Xing Song, Tamara M McMahon, Suman Sahil, Meredith Zozus, Zhan Wang, Lemuel R Waitman

Open access · greenAbstract read
In one paragraph

Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
1.2field-weighted citation impact, top 19% 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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it, 7 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. A Customizable Data Quality Tool for Global Observational Research Networks.Studies in health technology and informatics · 2025
    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

7 authors at 3 institutions in 1 country.

Yahia MohamedUniversity of Missouri-Kansas City School of Medicine, Kansas City, MO, USA.
Xing SongUniversity of Missouri School of Medicine, Columbia, MO, USA.
Tamara M McMahonUniversity of Missouri-Kansas City School of Medicine, Kansas City, MO, USA.
Suman SahilUniversity of Missouri-Kansas City School of Medicine, Kansas City, MO, USA.
Meredith ZozusUniversity of Texas Health Science Center at San Antonio.
Zhan WangUniversity of Texas Health Science Center at San Antonio.
Lemuel R WaitmanUniversity of Missouri-Kansas City School of Medicine, Kansas City, MO, USA.
University of Missouri–Kansas City · USThe University of Texas Health Science Center at San Antonio · USUniversity of Missouri · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Individual researchers and research networks have developed and applied different approaches to assess the data quality of electronic health record (EHR) data. A previously published rules-based method to evaluate the data quality of EHR data provides deeper levels of data quality analysis. To examine the effectiveness and generalizability of the rule-based framework, we reprogrammed and translated published rule templates to operate against the PCORnet Common Data Model and executed them against a database for a single center of the Greater Plains Collaborative (GPC) PCORnet Clinical Research Network. The framework detected additional data errors and logical inconsistencies not revealed by current data quality procedures. Laboratory and medication data were more vulnerable to errors. Hemolyzed samples in the emergency department and metformin prescribing in ambulatory clinics are further described to illustrate application of specific rule-based findings by researchers to engage their health systems in evaluating healthcare delivery and clinical quality concerns.

Indexed as

Data AccuracyElectronic Health RecordsDelivery of Health CareHumansPatient Outcome Assessment

Identifiers

PMID37128433
PMCPMC10148276
OpenAlexW4367668345

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.