Evidence map›Paper›PMID 34537047›Full record

ArticleBMC medical informatics and decision making2021

Use of large scale EHR data to evaluate A1c utilization among sickle cell disease patients.

Shivani Sivasankar, An-Lin Cheng, Ira M Lubin, Kamani Lankachandra, Mark A Hoffman

Open access · goldAbstract read
In one paragraph

Article in BMC medical informatics and decision making, 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
0.1field-weighted citation impact, top 50% 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, 1 citations in OpenAlex.

  1. Article
  2. Review
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

5 authors at 2 institutions in 1 country.

Shivani SivasankarSchool of Medicine, University of Missouri-Kansas City, Kansas City, MO, USA.
An-Lin ChengSchool of Medicine, University of Missouri-Kansas City, Kansas City, MO, USA.
Ira M LubinDivision of Laboratory Systems, Centers for Disease Control and Prevention, Atlanta, GA, USA.
Kamani LankachandraSchool of Medicine, University of Missouri-Kansas City, Kansas City, MO, USA.
Mark A HoffmanSchool of Medicine, University of Missouri-Kansas City, Kansas City, MO, USA. mhoffman@cmh.edu.
University of Missouri–Kansas City · USCenters for Disease Control and Prevention · US

Funding

CDC HHS NU47OE000105-01-01
6 · The paper itself

Abstract

backgroundThe glycated hemoglobin (A1c) test is not recommended for sickle cell disease (SCD) patients. We examine ordering patterns of diabetes-related tests for SCD patients to explore misutilization of tests among this underserved population.

methodsWe used de-identified electronic health record (EHR) data in the Cerner Health Facts™ (HF) data warehouse to evaluate the frequency of A1c and fructosamine tests during 2010 to 2016, for 37,151 SCD patients from 393 healthcare facilities across the United States. After excluding facilities with no A1c data, we defined three groups of facilities based on the prevalence of SCD patients with A1c test(s): adherent facilities (no SCD patients with A1c test(s)), minor non-adherent facilities, major non-adherent facilities.

resultsWe determined that 11% of SCD patients (3927 patients) treated at 393 facilities in the US received orders for at least one A1c test. Of the 3927 SCD patients with an A1c test, only 89 patients (2.3%) received an order for a fructosamine test. At the minor non-adherent facilities, 5% of the SCD patients received an A1c test while 58% of the SCD patients at the least adherent facilities had at least one A1c test. Overall, the percent of A1c tests ordered for SCD patients between 2010 and 2016 remained similar.

conclusionsInappropriate A1c test orders among a sickle cell population is a significant quality gap. Interventions to advance adoption of professional recommendations that advocate for alternate tests, such as fructosamine, can guide clinicians in test selection to reduce this quality gap are discussed. The informatics strategy used in this work can inform other largescale analyses of lab test utilization using de-identified EHR data.

Indexed as

Anemia, Sickle CellDiabetes MellitusElectronic Health RecordsFructosamineGlycated HemoglobinHumansUnited StatesFructosamineGlycated HemoglobinA1cElectronic health recordsFructosamineSickle cell disease

Identifiers

PMID34537047
PMCPMC8449923
OpenAlexW3200574721

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.