Evidence map›Paper›PMID 32927058›Full record

ArticleJournal of biomedical informatics2020

A method for measuring the effect of certified electronic health record technology on childhood immunization status scores among Medicaid managed care network providers.

Paul J Messino, Hadi Kharrazi, Julia M Kim, Harold Lehmann

Open access · greenAbstract read
In one paragraph

Article in Journal of biomedical informatics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 43% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 3 institutions in 1 country.

Paul J MessinoMathematica, Woodlawn, MD, USA. Electronic address: pmessino@mathematica-mpr.com.
Hadi KharraziJohns Hopkins School of Public Health, Center for Population Health IT, Baltimore, MD, USA; Johns Hopkins School of Medicine, Division of Health Sciences Informatics, Baltimore, MD, USA.
Julia M KimJohns Hopkins School of Medicine, Department of Pediatrics, Baltimore, MD, USA.
Harold LehmannJohns Hopkins School of Medicine, Division of Health Sciences Informatics, Baltimore, MD, USA.
Johns Hopkins University · USBloomberg (United States) · USMathematica Policy Research · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo provide a methodology for estimating the effect of U.S.-based Certified Electronic Health Records Technology (CEHRT) implemented by primary care physicians (PCPs) on a Healthcare Effectiveness Data and Information Set (HEDIS) measure for childhood immunization delivery. MATERIALS AND

methodsThis study integrates multiple health care administrative data sources from 2010 through 2014, analyzed through an interrupted time series design and a hierarchical Bayesian model. We compared managed care physicians using CEHRT to propensity-score matched comparisons from network physicians who did not adopt CEHRT. Inclusion criteria for physicians using CEHRT included attesting to the Childhood Immunization Status clinical quality measure in addition to meeting "Meaningful Use" (MU) during calendar year 2013. We used a first-presence patient attribution approach to develop provider-specific immunization scores.

resultsWe evaluated 147 providers using CEHRT, with 147 propensity-score matched providers selected from a pool of 1253 PCPs practicing in Maryland. The estimate for change in odds of increasing immunization rates due to CEHRT was 1.2 (95% credible set, 0.88-1.73). DISCUSSION: We created a method for estimating immunization quality scores using Bayesian modeling. Our approach required linking separate administrative data sets, constructing a propensity-score matched cohort, and using first-presence, claims-based childhood visit information for patient attribution. In the absence of integrated data sets and precise and accurate patient attribution, this is a reusable method for researchers and health system administrators to estimate the impact of health information technology on individual, provider-level, process-based, though outcomes-focused, quality measures.

conclusionThis research has provided evidence for using Bayesian analysis of propensity-score matched provider populations to estimate the impact of CEHRT on outcomes-based quality measures such as childhood immunization delivery.

Indexed as

Electronic Health RecordsMedicaidBayes TheoremChildHumansImmunizationManaged Care ProgramsMarylandTechnologyUnited StatesAttributionBayesElectronic health recordImmunizationPropensity scoreQuality

Identifiers

PMID32927058
PMCPMC7486207
OpenAlexW3085161819

What OpenQuestion holds

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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.