Evidence map›Paper›PMID 38073398›Full record

ArticleJournal of neonatal-perinatal medicine2023

Identifying neonatal intensive care (NICU) admissions using administrative claims data.

A J Vance, S Bell, A Tilea, D Beck, K M Tabb, K Zivin

Open access · greenAbstract read
In one paragraph

Article in Journal of neonatal-perinatal medicine, 2023. 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
2.9field-weighted citation impact, top 9% 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, 5 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

6 authors at 3 institutions in 1 country.

A J VanceCenter for Health Policy and Health Services Research, Henry Ford Health, Detroit, MI, USA.
S BellDepartment of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, USA.
A TileaDepartment of Obstetrics and Gynecology, University of Michigan, Ann Arbor, MI, USA.
D BeckUCLA School of Nursing, Los Angeles, CA, USA.
K M TabbUniversity of Illinois at Urbana-Champaign, School of Social Work, Urbana, IL, USA.
K ZivinInstitute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA.
University of Michigan–Ann Arbor · USMichigan State University · USUniversity of Illinois Urbana-Champaign · US

Funding

Disparities in utilization and delivery outcomes for women with perinatal mood and anxiety disorders (PMAD): groundwork for state policymakingR01MD014958 · NIMHD · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZIVIN, KARA · 2021 to 2025
$3.2M
Relationship between mental health coverage and outcomes for privately insured women with perinatal mood and anxiety disorders (PMAD)R01MH120124 · NIMH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZIVIN, KARA · 2019 to 2022
$2.8M
NIMHD NIH HHS R01 MD014958NIMH NIH HHS R01 MH120124NINR NIH HHS L40 NR020542
6 · The paper itself

Abstract

backgroundTo define a method for identifying neonatal intensive care unit (NICU) admissions using administrative claims data.

methodsThis was a retrospective cohort study using claims from Optum's de-identified Clinformatics® Data Mart Database (CDM) from 2016 -2020. We developed a definition to identify NICU admissions using a list of codes from the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), Current Procedural Terminology (CPT), and revenue codes frequently associated with NICU admissions. We compared agreement between codes using Kappa statistics and calculated positive predictive values (PPV) and 95% confidence intervals (CI).

resultsOn average, revenue codes (3.3%) alone identified more NICU hospitalizations compared to CPT codes alone (1.5%), whereas the use of CPT and revenue (8.9%) and CPT or revenue codes (13.7%) captured the most NICU hospitalizations, which aligns with rates of preterm birth. Gestational age alone (4.2%) and birthweight codes alone (2.0%) identified the least number of potential NICU hospitalizations. Setting CPT codes as the standard and revenue codes as the "test,", revenue codes resulted in identifying 86% of NICU admissions (sensitivity) and 97% of non-NICU admissions (specificity).

conclusionsUsing administrative data, we developed a robust definition for identifying neonatal admissions. The identified definition of NICU codes is easily adaptable, repeatable, and flexible for use in other datasets.

Indexed as

Intensive Care, NeonatalPremature BirthFemaleHospitalizationHumansInfant, NewbornIntensive Care Units, NeonatalRetrospective StudiesClaims datainfantneonatal intensive care unitvalidation

Identifiers

PMID38073398
PMCPMC10916318
OpenAlexW4389474969

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.