Evidence map›Paper›PMID 41143815›Full record

ArticleJAMA pediatrics2026

Development of an Atlas for US Pediatric Acute Care.

Kenneth A Michelson, Andrew D Skol, John A Graves, Katherine E Remick, Patrick D McMullen, Naveen Singamsetty, Danielle K Cory, Emily M Bucholz

Abstract read
In one paragraph

Article in JAMA pediatrics, 2026. 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
–field-weighted citation impact
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. Article
  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

8 authors.

Kenneth A MichelsonDivision of Emergency Medicine, Ann & Robert H. Lurie Children's Hospital, Chicago, Illinois.
Andrew D SkolStanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital, Chicago, Illinois.
John A GravesDepartment of Health Policy, Vanderbilt University School of Medicine, Nashville, Tennessee.
Katherine E RemickDepartment of Pediatrics, Dell Medical School, University of Texas at Austin, Austin.
Patrick D McMullenStanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital, Chicago, Illinois.
Naveen SingamsettyStanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital, Chicago, Illinois.
Danielle K CoryDivision of Emergency Medicine, Ann & Robert H. Lurie Children's Hospital, Chicago, Illinois.
Emily M BucholzSection of Cardiology, Department of Pediatrics, University of Colorado and Children's Hospital Colorado, Aurora.

Funding

Measuring and Mapping National Pediatric Acute Care OutcomesR01HD112321 · NICHD · LURIE CHILDREN'S HOSPITAL OF CHICAGO · PI Kenneth Michelson · 2023 to 2026
$1.6M
NICHD NIH HHS R01 HD112321
6 · The paper itself

Abstract

Importance: Pediatric acute care in the US is highly regionalized. Existing geographic frameworks to measure acute care patterns were developed based on adults and do not reflect pediatric use patterns. Objective: To develop a national US atlas of pediatric acute care regions. Design, Setting, and Participants: This was a cross-sectional study of Medicaid data from January 2021 to December 2022, with analysis from April 2024 to June 2025, of US acute care hospitals. Emergency and inpatient encounters among youth younger than 16 years enrolled in Medicaid or the Children's Health Insurance Program, comprising more than half of US youths, were included. Main Outcome and Measures: The primary outcome was modularity, a measure of how well an atlas fits pediatric use patterns. Using network analysis, pediatric emergency service areas (PESAs) were derived capturing home-to-hospital care seeking and pediatric emergency referral regions (PERRs) capturing interhospital referrals. Modularity, proportion of encounters staying within region, size, and hospital counts between atlases were compared. Local-level comparisons included PESAs, Dartmouth Atlas hospital service areas (HSAs), and pediatric HSAs (PHSAs) derived using Dartmouth methods. Referral-level comparisons compared PERRs with Dartmouth hospital referral regions (HRRs), pediatric HRRs (PHRRs), and states. Results: Using data from 27 817 736 encounters (median [IQR] age, 5 [2-10] years; 14 547 400 [52.3%] male) from 4830 hospitals, 835 PESAs and 105 PERRs were identified. PESAs were larger and included more hospitals and youths than HSAs or PHSAs. PERRs were larger (median [IQR], 17 595 [7781-33 251] square miles) and contained more hospitals (median [IQR], 39 [23-59]) and youths (median [IQR], 597 000 [358 000-864 000]) than HRRs (medians [IQRs]: 4822 [2044-9425] square miles, 11 [6-18] hospitals, 146 000 [74 000-282 000] youths) or PHRRs (medians [IQRs]: 8845 [4209-16 608] square miles, 21 [13-35] hospitals, 348 000 [26 703-70 282] youths). States were larger (median [IQR], 50 097 [211 000-638 000] square miles) and had more hospitals (median [IQR], 74 [41-113]), and youths (median [IQR], 961 000 [366 000-1 615 000]) than PERRs. PESAs had the highest local-level modularity. PERRs had the highest referral-level modularity. Among acute care encounters, 89.9% stayed within PESA, 68.6% within HSA, and 80.1% within PHSA. Among referrals, 92.3% stayed within PERR, 73.0% within HRR, 81.9% within PHRR, and 93.4% within state. Conclusions and Relevance: The Atlas of Pediatric Acute Care is the first empirically derived, pediatric-specific map of acute care regions spanning the US. Based on actual use patterns, this atlas may serve as a foundation for pediatric research, policy, regional planning, and quality improvement.

Indexed as

Atlases as TopicEmergency Service, HospitalAdolescentChildChild, PreschoolCross-Sectional StudiesFemaleHumansInfantMaleMedicaidUnited States

Identifiers

PMID41143815
PMCPMC12560029

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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.