Evidence map›Paper›PMID 29606286›Full record

ArticleAnnals of emergency medicine2018

Referral Regions for Time-Sensitive Acute Care Conditions in the United States.

David J Wallace, Deepika Mohan, Derek C Angus, Julia R Driessen, Christopher M Seymour, Donald M Yealy, Mark M Roberts, Kristen S Kurland, Jeremy M Kahn

Abstract read
In one paragraph

Article in Annals of emergency medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

9 authors.

David J WallaceClinical Research, Investigation and Systems Modeling of Acute Illness Center, and the Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA. Electronic address: wallacedj@upmc.edu.
Deepika MohanClinical Research, Investigation and Systems Modeling of Acute Illness Center, and the Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA; Department of Surgery, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Derek C AngusClinical Research, Investigation and Systems Modeling of Acute Illness Center, and the Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA; Department of Health Policy and Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA.
Julia R DriessenDepartment of Health Policy and Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA.
Christopher M SeymourClinical Research, Investigation and Systems Modeling of Acute Illness Center, and the Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA; Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Donald M YealyDepartment of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA.
Mark M RobertsDepartment of Health Policy and Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA.
Kristen S KurlandSchool of Architecture, College of Fine Arts, Heinz College, Carnegie Mellon University, Pittsburgh, PA.
Jeremy M KahnClinical Research, Investigation and Systems Modeling of Acute Illness Center, and the Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA; Department of Health Policy and Management, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA.

Funding

Sepsis subtypes: biology, treatment, and bedside applicationR35GM119519 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Christopher W. Seymour · 2016 to 2026
$4.9M
A novel intervention to make heuristics a source of power for physiciansDP2LM012339 · NLM · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI MOHAN, DEEPIKA · 2015 to 2015
$2.3M
Understanding Regional Critical Care Delivery in Acute Respiratory FailureK08HL122478 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI WALLACE, DAVID JOHN · 2015 to 2018
$606k
Patient Oriented Research and Mentoring in Critical Care Implementation ScienceK24HL133444 · NHLBI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI KAHN, JEREMY M · 2016 to 2018
$348k
NHLBI NIH HHS K08 HL122478NHLBI NIH HHS K24 HL133444NIGMS NIH HHS R35 GM119519NLM NIH HHS DP2 LM012339
6 · The paper itself

Abstract

STUDY

objectiveRegional, coordinated care for time-sensitive and high-risk medical conditions is a priority in the United States. A necessary precursor to coordinated regional care is regions that are actionable from clinical and policy standpoints. The Dartmouth Atlas of Health Care, the major health care referral construct in the United States, uses regions that cross state and county boundaries, limiting fiscal or political ownership by key governmental stakeholders in positions to create incentive and regulate regional care coordination. Our objective is to develop and evaluate referral regions that define care patterns for patients with acute myocardial infraction, acute stroke, or trauma, yet also preserve essential political boundaries.

methodsWe developed a novel set of acute care referral regions using Medicare data in the United States from 2011. For acute myocardial infraction, acute stroke, or trauma, we iteratively aggregated counties according to patient home location and treating hospital address, using a spatial algorithm. We evaluated referral political boundary preservation and spatial accuracy for each set of referral regions.

resultsThe new set of referral regions, the Pittsburgh Atlas, had 326 distinct regions. These referral regions did not cross any county or state borders, whereas 43.1% and 98.1% of all Dartmouth Atlas hospital referral regions crossed county and state borders. The Pittsburgh Atlas was comparable to the Dartmouth Atlas in measures of spatial accuracy and identified larger at-risk populations for all 3 conditions.

conclusionA novel and straightforward spatial algorithm generated referral regions that were politically actionable and accountable for time-sensitive medical emergencies.

Indexed as

AgedAged, 80 and overAlgorithmsCritical CareEmergency Medical ServicesFemaleHumansMaleMedicareMyocardial InfarctionPractice Guidelines as TopicReferral and ConsultationStrokeTime FactorsUnited States

Identifiers

PMID29606286
PMCPMC6977951

What OpenQuestion holds

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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.