Evidence map›Paper›PMID 37347481›Full record

ArticleJAMA network open2023

Patterns in Patient Encounters and Emergency Department Capacity in California, 2011-2021.

Renee Y Hsia, Stefany Zagorov, Nandita Sarkar, Michael T Savides, Madeline Feldmeier, Newton Addo

Abstract read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
–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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Article
  6. The Benefit of the Doubt Phenomenon in Emergency Triage Assignment Disparities.medRxiv : the preprint server for health sciences · 2026
    Article
  7. Article
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  14. Emergency department crowding: a national data report.Clinical and experimental emergency medicine · 2024
    Article
  15. Observational
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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

6 authors.

Renee Y HsiaDepartment of Emergency Medicine, University of California, San Francisco.
Stefany ZagorovDepartment of Emergency Medicine, University of California, San Francisco.
Nandita SarkarNational Bureau of Economic Research, Cambridge, Massachusetts.
Michael T SavidesDepartment of Emergency Medicine, University of California, San Francisco.
Madeline FeldmeierDepartment of Emergency Medicine, University of California, San Francisco.
Newton AddoDepartment of Emergency Medicine, University of California, San Francisco.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: The health care system has undergone major changes in the past decade, and emergency department (ED) crowding has worsened over time; however, the most recent patterns in ED capacity and use in California have yet to be studied. Objective: To analyze patterns in ED capacity and utilization in California hospitals from 2011 to 2021. Design, Setting, and Participants: This retrospective cohort study used data from the California Department of Health Care Access and Information and the US Census Bureau to analyze ED facility characteristics from more than 400 general acute care hospitals with more than 320 EDs in California as well as patients who presented to those EDs between January 1, 2011, and December 31, 2021. Main Outcomes and Measures: Linear patterns (measured by percentage change) in total annual ED capacity (volume of hospital beds, EDs, ED treatment stations, and trauma centers) and ED use (ED visits by disposition and acuity) were assessed as primary outcomes. Patterns in ambulance diversion hours and the number of patients who left the ED without being seen were also examined as secondary outcomes. Visit acuity was categorized into 5 levels by increasing severity (minor, low to moderate, moderate, severe without threat, and severe with threat) based on California Department of Health Care Access and Information descriptions corresponding to Current Procedural Terminology codes. Results: In the prepandemic period (2011-2019), the total population of California increased from 37 638 369 to 39 512 223 (5.0%; 95% CI, 4.1%-5.8%), then decreased to 39 237 836 in 2021 (0.7%; 95% CI, -3.9% to 2.5%). Over the entire study period (2011-2021), the total California population increased by 4.2% (95% CI, 3.3%-5.2%). From 2011 to 2019, the annual number of ED visits increased from 12 054 885 to 14 876 653 (23.4%; 95% CI, 20.0%-26.8%) before decreasing to 12 944 692 in 2021 (-13.0%; 95% CI, -33.1% to 7.1%); from 2011 to 2021, total ED visits increased by 7.4% (95% CI, 5.6%-9.1%). From 2011 to 2021, the total number of EDs decreased from 339 to 326 (-3.8%; 95% CI, -4.4% to -3.2%) and the total number of hospital beds decreased from 75 940 to 74 052 (-2.5%; 95% CI, -3.3% to -1.6%), while the number of ED treatment stations in these fewer EDs increased from 7159 to 8667 (21.1%; 95% CI, 19.7%-22.4%). The number of visits rated as severe with threat also increased, from 2 011 637 in 2011 to 3 375 539 in 2021 (67.8%; 95% CI, 59.7%-75.9%), while visits rated as minor decreased from 913 712 to 336 071 (-63.2%; 95% CI, -75.2% to -51.2%) over the same period. Conclusions and Relevance: In this cohort study, multiple measures of ED capacity did not proportionally increase with the increasing demand for services; however, the COVID-19 pandemic appears to have substantially affected some of these patterns. These findings may be helpful to policy makers and health care stakeholders when planning resource allocation of limited health care resources.

Indexed as

COVID-19CaliforniaCohort StudiesEmergency Service, HospitalHumansPandemicsRetrospective Studies

Identifiers

PMID37347481
PMCPMC10288334

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.