Evidence map›Paper›PMID 36269531›Full record

ArticleJournal of community health2023

Evaluating Social Determinants of Health in a Mobile Integrated Healthcare-Community Paramedicine Program.

Sean Naimi, Benoit Stryckman, Yuanyuan Liang, Kristin Seidl, Erinn Harris, Colleen Landi, Jessica Thomas, David Marcozzi, Daniel B Gingold

Abstract read
In one paragraph

Article in Journal of community health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Observational
  2. Article
  3. Observational
  4. Article
  5. Observational
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.

Sean NaimiUniversity of Maryland School of Medicine, 620 W Lexington St, Baltimore, MD, 21201, USA. snaimi@som.umaryland.edu.ORCID 0000-0003-4546-715X
Benoit StryckmanDepartment of Emergency Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Yuanyuan LiangDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Kristin SeidlDepartment of Quality and Safety, University of Maryland Medical Center, Baltimore, USA.
Erinn HarrisBaltimore City Fire Department, Baltimore, MD, 21201, USA.
Colleen LandiMobile Integrated Health Community Paramedicine, University of Maryland Medical Center, Baltimore, MD, 21201, USA.
Jessica ThomasBaltimore City Fire Department, Baltimore, MD, 21201, USA.
David MarcozziDepartment of Emergency Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
Daniel B GingoldDepartment of Emergency Medicine, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.

Funding

QAQC Johns Hopkins Institute for Clinical and Translational ResearchUL1TR003098 · NCATS · JOHNS HOPKINS UNIVERSITY · PI FORD, DANIEL ERNEST · 2019 to 2023
$57.7M
NCATS NIH HHS UL1 TR003098
6 · The paper itself

Abstract

In 2018, the University of Maryland Medical Center and the Baltimore City Fire Department implemented a community paramedicine program to help medically or socially complex patients transition from hospital to home and avoid hospital utilization. This study describes how patients' social determinants of health (SDoH) needs were identified, and measures the association between needs and hospital utilization. SDoH needs were categorized into ten domains. Multinomial logistic regression was used to measure association between identified SDoH domains and predicted risk of readmission. Poisson regression was used to measure association between SDoH domains and actual 30-day hospital utilization. The most frequently identified SDoH needs were in the Coordination of Healthcare (37.7%), Durable Medical Equipment (18.8%), and Medication (16.3%) domains. Compared with low-risk patients, patients with an intermediate risk of readmission were more likely to have needs within the Coordination of Healthcare (RRR [95% CI] 1.12 [1.01, 1.24], p = 0.032) and Durable Medical Equipment (RRR = 1.13 [1.00, 1.27], p = 0.046) domains. Patients with the highest risk for readmission were more likely to have needs in the Utilities domain (RRR = 1.76 [0.97, 3.19], p = 0.063). Miscellaneous domain needs, such as requiring a social security card, were associated with increased 30-day hospital utilization (IRR = 1.23 [0.96, 1.57], p = 0.095). SDoH needs within the Coordination of Healthcare, Durable Medical Equipment, and Utilities domains were associated with higher predicted 30-day readmission, while identification documentation and social services needs were associated with actual readmission. These results suggest where to allocate resources to effectively diminish hospital utilization.

Indexed as

Delivery of Health Care, IntegratedParamedicineHumansSocial Determinants of HealthCommunity paramedicineHospital utilizationMobile integrated healthcareSocial determinants of health

Identifiers

PMID36269531
PMCPMC12081202

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.