Evidence map›Paper›PMID 38682441›Full record

Observational studyPopulation health management2024

Association of Timely Outpatient Follow-Up and Readmission Risk in a Mobile Integrated Health Program.

Nicholas Brady, Yuanyuan Liang, Kristin L Seidl, David Marcozzi, Benoit Stryckman, Daniel B Gingold

Abstract readObservational Study
In one paragraph

Observational study in Population health management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Nicholas BradyUniversity of Maryland School of Medicine, Baltimore, Maryland, USA.ORCID 0000-0003-1568-3433
Yuanyuan LiangDepartment of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Kristin L SeidlDepartment of Quality and Safety, University of Maryland Medical Center, Baltimore, USA.
David MarcozziDepartments of Emergency Medicine and Epidemiology, , University of Maryland School of Medicine, Baltimore, Maryland, USA.
Benoit StryckmanDepartment of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Daniel B GingoldDepartment of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland, 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

The objective was to identify medical conditions associated with 30-day readmission, determine patient characteristics for which outpatient follow-up is most associated with reduced readmission, and evaluate how readmission risk changes with time to outpatient follow-up within a mobile integrated health-community paramedicine (MIH-CP) program. This retrospective observational study used data from 1,118 adult patient enrollments in a MIH-CP program operating in Baltimore, Maryland, from May 14, 2018, to December 21, 2021. Bivariate analysis identified chronic disease exacerbations associated with higher 30-day readmission risk. Kaplan-Meier curves and Cox proportional hazard regressions were used to measure how hazard of readmission changes with outpatient follow-up and how that association may vary with other factors. Receiver operating characteristic analysis was used to evaluate how well time to follow-up could predict 30-day readmission. Timely outpatient follow-up was associated with a significant reduction in hazard of readmission for patients aged 50 and younger and for patients with fewer than 5 social determinants of health needs identified. No significant association between readmission and specific chronic disease exacerbations was observed. An optimal follow-up time frame to reduce readmissions could not be identified. Timely outpatient follow-up may be effective for reducing readmissions in younger patients and patients who are less socially complex. Programs and policies aiming to reduce 30-day readmissions may have more success by expanding efforts to include these patients.

Indexed as

Patient ReadmissionAdultAgedBaltimoreDelivery of Health Care, IntegratedFemaleHumansMaleMiddle AgedOutpatientsRetrospective StudiesTime Factorshealth services researchpolicy evaluationprimary carequality improvementutilization

Identifiers

PMID38682441
PMCPMC13175386

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.