Evidence map›Paper›PMID 39391571›Full record

ArticleCHEST pulmonary2024

A Qualitative Study Identifying the Potential Risk Mechanisms Leading to Hospitalization for Patients With Chronic Lung Disease.

Gary E Weissman, Jasmine A Silvestri, Folasade Lapite, Isabelle S Mullen, Nicholas S Bishop, Tyler Kmiec, Amy Summer, Michael W Sims, Vivek N Ahya, Shreya Kangovi and 3 more

Abstract read
In one paragraph

Article in CHEST pulmonary, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Gary E WeissmanPalliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA; Pulmonary, Allergy, and Critical Care Division, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA.
Jasmine A SilvestriPalliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA.
Folasade LapiteTulane University School of Medicine, New Orleans, LA.
Isabelle S MullenPerelman School of Medicine, University of Pennsylvania, Philadelphia, PA.
Nicholas S BishopPalliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA.
Tyler KmiecPalliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA.
Amy SummerPalliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA.
Michael W SimsPulmonary, Allergy, and Critical Care Division, University of Pennsylvania, Philadelphia, PA.
Vivek N AhyaPulmonary, Allergy, and Critical Care Division, University of Pennsylvania, Philadelphia, PA.
Shreya KangoviLeonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA; Division of General Internal Medicine, University of Pennsylvania, Philadelphia, PA; Penn Center for Community Health Workers, University of Pennsylvania, Philadelphia, PA.
Tamar A KlaimanPalliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA.
Julia E SzymczakDivision of Epidemiology, University of Utah School of Medicine, Salt Lake City, UT; Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT.
Joanna L HartPalliative and Advanced Illness Research (PAIR) Center, University of Pennsylvania, Philadelphia, PA; Pulmonary, Allergy, and Critical Care Division, University of Pennsylvania, Philadelphia, PA; Leonard Davis Institute of Health Economics, University of Pennsylvania, Philadelphia, PA; Center for Health Incentives and Behavioral Economics, University of Pennsylvania, Philadelphia, PA; Department of Medical Ethics and Health Policy, University of Pennsylvania, Philadelphia, PA.

Funding

Using natural language processing and machine learning to identify potentially preventable hospital admissions among outpatients with chronic lung diseasesK23HL141639 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI WEISSMAN, GARY · 2018 to 2022
$933k
NHLBI NIH HHS K23 HL141639
6 · The paper itself

Abstract

backgroundCare management programs for chronic lung disease attempt to reduce hospitalizations, yet have not reliably achieved this goal. A key limitation of many programs is that they target patients with characteristics associated with hospitalization risk, but do not specifically modify the mechanisms that lead to hospitalization. RESEARCH QUESTION: What are the common mechanisms underlying known patient-level risk characteristics leading to hospitalizations for acute exacerbations of chronic lung disease? STUDY DESIGN AND

methodsWe conducted a qualitative study of patients admitted to the University of Pennsylvania Health System with acute exacerbations of chronic lung disease between January and September 2019. We interviewed patients, their family caregivers, and their inpatient and outpatient clinicians about experiences leading up to the hospitalization. We analyzed the interview transcripts using triangulation and abductive analytic methods.

resultsWe conducted 69 interviews focused on the admission of 22 patients with a median age of 66 years (interquartile range, 60-70 years), of whom 16 patients (73%) were female and 14 patients (64%) were Black. We interviewed 22 patients, 14 caregivers, 19 inpatient clinicians, and 14 outpatient clinicians. We triangulated the available interview data for each patient admission and identified the underlying mechanisms of how several known patient characteristics associated with risk actually led to hospitalization. These mechanisms included limited capacity for home management of acute symptom changes, barriers to accessing care, chronic functional limitations, and comorbid behavioral health disorders. Importantly, many of the clinical, social, and behavioral mechanisms underlying hospitalizations were present for months or years before the symptoms that prompted inpatient care.

interpretationCare management programs should be built to target specific clinical, social, and behavioral mechanisms that directly lead to hospitalization. Upstream interventions that reduce hospitalization risk are possible given that many contributory mechanisms are present for months or years before the onset of acute exacerbations.

Indexed as

acute care utilizationChronic lung diseaserisk factorsrisk mechanisms

Identifiers

PMID39391571
PMCPMC11465817

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.