Evidence map›Paper›PMID 41735019›Full record

ArticleCancer medicine2026

Hospitalist Care for Unplanned Oncology Admissions: A Mixed-Method Analysis of Oncology and General Hospitalist Outcomes and Processes.

Megan A Mullins, Sanah Ladhani, Abril Carrillo, Emily C Repasky, Michael Wu, Bella Etingen, Emre Tarhan, Navid Sadeghi, Jason B Fleming, Suzanne D Conzen and 1 more

Abstract read
In one paragraph

Article in Cancer medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

11 authors.

Megan A MullinsDepartment of Health Economics, Systems, and Policy, Peter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0003-2753-9068
Sanah LadhaniDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0003-1080-2800
Abril CarrilloDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Emily C RepaskyPeter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0002-5714-6540
Michael WuDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Bella EtingenPeter O'Donnell Jr. School of Public Health, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Emre TarhanDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Navid SadeghiDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.ORCID https://orcid.org/0000-0002-7786-8786
Jason B FlemingDepartment of Surgical Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Suzanne D ConzenDivision of Hematology and Oncology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Arthur S HongDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.

Funding

National Center for Advancing Translational Sciences of the National Institutes of Health UL1TR003163Texas Health Resources Clinical Scholar Award
6 · The paper itself

Abstract

purposeTo compare patient outcomes across oncology hospitalist (OH) and general hospitalist (GH) teams and understand related team practices.

methodsUsing an explanatory sequential mixed-methods design, we compared unplanned inpatient admissions to the GH or OH teams at our academic medical center between 2018 and 2022 using propensity-score matching to balance characteristics across teams. Primary outcomes included outpatient oncology follow-up, 30-day readmission, and discharge to hospice. Outcomes were modeled with multivariable logistic regression, adjusted for age, race, and comorbidity. We conducted semi-structured interviews with OH (n = 6), GH (n = 7), and oncology consult team (n = 4) clinicians. Themes were identified through rapid qualitative analysis and consensus discussions between two qualitative researchers.

resultsThe matched sample included 1082 GH and 361 OH team admissions. Median length of stay was 5 days (IQR 3,8) for GH and 6 days for OH (IQR 4, 10) (p < 0.01). The OH team had higher adjusted odds of discharge to hospice (aOR: 1.9, 95% CI: 1.1-3.5), outpatient oncology follow-up within 30 days (aOR: 4.2, 95% CI: 3.1-5.6), but also 30-day readmissions (aOR: 1.8, 95% CI: 1.3-2.5) compared to the GH team. The OH team communicated directly with outpatient oncology throughout hospitalizations and sent discharge summaries with follow-up recommendations. In contrast, the GH team relied on the consulting oncology team to communicate with outpatient oncologists and had variable follow-up practices.

conclusionEngagement with outpatient oncologists throughout patient admissions may contribute to more effective discharge planning. Inpatient teams can use this strategy to help improve hospital transitions of care for patients with cancer.

Indexed as

HospitalistsMedical OncologyNeoplasmsAgedFemaleHospitalizationHumansLength of StayMaleMiddle AgedPatient AdmissionPatient Care TeamPatient DischargePatient Readmissionmixed‐methodsoncology hospitalistoutpatientteam communicationteaming

Identifiers

PMID41735019
PMCPMC12932068

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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.