Evidence map›Paper›PMID 27601514›Full record

ArticleJournal of oncology practice2016

No Exit: Identifying Avoidable Terminal Oncology Intensive Care Unit Hospitalizations.

Bobby Daly, Andrew Hantel, Kristen Wroblewski, Jay S Balachandran, Selina Chow, Rebecca DeBoer, Gini F Fleming, Olwen M Hahn, Justin Kline, Hongtao Liu and 7 more

Abstract read
In one paragraph

Article in Journal of oncology practice, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Article
  3. Surgical Treatment Intensity at the End of Life in Patients With Cancer: A Systematic Review.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024
    Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. 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

17 authors.

Bobby DalyUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Andrew HantelUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Kristen WroblewskiUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Jay S BalachandranUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Selina ChowUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Rebecca DeBoerUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Gini F FlemingUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Olwen M HahnUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Justin KlineUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Hongtao LiuUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Bhakti K PatelUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Anshu VermaUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Leah J WittUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Mayumi FukuiUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Aditi KumarUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Michael D HowellUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.
Blase N PoliteUniversity of Chicago Medicine; and University of Chicago, Chicago, IL.

Funding

Training of Junior Faculty for Careers in Omics of Lung DiseasesK12HL119995 · NHLBI · UNIVERSITY OF CHICAGO · PI GOZAL, DAVID, GROSSMAN, ROBERT L. · 2013 to 2017
$1.3M
NHLBI NIH HHS K12 HL119995
6 · The paper itself

Abstract

purposeTerminal oncology intensive care unit (ICU) hospitalizations are associated with high costs and inferior quality of care. This study identifies and characterizes potentially avoidable terminal admissions of oncology patients to ICUs.

methodsThis was a retrospective case series of patients cared for in an academic medical center's ambulatory oncology practice who died in an ICU during July 1, 2012 to June 30, 2013. An oncologist, intensivist, and hospitalist reviewed each patient's electronic health record from 3 months preceding terminal hospitalization until death. The primary outcome was the proportion of terminal ICU hospitalizations identified as potentially avoidable by two or more reviewers. Univariate and multivariate analysis were performed to identify characteristics associated with avoidable terminal ICU hospitalizations.

resultsSeventy-two patients met inclusion criteria. The majority had solid tumor malignancies (71%), poor performance status (51%), and multiple encounters with the health care system. Despite high-intensity health care utilization, only 25% had documented advance directives. During a 4-day median ICU length of stay, 81% were intubated and 39% had cardiopulmonary resuscitation. Forty-seven percent of these hospitalizations were identified as potentially avoidable. Avoidable hospitalizations were associated with factors including: worse performance status before admission (median 2 v 1; P = .01), worse Charlson comorbidity score (median 8.5 v 7.0, P = .04), reason for hospitalization (P = .006), and number of prior hospitalizations (median 2 v 1; P = .05).

conclusionGiven the high frequency of avoidable terminal ICU hospitalizations, health care leaders should develop strategies to prospectively identify patients at high risk and formulate interventions to improve end-of-life care.

Indexed as

AgedFemaleHealth Services MisuseHospitalizationHumansIntensive Care UnitsMaleMiddle AgedNeoplasmsTerminal Care

Identifiers

PMID27601514
PMCPMC5063186

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.