Evidence map›Paper›PMID 24612854›Full record

ArticleDisaster medicine and public health preparedness2014

Informing the gestalt: an ethical framework for allocating scarce federal public health and medical resources to states during disasters.

Ann R Knebel, Virginia A Sharpe, Marion Danis, Lauren M Toomey, Deborah K Knickerbocker

Abstract read
In one paragraph

Article in Disaster medicine and public health preparedness, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. What Can COVID-19 Teach Us about Using AI in Pandemics?Healthcare (Basel, Switzerland) · 2020
    Article
  4. Review
  5. Article
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

5 authors.

Ann R KnebelNational Institute for Nursing Research, Bethesda, Maryland.
Virginia A SharpeNational Center for Ethics in Health Care, Veterans Health Administration, Washington, DC.
Marion DanisClinical Center Department of Bioethics, National Institutes of Health, Bethesda, Maryland.
Lauren M ToomeyOffice of the Assistant Secretary for Preparedness and Response, Office of Emergency Management, US Department of Health and Human Services, Washington, DC.
Deborah K KnickerbockerOffice of the Assistant Secretary for Preparedness and Response, Office of Emergency Management, US Department of Health and Human Services, Washington, DC.

Funding

Intramural NIH HHS Z99 CL999999
6 · The paper itself

Abstract

During catastrophic disasters, government leaders must decide how to efficiently and effectively allocate scarce public health and medical resources. The literature about triage decision making at the individual patient level is substantial, and the National Response Framework provides guidance about the distribution of responsibilities between federal and state governments. However, little has been written about the decision-making process of federal leaders in disaster situations when resources are not sufficient to meet the needs of several states simultaneously. We offer an ethical framework and logic model for decision making in such circumstances. We adapted medical triage and the federalism principle to the decision-making process for allocating scarce federal public health and medical resources. We believe that the logic model provides a values-based framework that can inform the gestalt during the iterative decision process used by federal leaders as they allocate scarce resources to states during catastrophic disasters.

Indexed as

Decision MakingDisastersPublic HealthDisaster PlanningFederal GovernmentHealth Care RationingHealth Services Needs and DemandHumansResource AllocationState GovernmentVulnerable Populations

Identifiers

PMID24612854
PMCPMC5549946

What OpenQuestion holds

Textmetadata
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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.