Evidence map›Paper›PMID 25846533›Full record

ReviewChest2015

ICU director data: using data to assess value, inform local change, and relate to the external world.

David J Murphy, Ogbonna C Ogbu, Craig M Coopersmith

Abstract readReview
In one paragraph

Review in Chest, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 2 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

11 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. [S3 Guideline Sepsis-prevention, diagnosis, therapy, and aftercare : Long version].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2020
    Guideline
  2. Guideline
  3. Article
  4. Article
  5. Development and validation of a deep learning model to predict the survival of patients in ICU.Journal of the American Medical Informatics Association : JAMIA · 2022
    Article
  6. Article
  7. Observational
  8. Article
  9. Article
  10. Review
  11. 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

3 authors.

David J MurphyEmory Critical Care Center, Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Atlanta, GA; Department of Surgery, Atlanta, GA. Electronic address: david.j.murphy@emory.edu.
Ogbonna C OgbuEmory Critical Care Center, Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Atlanta, GA; Department of Surgery, Atlanta, GA.
Craig M CoopersmithEmory Critical Care Center, Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Atlanta, GA; Emory University School of Medicine, Atlanta, GA.

Funding

Critical Care Training ProgramT32GM095442 · NIGMS · EMORY UNIVERSITY · PI Craig M Coopersmith · 2011 to 2026
$4.7M
NIGMS NIH HHS GM095442NIGMS NIH HHS T32 GM095442
6 · The paper itself

Abstract

Improving value within critical care remains a priority because it represents a significant portion of health-care spending, faces high rates of adverse events, and inconsistently delivers evidence-based practices. ICU directors are increasingly required to understand all aspects of the value provided by their units to inform local improvement efforts and relate effectively to external parties. A clear understanding of the overall process of measuring quality and value as well as the strengths, limitations, and potential application of individual metrics is critical to supporting this charge. In this review, we provide a conceptual framework for understanding value metrics, describe an approach to developing a value measurement program, and summarize common metrics to characterize ICU value. We first summarize how ICU value can be represented as a function of outcomes and costs. We expand this equation and relate it to both the classic structure-process-outcome framework for quality assessment and the Institute of Medicine's six aims of health care. We then describe how ICU leaders can develop their own value measurement process by identifying target areas, selecting appropriate measures, acquiring the necessary data, analyzing the data, and disseminating the findings. Within this measurement process, we summarize common metrics that can be used to characterize ICU value. As health care, in general, and critical care, in particular, changes and data become more available, it is increasingly important for ICU leaders to understand how to effectively acquire, evaluate, and apply data to improve the value of care provided to patients.

Indexed as

Health ResourcesData CollectionDelivery of Health CareHumansIntensive Care UnitsUnited States

Identifiers

PMID25846533
PMCPMC4388121

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.