Evidence map›Paper›PMID 37681013›Full record

ArticleAnnual IEEE Systems Conference. IEEE Systems Conference2022

Healthcare Quality Improvement: The Need for a Macro-Systems Approach.

Inas S Khayal

Abstract read
In one paragraph

Article in Annual IEEE Systems Conference. IEEE Systems Conference, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

1 author.

Inas S KhayalThe Dartmouth Institute and Biomedical Data Science, Geisel School of Medicine at Dartmouth Department of Computer Science, Dartmouth College, Hanover, NH, USA.

Funding

Translational Engineering in Cancer (TEC)P30CA023108 · NCI · DARTMOUTH COLLEGE · PI Fred W Kolling IV · 1985 to 2026
$91.3M
Empirical Classification of the Typologies of Hospital DeathsR21AG065704 · NIA · DARTMOUTH COLLEGE · PI BARNATO, AMBER E, KHAYAL, INAS S · 2020 to 2021
$451k
NCI NIH HHS P30 CA023108NIA NIH HHS R21 AG065704
6 · The paper itself

Abstract

While the structure of healthcare systems evolved out of the need to address acute conditions, the function of healthcare systems evolved to primarily address chronic conditions. The healthcare delivery system organically developed to respond to "one-off" acute illness or injury. Subsequently, healthcare delivery systems grew into legacy systems that evolved into complex systems over time. Healthcare delivery for acute conditions tends to utilize a specific part or form of the healthcare delivery system. In contrast, healthcare delivery for chronic conditions forces patients to seek care over time between different places or healthcare entities. Because of the self-contained structural organization of these healthcare delivery systems, they were not designed to provide coordinated, integrated, and longitudinal care over time and place. Consequently, today's complex legacy healthcare delivery system requires significant improvement in the quality of care delivered to patients, especially those with chronic conditions. As a complex and legacy system, the most appropriate approach to improve the quality of delivered care is through a re-design quality improvement process, rather than a new system design process. In this paper, we describe the conceptual framework for quality improvement (QI) and the current micro and macro level approaches to quality improvement. We applied the current quality improvement approaches to the QI conceptual framework. We identified the limitations in current quality improvement processes in complex healthcare systems at the macro-level, pointing to the need for macro-systems approaches to healthcare quality improvement.

Indexed as

Complex SystemsDecision-making for Complex SystemsHealthcare SystemsQuality Improvement

Identifiers

PMID37681013
PMCPMC10483430

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.