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Record W4410711871 · doi:10.1136/bmjqs-2025-018519

Metrics used in quality improvement publications addressing environmental sustainability in healthcare: a scoping review

2025· review· en· W4410711871 on OpenAlexaff
Colin Sue‐Chue‐Lam, Sezgi Yanikomeroglu, Darius Baginskis, Doulia Hamad, Brian M. Wong, Nicole Simms, Karen Born

Bibliographic record

VenueBMJ Quality & Safety · 2025
Typereview
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentrePublic Health OntarioUniversity of Toronto
Fundersnot available
KeywordsSustainabilityCINAHLScopusMedicineSustainability reportingMEDLINEHealth careMetric (unit)Environmental resource managementEnvironmental healthPsychological interventionNursingBusinessPolitical scienceEnvironmental scienceEcology

Abstract

fetched live from OpenAlex

OBJECTIVE: Quality improvement (QI) practices and scholarship are increasingly concerned with environmental sustainability given the negative health outcomes caused by the ecological crisis, as well as the environmental impacts of healthcare delivery itself. A core component of QI activities is measuring change. How sustainability metrics have been used in QI is unclear. We conducted a scoping review of metrics used in published sustainability-focused QI initiatives. DATA SOURCES: MEDLINE, EMBASE, CINAHL and Scopus from 2000 to 2023. ELIGIBILITY CRITERIA: Published healthcare QI initiatives intended to address environmental sustainability with at least one quantitative sustainability metric. DATA ANALYSIS: Publication, study, measurement and QI intervention characteristics were charted from included studies. Data items were synthesised and presented narratively as well as quantitatively. RESULTS: We screened 6294 studies and included 90 full-text publications. The studies were published from 2000 to 2023, with the majority (61%, 55/90) published since 2020. Publications originated from a wide range of clinical disciplines with most QI projects situated in the inpatient setting (78%, 70/90). Environmental sustainability metrics were subcategorised into activity data and environmental impact indicators. Some papers included more than one category of activity data, with the most common being cost (88%, 79/90), hospital waste (52%, 47/90), anaesthetic gases (49%, 44/90), disposable use (24%, 22/90) and distance travelled (14%, 13/90). Fewer publications included environmental impact indicators, with global warming potential dominating this category (53%, 48/90). DISCUSSION: There is a need to align QI efforts with environmental sustainability. However, there is limited guidance specific to healthcare QI on how to measure environmental impacts of these efforts. This review illuminates that sustainability-focused QI efforts to date have used a relatively narrow set of sustainability metrics. QI scholars and practitioners can benefit from further education, measurement frameworks and guidelines to effectively incorporate environmental sustainability metrics into QI efforts.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.019
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.694
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0190.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.003
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.312
GPT teacher head0.542
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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