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Record W3112152134 · doi:10.7759/cureus.12146

Quality Improvement Focused Morbidity and Mortality Rounds: An Integrative Review

2020· review· en· W3112152134 on OpenAlexaff
K. Churchill, Justin R. Murphy, Nick Smith

Bibliographic record

VenueCureus · 2020
Typereview
Languageen
FieldHealth Professions
TopicPatient Safety and Medication Errors
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPatient safetyMedicineMEDLINEQuality (philosophy)RestructuringQuality managementEnglish languageAlternative medicineMedical educationPsychologyHealth carePathologyPolitical scienceEngineeringOperations management

Abstract

fetched live from OpenAlex

Morbidity and mortality conference (MMC) is a century-old tradition in medicine that was initially primarily focused on the review of surgical outcomes and errors. In recent years, the value of MMC in quality improvement (QI) and patient safety initiatives has been realized and incorporated into the MMCs of some disciplines and institutions. Despite this, there is a need for a standardized structure of MMC that emphasizes both QI and patient safety. The purpose of this integrative review is to synthesize the literature on MMC structure that is reflective of QI and patient safety. An integrative literature search was carried out using PubMed and MEDLINE. Abstracts were reviewed and non-relevant articles were excluded. Exclusion criteria were no mention of MMC, analysis of specific case, no focus on QI or patient safety, and non-English language. A total of 21 articles were identified for review. Articles were reviewed in their entirety for content regarding structuring of the MMC to reflect and further develop QI and patient safety. The follwing three themes emerged that were consistently identified as being important for restructuring MMCs: (1) the importance of careful case selection, (2) the format of discussion during the conferences, and (3) the action plans reflecting QI initiatives derived from the conferences. The review suggests that one standardized method of MMC implementation that encompasses the three pivotal themes should be developed. Further research needs to focus on instituting measures of effectiveness for the new MMC model.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.341
GPT teacher head0.563
Teacher spread0.223 · 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 designNot applicable
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

Citations19
Published2020
Admission routes1
Has abstractyes

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