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Record W2911745223

THE ECOLOGY OF CLINICAL DECISION MAKING

2019· dissertation· en· W2911745223 on OpenAlexfundaboutno aff
Veena Manja

Bibliographic record

VenueMacSphere (McMaster University) · 2019
Typedissertation
Languageen
FieldMedicine
TopicMedical and Biological Sciences
Canadian institutionsnot available
FundersCanadian Cardiovascular Society
KeywordsEcologyGeographyBiology
DOInot available

Abstract

fetched live from OpenAlex

Despite substantial healthcare costs, patient outcomes are sub-optimal in the United States and Canada compared to other countries that spend proportionally less on healthcare. This has led to recognition of the need to improve healthcare value, utilization of tools including clinical practice guidelines and development of initiatives such as the Choosing Wisely Campaign to achieve this goal. In spite of the intuitive appeal of these interventions designed to increase physician awareness of evidence and empower patients to engage in shared decision-making, they have had limited success in changing practice and physician prescribing behaviours. Using a mixed-methods approach, this thesis represents a purposeful attempt to understand the failure of existing approaches through an examination of the factors that influence clinical decision making. Specifically, the thesis integrates quantitative and qualitative methodologies to develop a deeper understanding of clinical decision-making. Consisting of a clinical vignette based survey, the quantitative study explores decision-making in four specific commonly encountered case contexts. After choosing the preferred management option, participants rated the influence of different factors on their decisions. Follow-up questions explored knowledge, attitudes and practices regarding incorporating cost considerations into decision-making. The results of the study were explored further in the qualitative component of the mixed study. The results indicate that clinical decision-making is influenced by an interrelated set of socioecological factors with evidence and clinical practice guidelines playing a secondary role. Because lack of knowledge is not a major factor in guideline discordant care, strategies to improve knowledge will have minimal effect in improving care. The qualitative study included an inquiry into the need for teaching and learning on the topic of cost and cost-effectiveness and sought input from physicians working in diverse settings on methods and topics that need to be included in medical education. The contributions of this thesis include a deeper understanding of the factors that influence clinical decision-making and suggestions for enhancing medical education.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.955
Threshold uncertainty score0.956

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0450.000

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 head0.038
GPT teacher head0.318
Teacher spread0.280 · 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 designOther design
Domainnot available
GenreOther

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

Citations1
Published2019
Admission routes2
Has abstractyes

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