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Record W4243038978 · doi:10.21203/rs.2.14367/v1

Understanding health professional role integration in complex adaptive systems A multiple-case study of Physician Assistants in Ontario, Canada

2019· preprint· en· W4243038978 on OpenAlexafffundabout
Kristen Burrows, Julia Abelson, Patricia A. Miller, Mitchell Levine, Meredith Vanstone

Bibliographic record

VenueResearch Square · 2019
Typepreprint
Languageen
FieldHealth Professions
TopicNursing Roles and Practices
Canadian institutionsMcMaster University
FundersGovernment of OntarioMcMaster University
KeywordsComplex adaptive systemHealthcare systemPhysician assistantsPsychologyMedical educationPublic relationsNursingSociologyPolitical scienceHealth careMedicineComputer scienceLawNurse practitionersArtificial intelligence

Abstract

fetched live from OpenAlex

Abstract Background To meet the complex needs of healthcare delivery, the Ministry of Health and Long Term Care (MOHLTC) introduced Physician Assistants (PAs) into the Ontario health care system in 2006 to help increase access to care, decrease wait times, and improve continuity of care. Integration of new health professional roles is often stymied by role resistance and funding barriers. The characterization of healthcare organizations as complex adaptive systems (CAS) may offer insight into the relationships and interactions that optimize and restrict successful PA integration. The aim of this study is to explore the integration of PAs across multiple case settings and to understand the role of PAs within complex adaptive systems.Methods An exploratory, multiple-case study was used to examine PA role integration in four settings: family medicine, emergency, general surgery, and inpatient medicine. Interviews were conducted with 46 healthcare providers and administrators across 13 hospitals and 6 family medicine clinics in Ontario, Canada. Analysis was conducted in three phases: inductive thematic analysis within each of the four cases; a cross-case thematic analysis; and a broader exploration of cross-case patterns pertaining to specific complexity theory principles of interest.Results Support for PA contributions across various health care settings, the importance of role awareness, supervisory relationship attributes, and role vulnerability (in relation to sustainability and funding) are interconnected and dynamic in hospital and community settings. Findings represent the experiences of PAs and other healthcare providers, and demonstrate how the PA’s willingness to work and ability to build relationships within existing health systems allows for the establishment of interprofessional, collaborative, and person-centered care. As a self-organizing agent in complex adaptive systems (i.e. health organizations), PA role exploration revealed patterns of team behavior, non-linear interconnections, open relationships, dynamic systems, and the legacy of role implementation as defined by complexity theory.Conclusions By exploring the role of PAs across multiple sites, the complexity theory lens concurrently fosters an awareness of emerging patterns, relationships and non-linear interactions within the defined context of the Ontario healthcare system. By establishing collaborative, interprofessional care models in community and hospital settings, PAs are making a significant contribution to Ontario healthcare settings.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.902
Threshold uncertainty score0.708

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0250.007
Scholarly communication0.0040.002
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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 head0.485
GPT teacher head0.530
Teacher spread0.045 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2019
Admission routes3
Has abstractyes

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