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Record W4386562663 · doi:10.12927/hcpol.2023.27152

Productivity Decline or Administrative Avalanche? Examining Factors That Shape Changing Workloads in Primary Care

2023· article· en· W4386562663 on OpenAlexaffvenueabout
Ruth Lavergne, Sandra Peterson, David Rudoler, Ian Scott, Rita McCracken, Goldis Mitra, Alan Katz

Bibliographic record

VenueHealthcare policy · 2023
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of British ColumbiaUniversity of ManitobaCentre for Advancing Health OutcomesOntario Shores Centre for Mental Health SciencesDalhousie University
Fundersnot available
KeywordsWorkloadMedicinePer capitaReceiptPopulationProductivityEmergency departmentService delivery frameworkService (business)Family medicineMedical emergencyEmergency medicineNursingEnvironmental healthBusiness

Abstract

fetched live from OpenAlex

Background: In Canada, family physicians (FPs) per capita have increased but so have access challenges. We explored changes in population characteristics, service delivery and FP practice that may help understand these trends. Methods: We used linked administrative data in British Columbia to describe changes in patient ages and comorbidities, hospitalizations and receipt of services that may require FP coordination, review and/or follow-up: prescriptions dispensed, laboratory tests, diagnostic imaging (radiology and ultrasound), specialist visits and emergency department visits. We estimate the number of FPs delivering community-based comprehensive care and report changes in service volume per community-based FP visit. Results: Between 1999/2000 and 2017/2018, people experienced fewer days in hospital, but the number of treated comorbidities, day surgeries and other services requiring FP coordination increased over and above the expected levels attributed to population aging. While the total number of FPs per capita have increased, numbers in community-based care have not and visits per physician have fallen. Increases in services that may involve FP coordination per community-based FP visit ranged from 32.2% for diagnostic radiology to 122.1% for lab tests. Conclusion: Findings suggest substantially increased coordination workload per FP visit. Ongoing impacts of population aging and changing service delivery on primary care workload require further examination.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.295
GPT teacher head0.500
Teacher spread0.204 · 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 designObservational
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".

Quick stats

Citations12
Published2023
Admission routes3
Has abstractyes

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