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Record W3121616721 · doi:10.55016/ojs/sppp.v6i1.42440

Accountability by Design: Moving Primary Care Reform Ahead in Alberta

2013· article· en· W3121616721 on OpenAlexaffabout
Shannon Spenceley, Cheryl Andres, Janet Lapins, Robert Wedel, Tobias Gelber, Lisa Halma

Bibliographic record

VenueThe School of Public Policy Publications · 2013
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsChinook Regional HospitalAlberta Health ServicesUniversity of Lethbridge
Fundersnot available
KeywordsAccountabilityPrimary careBusinessPublic administrationPolitical scienceMedicineFamily medicine

Abstract

fetched live from OpenAlex

Health-care reform is perennially popular in Alberta, but reality doesn’t match the rhetoric. Government has invested more than $700 million in Primary Care Networks — with little beyond anecdotal evidence of the value achieved with this investment. As the province redirects primary care to Family Care Clinics, the authors assert that simply tinkering with one part of the system is not the answer: health care must change on a system-wide basis. Drawing on the experiences of frontline staff and a rich body of literature, the authors present their vision for integrated team-based primary care, designed to be accountable to meet the needs of populations. This will require governance that makes primary care the hub of the system, and brings together government and health-services leadership to support the integration of primary and specialty care. There are shared accountabilities for achieving primary care that exhibits the attributes of high performing primary care systems, and these exist at multiple levels, from individuals seeking primary care, up to and including government. The authors make these accountabilities explicit, and outline strategies to secure their achievement that include system redesign, service delivery redesign and payment reform. All of this demands whole-system reform focused on primary care, and it won’t be easy. There are plenty of vested interests at stake, and a truly transformative vision requires buy-in at every level. However, Alberta’s rapidly growing and aging population makes it more urgent than ever to realize such a vision. This paper offers guidelines to spark the fresh thinking required.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.075
GPT teacher head0.409
Teacher spread0.334 · 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; both teacher heads agree on what is shown here.

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

Citations14
Published2013
Admission routes2
Has abstractyes

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