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Record W2890769876 · doi:10.1377/hlthaff.2018.0372

Evaluation Of The Behavioral Health Integration And Complex Care Initiative In Medi-Cal

2018· article· en· W2890769876 on OpenAlexaff
Todd Gilmer, Marc Avery, Elizabeth Siantz, Benjamin F. Henwood, Elise Pomerance, Jennifer N. Sayles

Bibliographic record

VenueHealth Affairs · 2018
Typearticle
Languageen
FieldMedicine
TopicChronic Disease Management Strategies
Canadian institutionsKimberly-Clark (Canada)
Fundersnot available
KeywordsStaffingGeneral partnershipHealth careChronic careIntegrated careNursingMedicineMultiple Chronic ConditionsBusinessFamily medicineChronic diseasePolitical science

Abstract

fetched live from OpenAlex

This article reports how a large Medi-Cal managed care plan addressed challenges in accessing health care for approximately 7,000 enrollees with multiple chronic conditions through a project known as the Behavioral Health Integration and Complex Care Initiative. The initiative increased staffing for care management, care coordination, and behavioral health integration. In our evaluation of the initiative, we demonstrated that participation in it was associated with improved clinical indicators for common chronic conditions, reduced inpatient costs in some sites, and improved patient experience in all sites. The initiative may be best understood as a new type of ongoing strategic partnership among the health plan, its providers, and their patients. Changes in funding to support models of value-based care are needed to sustain these efforts in the long term.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.787
Threshold uncertainty score0.575

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.209
GPT teacher head0.465
Teacher spread0.257 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations13
Published2018
Admission routes1
Has abstractyes

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