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Record W1994562652 · doi:10.1377/hlthaff.2011.1332

In A California Program, Quality And Utilization Reports On Reproductive Health Services Spurred Providers To Change

2012· article· en· W1994562652 on OpenAlexaff
Leslie A. Watts, Heike Thiel de Bocanegra, Philip D. Darney, Denis Hulett, Michael Howell, John Mikanda, Regina Zerne, Michael S. Policar

Bibliographic record

VenueHealth Affairs · 2012
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsSaskatchewan Health
Fundersnot available
KeywordsMedicaidFamily planningReproductive healthService providerBusinessPublic healthProgram evaluationQuality (philosophy)Health careQuality managementEnvironmental healthMedicineService (business)NursingEconomic growthPopulationMarketing

Abstract

fetched live from OpenAlex

The use of performance indicators has the potential to improve service quality and avert costs, yet such indicators have typically not been used to assess family planning and reproductive health services. An exception is California's Family PACT (Planning, Access, Care, and Treatment) Program, a statewide family planning and reproductive health services program. Our study assessed whether the behavior of providers participating in this program was influenced by performance reports that used both quality improvement and utilization management indicators. We examined three indicators in each category from 2005 to 2009 and found that change occurred in five of six indicators among private providers and in three of six indicators among public providers. Chlamydia screening rates in women age twenty-five and younger, for example, increased significantly among both private and public providers. Despite the challenges enumerated in this article, we conclude that the methodology used in the program could serve as a starting point for the development of a uniform set of provider-focused reproductive health quality and utilization reports that could be instituted by state family planning programs, state Medicaid programs and health plans, and other health care delivery systems.

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)0.006
metaresearch head score (Gemma)0.000
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: none
Teacher disagreement score0.590
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.199
GPT teacher head0.514
Teacher spread0.315 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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