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Record W2593938545 · doi:10.1111/1475-6773.12674

The Reduction in <scp>ED</scp> and Hospital Admissions in Medical Home Practices Is Specific to Primary Care–Sensitive Chronic Conditions

2017· article· en· W2593938545 on OpenAlex
Lee A. Green, Hsiu‐Ching Chang, Amanda R. Markovitz, Michael L. Paustian

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHealth Services Research · 2017
Typearticle
Languageen
FieldHealth Professions
TopicPrimary Care and Health Outcomes
Canadian institutionsUniversity of Alberta
FundersAgency for Healthcare Research and Quality
KeywordsMedicineMedical homePrimary careObservational studyEmergency departmentEmergency medicineFamily medicineInternal medicineNursing

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether the Patient-Centered Medical Home (PCMH) transformation reduces hospital and ED utilization, and whether the effect is specific to chronic conditions targeted for management by the PCMH in our setting. DATA SOURCES AND STUDY SETTING: All patients aged 18 years and older in 2,218 primary care practices participating in a statewide PCMH incentive program sponsored by Blue Cross Blue Shield of Michigan (BCBSM) in 2009-2012. STUDY DESIGN: Quantitative observational study, jointly modeling PCMH-targeted versus other hospital admissions and ED visits on PCMH score, patient, and practice characteristics in a hierarchical multivariate model using the generalized gamma distribution. DATA COLLECTION: Claims data and PCMH scores held by BCBSM. PRINCIPAL FINDINGS: Both hospital and ED utilization were reduced proportionately to PCMH score. Hospital utilization was reduced by 13.9 percent for PCMH-targeted conditions versus only 3.8 percent for other conditions (p = .003), and ED utilization by 11.2 percent versus 3.7 percent (p = .010). Hospital PMPM cost was reduced by 17.2 percent for PCMH-targeted conditions versus only 3.1 percent for other conditions (p < .001), and ED PMPM cost by 9.4 percent versus 3.6 percent (p < .001). CONCLUSIONS: PCMH transformation reduces hospital and ED use, and the majority of the effect is specific to PCMH-targeted conditions.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.419
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0080.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.003
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 head0.084
GPT teacher head0.528
Teacher spread0.445 · 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