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Record W2290145698 · doi:10.1377/hlthaff.2015.0133

Private Payers Disagree With Medicare Over Medical Device Coverage About Half The Time

2015· article· en· W2290145698 on OpenAlexaboutno aff
James D. Chambers, Matthew Chenoweth, Teja Thorat, Peter J. Neumann

Bibliographic record

VenueHealth Affairs · 2015
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsMedicaidQuarter (Canadian coin)Actuarial scienceBusinessPrivate insuranceMedical careHealth careMedicineFamily medicineEconomicsEconomic growth

Abstract

fetched live from OpenAlex

There are multiple payers in the US health care system, each making its own coverage determinations for medical technologies. For each of the forty-seven medical devices considered in national coverage determinations (NCDs) of the Centers for Medicare and Medicaid Services (CMS) issued between February 1999 and August 2013, we compared CMS's coverage policy with the policies issued by the largest sixteen private payers that made their decisions publicly available. Overall, we found that NCDs were equivalent to the corresponding private payer policies roughly half of the time, more restrictive approximately a quarter of the time, and less restrictive about a quarter of the time. Our findings indicate that patients may have variable access to medical technology across Medicare and private plans. They also suggest that private plans do not necessarily follow CMS's lead in making coverage decisions.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.943
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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)0.0010.001

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 head0.042
GPT teacher head0.286
Teacher spread0.244 · 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 designNot applicable
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

Citations39
Published2015
Admission routes1
Has abstractyes

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