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Record W2055273431 · doi:10.1359/jbmr.081116

Bridging the Osteoporosis Quality Chasm

2008· article· en· W2055273431 on OpenAlexaff
Jeffrey R. Curtis, Jonathan D. Adachi, Kenneth G. Saag

Bibliographic record

VenueJournal of Bone and Mineral Research · 2008
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineOsteoporosisQuality managementHealth careQuality assuranceQuality (philosophy)PopulationFamily medicineGerontologyEnvironmental healthBusinessMarketingService (business)

Abstract

fetched live from OpenAlex

The persistent chasm between best evidence and best practices in osteoporosis is an international phenomenon. There is considerable evidence that individuals in many developed nations who experience a fragility fracture are not receiving adequate osteoporosis management. Among these persons, many go on to experience subsequent fractures, and many have never been told they may have osteoporosis, let alone been tested or treated. Efforts to improve quality of care in osteoporosis are predicated on first defining the term “quality.” In the United States and internationally, many groups have established quality metrics, often referred to as performance measures or quality indicators. When properly constructed, these metrics represent minimal acceptable standards of care that can be used by physicians and health plans to establish and monitor quality. Most performance measures focus on the process of care. Process measures are used preferentially because they are evidence based, actionable, measurable, and do not need to account for compliance and other patient characteristics that may influence actual health outcomes. As shown in Table 1, performance measures contain a denominator expressing the at risk population (i.e., number of women over the age of 65) and a numerator (i.e., the number of women who have received either a BMD test or an anti‐osteoporotic therapy). In the United States, the National Committee on Quality Assurance (NCQA), which devises the Healthcare Effectiveness Data and Information Set (HEDIS) quality measures,(1) first implemented an osteoporosis performance measure in 2003. The HEDIS measures assess the performance of the majority of U.S. health plans. The osteoporosis HEDIS measure defines the proportion of women ≥67 yr of age with a new fracture who received either a BMD test or prescription treatment for osteoporosis within 6 mo of their fracture. Other groups including the American Medical Association Physician Consortium for Performance Improvement and the Joint Commissions also have established osteoporosis performance measures. These added measures include evaluation for secondary osteoporosis, education regarding calcium and vitamin D supplementation, physical activity and fall risk assessment, continuity of care, monitoring, and recommendations on appropriate timing of pharmacotherapy.(1,2)

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.120
metaresearch head score (Gemma)0.226
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.120
Threshold uncertainty score0.635

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1200.226
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0100.009
Science and technology studies0.0080.018
Scholarly communication0.0250.023
Open science0.0050.037
Research integrity0.0140.025
Insufficient payload (model declined to judge)0.0200.003

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 head0.159
GPT teacher head0.435
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations33
Published2008
Admission routes1
Has abstractyes

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