MétaCan
Menu
Back to cohort
Record W2908030200 · doi:10.1017/s0266462318000922

OP35 Integrated Knowledge Translation In Policy Development

2018· article· en· W2908030200 on OpenAlexaboutno aff
Glenna Laing, Rume Djebah, Judy Hoff, Robert W. Shaffer, Sheila Rutledge Harding, Carmen Moga, Stefanie Kletke, Ann Scott

Bibliographic record

VenueInternational Journal of Technology Assessment in Health Care · 2018
Typearticle
Languageen
FieldMedicine
TopicBiomedical Ethics and Regulation
Canadian institutionsnot available
Fundersnot available
KeywordsBenchmarkingGuidelineReimbursementMedicineMultidisciplinary approachKnowledge translationHealth technologyBusinessHealth careFamily medicinePolitical scienceKnowledge managementComputer scienceMarketing

Abstract

fetched live from OpenAlex

Introduction: Immune globulin (IG) is a publicly funded blood product with high utilization rates and rapidly rising costs. Inappropriate use of IG, particularly in dose and treatment duration, is observed in about 10 percent of cases, and the national guidelines for IG treatment are outdated. To develop a utilization management policy for IG, the Alberta, Manitoba and Saskatchewan Ministries of Health collaborated with health technology assessment (HTA) researchers and clinicians to develop evidence-based guideline recommendations for IG treatment to inform an authorization policy for IG utilization in the provinces. Methods: A multidisciplinary committee comprising HTA researchers and 22 physicians from seven medical specialties adapted recommendations from 43 “seed” guidelines into one locally contextualized IG guideline. HTA methods and rapid review products were used extensively to update gaps in the evidence base. The guideline recommendation document was used to develop a provincial IG utilization management policy. The challenges of achieving a methodologically rigorous guideline development process will be discussed. Results: The guideline contained over 60 recommendations for IG use in different medical specialties. The health ministries used the guideline recommendations to develop an IG authorization policy. The clinician-sanctioned review criteria were used to construct a conditional reimbursement system for generating outcome data from controlled off-label IG use for conditions where evidence gaps existed, and were built into policies for benchmarking compliance. Conclusions: Three provinces successfully collaborated to develop an IG utilization management policy. The unique approach involved a credible and transparent process that incorporated key review elements for compliance benchmarking and reimbursement, promoted clinician buy-in, and created a cadre of clinical champions willing to assist in policy development and implementation. The proactive, rather than retroactive, incorporation of clinician-sanctioned benchmarking and review criteria into policy will help bridge the know-do gap and foster a stronger, more direct link between health policy and evidence.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.955
Threshold uncertainty score0.608

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.043
GPT teacher head0.465
Teacher spread0.422 · 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 designOther design
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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Technology Assessment in Health CareSame topicBiomedical Ethics and RegulationFrench-language works237,207