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Record W3212550404 · doi:10.1182/blood-2021-146171

Guiding the Standardization in Acute Leukemia Service Delivery through the Development of Organizational Requirements

2021· article· en· W3212550404 on OpenAlexaffabout
Cassandra McKay, C. Tom Kouroukis, Sherrie Hertz, Rena Buckstein, Kardi Kennedy, Lia I. T. Kutzscher, Janet MacEachern, Mary Catherine McCann, Mitchell Sabloff, Karen Yee, Suzanna Apostolovski, Amanda Wong, Christopher Bredeson

Bibliographic record

VenueBlood · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health NetworkHealth Sciences CentreWindsor Regional HospitalOttawa HospitalKingston Health Sciences CentreUniversity of OttawaJuravinski Cancer CentreVictoria HospitalSunnybrook Health Science CentreGrand River HospitalLondon Health Sciences CentreCancer Care Ontario
Fundersnot available
KeywordsService delivery frameworkBusinessGovernment (linguistics)MedicineBest practiceHealth carePopulationService (business)Public relationsEconomic growthPolitical scienceMarketingEnvironmental health

Abstract

fetched live from OpenAlex

Abstract Introduction: In Ontario, Canada, acute leukemia (AL) care is delivered to patients at three levels of specialized service provider sites: 1) Transplant and AL Service Sites, providing all services, including stem cell transplant, chimeric antigen receptor T-cell therapy, and high intensity chemotherapy (e.g., induction); 2) AL Service Sites, providing a subset of services, including high intensity chemotherapy; and 3) AL Shared-Care Partner Centres providing consolidation and less intense chemotherapy, supportive care and follow-up. Sites and healthcare are government funded, through a single-payer system. In 2017, Cancer Care Ontario (now a part of Ontario Health), the government agency managing the delivery of cancer services, released the Acute Leukemia Provincial Plan to provide a vision for the delivery of timely access to high-quality, coordinated services for patients with AL in Ontario. Working with the 14 Regional Cancer Programs in the province, a 10-year plan for expansion to meet the expected demand was developed. Subsequently, provincial stakeholders, including clinical and administrative leaders from across the Province identified a need to develop guidance to ensure all provider sites (existing, new and in development) have the same infrastructure, expertise, quality management, and policies and procedures necessary to deliver high quality care for this specialized, high-need patient population. Methods: The AL Specifications Working Group (WG) was formed to lead the development of organizational guidance. A systematic literature review and jurisdictional scan using key search terms identified existing standards and recommendations. Recommendations were extracted from relevant texts and reviewed. Through informal consensus, the WG endorsed recommendations "as is", adapted recommendations to meet the needs of Ontario, or rejected recommendations deemed not relevant. Where recommendations were lacking, but thought to be needed, new recommendations were written. Results: The literature search identified 2,651 potential texts, of which 17 texts were deemed relevant (Figure 1) and 642 recommendations were extracted. After three rounds of review by the WG members, the Cancer Care Ontario team, and targeted external stakeholders, 229 recommendations were approved (Figure 2). Recommendations were written for each level of service provider using the terminology shall (must be complied with), should (recommended or advised) and may (permissive). Recommendations were grouped into 9 sections: 1) 15 General recommendations related to infrastructure, patient volumes and service provider availability, 2) 25 Clinical Unit recommendations related to inpatient and outpatient structure and services, 3) 99 Personnel recommendations related to roles, responsibilities and training of the multidisciplinary clinical team, 4) 43 Quality Management program and plan recommendations, 5) 22 Policies and Procedures recommendations, 6) 9 Patient Care recommendations, 7) 2 Clinical Research recommendations, 8) 9 Data Management recommendations, and 9) 5 Laboratory Services recommendations related to testing access and turnaround times. In June 2021, the recommendations were shared with impacted stakeholder groups, including health care providers and hospital administration through the release of the Organizational Requirements for Acute Leukemia Service Providers in Ontario: Recommendations Report 2021 (https://www.cancercareontario.ca/en/guidelines-advice/types-of-cancer/69431). The full list of recommendations is available in the Report. Conclusions: The development of these recommendations will serve as a framework for improvement and expansion at existing and new service sites, with the aim of ensuring AL service providers throughout Ontario have the same necessary organizational and operational requirements in place. A gap assessment will inform next steps for focused efforts to provide high quality care which will meet the needs of patients into the future. Figure 1 Figure 1. Disclosures Buckstein: Takeda: Research Funding; TAIHO: Research Funding; Otsuka: Research Funding; Celgene: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees. Sabloff: BMS: Membership on an entity's Board of Directors or advisory committees; Astellas: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; TaiHo: Membership on an entity's Board of Directors or advisory committees; Jaxx: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; ROCHE: Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees. Yee: Onconova: Research Funding; Astex: Membership on an entity's Board of Directors or advisory committees, Research Funding; Forma Therapeutics: Research Funding; Geron: Research Funding; F. Hoffmann La Roche: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero: Research Funding; Janssen: Research Funding; MedImmune: Research Funding; Jazz: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees; TaiHo: Membership on an entity's Board of Directors or advisory committees; Shattuck Labs: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Paladin: Membership on an entity's Board of Directors or advisory committees; Otsuka: Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb/Celgene: Membership on an entity's Board of Directors or advisory committees; AbbVie: Honoraria; Genentech: Research Funding.

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)0.272
metaresearch head score (Gemma)0.355
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.560
Threshold uncertainty score0.898

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2720.355
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0030.005
Bibliometrics0.0140.019
Science and technology studies0.0070.010
Scholarly communication0.0150.014
Open science0.0120.011
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0050.001

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 head0.299
GPT teacher head0.389
Teacher spread0.090 · 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.

Study designQualitative
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
Published2021
Admission routes2
Has abstractyes

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