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Record W1926884994

Enabling and Accelerating First Nations Telehealth Development in Canada

2009· article· en· W1926884994 on OpenAlexaboutno aff
Valerie Gideon, Eugene Nicholas, John Rowlandson, Florence Woolner

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsnot available
Fundersnot available
KeywordsTelehealthEnablingTelemedicineEconomic growthDocumentationBusinessPolitical sciencePublic administrationHealth careMedicineComputer scienceEconomics
DOInot available

Abstract

fetched live from OpenAlex

It is the AFN's position that a 100% investment ratio will enable and accelerate First Nations telemedicine services.This position is based on nation-wide consultations with First Nations, key informant interviews with provincial telemedicine principals and Canada Health Infoway Incorporated's (CHII's) investment record.The AFN asserts that CHII plays two complementary roles as an investor in First Nations Telehealth.The first role is enabler.CHII fulfills this role by investing in documentation, best practices, change management and management tools that reflect First Nations and Aboriginal circumstances, conditions and service models.The latter role is to "directly contribut [e] to increased utilization and expansion of telehealth services...in identified areas of need such as Aboriginal communities."The latter role addresses the need to prioritize telehealth service development in rural and remote First Nations and to accelerate their participation in regional health authority, provincial and federal telehealth systems and networks.While CHII has achieved some success as an enabler, its catalytic capacity is less clear.Accordingly, the AFN is concerned that the CHII telehealth investment program and criteria are dis-incenting First Nations and provincial partners from collaborating on sustainable telehealth development projects and, as a result, that the $17.5M First Nations investment envelope will be undersubscribed before the end of the program in December 2009.While complementary issues -such as the absence of FNIH operational funding for First Nations services, lack of First Nations telehealth policy and program leadership by FNIH, significant and ongoing human and system telehealth capacity gaps in remote First Nations, the high cost of connectivity and the generally poor state of the telecommunications infrastructure in or near First Nations territories -continue to mitigate against successful diffusion of telehealth innovations among First Nations, it is the position of the AFN that changes to CHII's investment ratio for First Nations telehealth and amendments to its investment requirements and eligibility criteria will substantively accelerate First Nations telehealth participation and First Nations capacity to integrate their needs and resources with federal and provincial partners.AFN support for First Nations telehealth services and systems is embedded in the First Nations Action Plan, the Aboriginal Health Blueprint and, recently, the Wait Times Road Map.Telehealth, in these contexts, provides an opportunity for First Nations to close long-time policy, program and health outcomes gaps by enabling strategic partnerships with F/P/T stakeholders, to increase First Nations health system influence and decisionmaking, to increase the level and quality of local health service delivery and to make more effective use of cross-jurisdictional health systems and scarce health human resources.Accordingly, the AFN views telehealth as a means for augmenting delivery of health services for achieving a more even distribution of health and wellness resources among First Nations and for supporting new health human resource opportunities in First Nations communities.In Fall 2006, the AFN's Health and Social Services Secretariat initiated discussions with CHII with the aim of increasing First Nation participation in the CHII telehealth A final section reviewed selection criteria and identified First Nations jurisdictions where potential 100% investment ratio projects are located.This version of the Position paper is focused on the first two sections.Section three and the Appendices have been removed.

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)0.002
metaresearch head score (Gemma)0.005
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: Other · Consensus signal: Other
Teacher disagreement score0.086
Threshold uncertainty score0.626

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.001
Scholarly communication0.0040.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0090.000

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 head0.041
GPT teacher head0.321
Teacher spread0.280 · 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
GenreOther

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

Citations1
Published2009
Admission routes1
Has abstractyes

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