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Record W3025763588 · doi:10.2196/18995

Emergency Response to COVID-19 in Canada: Platform Development and Implementation for eHealth in Crisis Management

2020· article· en· W3025763588 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJMIR Public Health and Surveillance · 2020
Typearticle
Languageen
FieldHealth Professions
TopicDisaster Response and Management
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsHealth careeHealthBusinessTriageResource allocationPublic healthCrisis managementDigital healthTelemedicinePandemicCorporate governanceRisk analysis (engineering)Computer securityComputer scienceMedicineMedical emergencyCoronavirus disease 2019 (COVID-19)DiseaseNursingEconomics

Abstract

fetched live from OpenAlex

BACKGROUND: Public health emergencies like epidemics put enormous pressure on health care systems while revealing deep structural and functional problems in the organization of care. The current coronavirus disease (COVID-19) pandemic illustrates this at a global level. The sudden increased demand on delivery systems puts unique pressures on pre-established care pathways. These extraordinary times require efficient tools for smart governance and resource allocation. OBJECTIVE: The aim of this study is to develop an innovative web-based solution addressing the seemingly insurmountable challenges of triaging, monitoring, and delivering nonhospital services unleashed by the COVID-19 pandemic. METHODS: An adaptable crisis management digital platform was envisioned and designed with the goal of improving the system's response on the basis of the literature; an existing shared health record platform; and discussions between health care providers, decision makers, academia, and the private sector in response to the COVID 19 epidemic. RESULTS: The Crisis Management Platform was developed and offered to health authorities in Ontario on a nonprofit basis. It has the capability to dramatically streamline patient intake, triage, monitoring, referral, and delivery of nonhospital services. It decentralizes the provision of services (by moving them online) and centralizes data gathering and analysis, maximizing the use of existing human resources, facilitating evidence-based decision making, and minimizing the risk to both users and providers. It has unlimited scale-up possibilities (only constrained by human health risk resource availability) with minimal marginal cost. Similar web-based solutions have the potential to fill an urgent gap in resource allocation, becoming a unique asset for health systems governance and management during critical times. They highlight the potential effectiveness of web-based solutions if built on an outcome-driven architecture. CONCLUSIONS: Data and web-based approaches in response to a public health crisis are key to evidence-driven oversight and management of public health emergencies.

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.

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)0.004
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.739
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.117
GPT teacher head0.442
Teacher spread0.325 · 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