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Record W3038896169

Maple respiratory : innovación disruptiva en un modelo de ateción en salud que dió un respiro al sahos en Colombia

2020· article· es· W3038896169 on OpenAlexaboutno aff
Mónica Martinez Gil, Carolina Hernández Gómez

Bibliographic record

Venuenot available
Typearticle
Languagees
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsnot available
Fundersnot available
KeywordsService (business)Business modelBusinessMarketingManagementEconomics
DOInot available

Abstract

fetched live from OpenAlex

Maple Respiratory Group (MRG) was created on April 1, 2001 in Calgary Canada, as a health services company that offered its patients the service of diagnosis of chronic respiratory diseases and sleep disorders, in addition to their treatment through the provision of different modalities of oxygen therapy and sale of equipment, where payment for products and services provided was made directly by patients, who subsequently made the recovery to insurance companies. In 2011, after a market investigation that showed positive results, MRG decided to enter the Colombian market, for which it hired John Harold Marin Kuan, a doctor who, due to his experience, was the ideal person to replicate the business model that the company had in Canada. However, John presented the MRG Board with the situation of the SAHOS in Colombia and the difficulties of replicating the Canadian business model, generated by the high coverage of the health system in the country. Given this scenario, MRG CEO Ben Asuchak, empowered John to design a proposal that would allow MRG to meet its objectives. In response to Ben's request, John designed Somnus et vita, a new business model that not only transformed the existing model in Canada, but also changed the model of care for Obstructive Sleep Apnea Hiccupping Syndrome (OSA) in Colombia. After analyzing the information presented by John, in September 2012 the MRG Board of Directors accepted the change in their business model. From that moment on, John faced two new challenges; the first, to create a marketing strategy that would allow him to take advantage of the market opportunities and encourage the acquisition of the service by the Health Promotion Companies (HPC); the second, to design the implementation strategy of the model created to generate a disruption in the market, displacing the traditional model and achieving the first goal established by MRG, corresponding to 2000 patients in the first year.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.338
Threshold uncertainty score0.673

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.004
Scholarly communication0.0100.004
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.001

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 head0.044
GPT teacher head0.382
Teacher spread0.338 · 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 designObservational
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
Published2020
Admission routes1
Has abstractyes

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