On Redefining Telemedicine Paradigm: An Innovative Integrated Model for Efficient Implementation of Healthcare Delivery in Developing Countries
Bibliographic record
Abstract
nomenclature in this field. This chapter makes a special effort to place telemedicine development in its proper context, not simply as a technological innovation but as an effective solution to persistent problems in healthcare delivery including inequitable access t o c a r e i n t h e p o p u l a t i o n a t l a r g e , u n e v e n d i s t r i b u t i o n o f q u a l i t y , a n d u n a b a t e d c o s t inflation. Indeed, the persistence of these problems has provided the strongest rationale for the development and growth of telemedicine. The search for telemedicine's roots revealed the enduring need for connectivity in medical care in ancient times and the failure of repeated initiatives and national programs to address problems of inequity of access to healthcare in the population, discrepancies in quality of care between areas and regions, and unabated cost inflation in modern times. There is a great difference between the developing and the developed world on issues of health and healthcare services. The emphasis of the developing world is on basic survival (such as providing better access to healthcare and increasing the quality of health) whilst in the developed world, the emphasis is on reducing public funding for healthcare. Indeed, the rapid increases in healthcare costs and finding ways to control them have become the most important health policy issues for the developed world in the past few decades (Industry Canada, 2006). The case for telemedicine rests on its promise to address some aspects of all of these problems in one form or another. Whereas the importance of these problems is universally acknowledged, for many observers, the efficacy of telemedicine remains a promise. For others, it has already been demonstrated at a reasonable level of confidence. In response to this discrepancy in perspective regarding the true merit of telemedicine, we have tried to highlight the scientific evidence available to date, in order to achieve as much closure on the question as possible. Also, since evaluative research will continue to occupy centre stage, we have attempted to identify the methodological requirements for this research as we pursue the search for more conclusive evidence regarding the true merit of telemedicine. www.intechopen.com On Redefining Telemedicine Paradigm: An Innovative Integrated Model for Efficient Implementation .... 141 2.1 The facts on India's health care situation are as follows 620 million live in rural India (National Council for Applied Economic Research (NCAER)) Bed-Population ratio 1.85 per thousand (2005) Vs. ideal of 1:500 Central bereau of health intelligence CBHI) Doctor-patient ratio in the country is one doctor for nearly 2,000 persons (in the US it is 1:400), 2 million beds are required as against 0.7 million available. 700 hospitals of 250 beds each are required every year. only 9% of 1 billion people are covered health schemes. only 0.9% of GDP for health (WHO recommends 5%)
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".