Revitalizing primary health care and family medicine/primary care in India – disruptive innovation?
Bibliographic record
Abstract
CONTEXT: India has rudimentary and fragmented primary health care (PHC) and family medicine systems, yet it also has the policy expectation that PHC should meet the needs of extremely large populations with slums and difficult to reach groups, rapid social and epidemiological transition from developing to developed nation profiles. Historically, the system has lacked impetus to achieve PHC. OBJECTIVE: To provide an overview of PHC approaches and the current state of PHC and family medicine in India in order to assess the opportunities for their revitalization. METHODS: A narrative review of the published and grey literature on PHC, family medicine, Web2.0 and health informatics key papers and policy documents, pertinent to India. OUTCOMES: A conceptual framework and recommendations for policy makers and practitioner audiences. FINDINGS: PHC is constructed through systems of local providers who address individual, family and local community basic health needs with strong community participation. Successful PHC is a pre-eminent strategy for India to address the determinants of health and the almost chaotic of massive social transition in its institutions and health care sector. There is a lack of an articulated comprehensive framework for the publicly stated goals of improving health and implementing PHC. Also, there exists a very limited education and organization of a medical and PHC workforce who are trained and resourced to address individual, family and local community health and who have become increasingly specialized. However, emerging technology, Health2.0 and user generated health care informatics, which are largely conducted through mobile phones, are co-evolving patient-driven health systems, and potentially enhance PHC and family medicine workforce development. CONCLUSIONS: In order to improve health outcomes in an equitable manner in India, there is a pressing need for a framework for implementing PHC. The co-emergence of information technologies accessible to the mass population and user-driven health care provide a potential catalyst or innovation for this transition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.016 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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 source (direct Gemma or distilled Codex), 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".