Internet Infrastructures and Health Care Systems: a Qualitative Comparative Analysis on Networks and Markets in the British National Health Service and Kaiser Permanente
Bibliographic record
Abstract
BACKGROUND: The Internet and emergent telecommunications infrastructures are transforming the future of health care management. The costs of health care delivery systems, products, and services continue to rise everywhere, but performance of health care delivery is associated with institutional and ideological considerations as well as availability of financial and technological resources. OBJECTIVE: to identify the effects of ideological differences on health care market infrastructures including the Internet and telecommunications technologies by a comparative case analysis of two large health care organizations: the British National Health Service and the California-based Kaiser Permanente health maintenance organization. METHODS: A qualitative comparative analysis focusing on the British National Health Service and the Kaiser Permanente health maintenance organization to show how system infrastructures vary according to market dynamics dominated by health care institutions ("push") or by consumer demand ("pull"). System control mechanisms may be technologically embedded, institutional, or behavioral. RESULTS: The analysis suggests that telecommunications technologies and the Internet may contribute significantly to health care system performance in a context of ideological diversity. CONCLUSIONS: The study offers evidence to validate alternative models of health care governance: the national constitution model, and the enterprise business contract model. This evidence also suggests important questions for health care policy makers as well as researchers in telecommunications, organizational theory, and health care management.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".