The state of prevention in allied health education and practice.
Bibliographic record
Abstract
HEALTH CARE COSTS, representing 13.3% of the U.S. gross domestic product in and 14.1% in 2001, remain a major barrier to providing adequate access to care. Escalating costs have been fueled primarily by spending for prescription drugs (15.7%), hospital services (8.3%), and physician and clinical services (8.6%),1 most of which are likely to be associated with illness care. Outcomes of care in the United States do not compare favorably with other countries committing similar resources to health care. The United States spent $4,000 per person in 1998 compared to $2,860 by Switzerland, the nation that ranked second in health care spending. Yet Americans lived an average of 77 years compared with the Swiss life expectancy of 80 years. Similarly, Canada and Japan, both with average life expectances of 81, spent $2,363 and $1,763 per person. There has been some benefit to the increased U.S. spending because the average life expectancy has increased from 70 to 77 years over the past 4 decades; however, the United States still falls behind other industrialized countries in the cost of health care relative to longevity of the population.2 Prevention (health promotion and risk reduction) has been touted as an important strategy to reduce health care costs. The underlying principle of such an approach is that the cost of prevention or early treatment would be less than the cost of aggressively treating a serious illness. Prevention can be accomplished only if all health care providers, regardless of discipline, integrate health promotion/risk reduction into their practice. This article reviews the state of prevention in allied health education and practice and discusses the experience of a College of Health Sciences and Human Services in encouraging integration of prevention into allied health practice. Emphasis on Prevention Since the 1970s, there have been significant efforts from governments and a variety of health care advocates to integrate prevention into health care. In 1979, the SurgeonGeneral's reports, Healthy and Healthy People 2000: National Health Promotion and Disease Prevention, established national health objectives that served as a basis for the development of state and community plans.3 Under the direction of the U.S. Public Health Services, the Healthy People 2000 goals have been replaced with Healthy People 2010 goals, revised to include (1) increasing life expectancy and improving quality of life and (2) eliminating health disparities among the U. S. population.4 Prevention also is receiving increased attention internationally. The objective of the Department of Noncommunicable Disease Prevention and Health Promotion of the World Health Organization is to reduce the incidence of noncommunicable diseases and promote positive health and well-being, with particular focus on developing countries. The strategy to reach this objective is to emphasize major risk factors for noncommunicable diseases and the underlying determinants of health.5 Similarly the goal of the PanAmerican Health Organization includes promotion of primary health care and expediting health promotion to help countries deal with health problems typical of development and urbanization, such as cardiovascular diseases, cancer, accidents, smoking, and addiction to drugs and alcohol.6 SPECIFIC GCWERNMENTAL INITIATIVES In 1984, the U.S. Public Health Services established the United States Preventive Health Service Task Force (USPHSTF). This independent panel of experts in primary care and prevention, now under the auspices of the Agency for Healthcare Research and Quality (AHRQ), reviews evidence of effectiveness and develops recommendations for clinical preventive services. Similarly, the Centers for Dis ease Control and Prevention (CDC) sponsor a task force on community preventive services and publish the Guide to Community Preventive Services.7 Both initiatives are designed to determine under what circumstances prevention/risk reduction strategies should be implemented and the standard of care for each intervention. …
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.081 | 0.029 |
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".