Abstract 182: The Impact of National and Regional Health Systems Arrangements on Hypertension Awareness, Treatment and Control: a Systematic Literature Review
Bibliographic record
Abstract
Background: Around a billion people worldwide have hypertension (HT), a major risk factor for cardiovascular disease. A significant proportion of HT patients remain unaware, untreated, and are uncontrolled, despite the availability of inexpensive and effective medications. Weaknesses in health systems are thought to be a key contributor to the inadequacies in HT care and control globally. We performed a systematic literature review to summarize the effects of national or regional health systems arrangements on HT care and control. Methods: An existing health systems framework was adapted to illustrate the impact of health systems components on HT outcomes (awareness, treatment prescription, treatment adherence and HT control) and guide the conduct of the systematic review. Studies analyzing effects of health systems arrangements at the regional or national level on HT outcomes were included, and Medline, Embase, and Global Health were searched for eligible studies. Two authors independently assessed papers for inclusion, extracted data, and assessed risk of bias using a simple proforma. Pooling of results was deemed inappropriate considering substantial variation in study designs. Results: Fifty studies met our eligibility criteria; 1 randomized controlled trial, 11 cohort, 3 case-control, 30 cross-sectional, 3 ecological, and 2 qualitative studies. Forty-one studies (82%) were set in high income countries, 35 of which were in the US. Most studies examined factors relating to the effect of either health systems financing (35) or health systems governance and delivery (16). Longitudinal studies, supported by some but not all cross-sectional studies, consistently reported a significant association between health insurance coverage in the US and improved HT awareness, medication adherence, and control (10 of 21 studies). There was also a consistent significant association, in both longitudinal and cross-sectional studies, between reduced co-payments for medical care and improved HT outcomes (10 of 11 studies). Although lacking longitudinal studies, we found a significant association in 12 of 14 US studies between having a routine place or physician for HT care, and HT outcomes. Conclusions: A largely consistent association between health insurance status, medication copayments, and routine availability of HT care with HT outcomes was found. Implications for policy are mainly applicable to the US setting, where our findings suggest that expanding insurance coverage and increasing access to routine care may improve HT outcomes. Additionally, minimization of co-payments for medication and care may improve HT outcomes in the US and to a limited extent in other non-US settings. Future research efforts should primarily focus on obtaining high quality longitudinal data and reducing the information gap in low and middle income countries, which bear three quarters of the global HT burden.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".