Health systems integration: state of the evidence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Integrated health systems are considered a solution to the challenge of maintaining the accessibility and integrity of healthcare in numerous jurisdictions worldwide. However, decision makers in a Canadian health region indicated they were challenged to find evidence-based information to assist with the planning and implementation of integrated healthcare systems. METHODS: A systematic literature review of peer-reviewed literature from health sciences and business databases, and targeted grey literature sources. RESULTS: Despite the large number of articles discussing integration, significant gaps in the research literature exist. There was a lack of high quality, empirical studies providing evidence on how health systems can improve service delivery and population health. No universal definition or concept of integration was found and multiple integration models from both the healthcare and business literature were proposed in the literature. The review also revealed a lack of standardized, validated tools that have been systematically used to evaluate integration outcomes. This makes measuring and comparing the impact of integration on system, provider and patient level challenging. DISCUSSION AND CONCLUSION: Healthcare is likely too complex for a one-size-fits-all integration solution. It is important for decision makers and planners to choose a set of complementary models, structures and processes to create an integrated health system that fits the needs of the population across the continuum of care. However, in order to have evidence available, decision makers and planners should include evaluation for accountability purposes and to ensure a better understanding of the effectiveness and impact of health systems integration.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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 it