Patient safety and safety culture in primary health care: a systematic review
Bibliographic record
Abstract
BACKGROUND: Patient safety in primary care is an emerging field of research with a growing evidence base in western countries but little has been explored in the Gulf Cooperation Council Countries (GCC) including the Sultanate of Oman. This study aimed to review the literature on the safety culture and patient safety measures used globally to inform the development of safety culture among health care workers in primary care with a particular focus on the Middle East. METHODS: A systematic review of the literature. Searches were undertaken using Medline, EMBASE, CINAHL and Scopus from the year 2000 to 2014. Terms defining safety culture were combined with terms identifying patient safety and primary care. RESULTS: The database searches identified 3072 papers that were screened for inclusion in the review. After the screening and verification, data were extracted from 28 papers that described safety culture in primary care. The global distribution of the articles is as follows: the Netherlands (7), the United States (5), Germany (4), the United Kingdom (1), Australia, Canada and Brazil (two for each country), and with one each from Turkey, Iran, Saudi Arabia and Kuwait. The characteristics of the included studies were grouped under the following themes: safety culture in primary care, incident reporting, safety climate and adverse events. The most common theme from 2011 onwards was the assessment of safety culture in primary care (13 studies, 46%). The most commonly used safety culture assessment tool is the Hospital survey on patient safety culture (HSOPSC) which has been used in developing countries in the Middle East. CONCLUSIONS: This systematic review reveals that the most important first step is the assessment of safety culture in primary care which will provide a basic understanding to safety-related perceptions of health care providers. The HSOPSC has been commonly used in Kuwait, Turkey, and Iran.
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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 | 0.016 | 0.085 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".