Knowledge, Implementation, and Perception of Enhanced Recovery After Surgery Amongst Surgeons in Pakistan: A Survey Analysis
Bibliographic record
Abstract
INTRODUCTION: An increasing shift towards non-communicable diseases and an existing high surgical burden of disease in low-middle-income countries (LMICs), such as Pakistan, has driven the need for implementing Enhanced Recovery After Surgery (ERAS), a safe and cost-effective surgical service aimed at improving patient recovery and reducing post-operative complications. Despite countless benefits, there are few ERAS programs throughout Pakistan and sparse literature on healthcare professionals' views regarding ERAS. Without a deep understanding of healthcare professionals' perspectives on ERAS, underlying barriers and facilitators to a long-term ERAS implementation cannot be addressed and improved upon. Therefore, the purpose of this study is to better understand the knowledge, implementation, and perception of ERAS from the perspective of healthcare professionals across Pakistan. METHODS: Upon receiving ethical approval from the McGill University Health Center (MUHC), a previously validated questionnaire was modified and a 29-question survey was developed and disseminated to healthcare professionals practising in Pakistan. Quantitative data was analyzed using descriptive statistics and potential correlations that exist between the implementation of ERAS and the participants' gender, employment setting, and surgical specialty were investigated using the chi-squared analysis with a p-value of 0.05 as the cutoff. RESULTS: A total of 49 participants responded to this survey of whom 34 (69%) worked at a tertiary care teaching hospital whereas 15 (31%) worked at a private hospital. Surprisingly, 42 (85%) participants expressed being aware of the ERAS guidelines with only 30 (61%) either strongly agreeing or agreeing to successfully implementing ERAS into practice. The largest discrepancies in implementation were seen when discussing specific elements of the ERAS guidelines such as preoperative carbohydrate loading, practicing prolonged preoperative fasting, performing mechanical bowel preparation, performing active patient warming, and early postoperative removal of Foley's catheter. Surgeons employed at a private institution were more likely to discuss postoperative pain management and control, less likely to utilize prolonged fasting, more likely to perform regular body temperature monitoring, more likely to practice providing chewing gum to patients postoperatively, and more likely to perform early removal of the Foley's catheter. CONCLUSION: An understanding of ERAS, the implementation of various elements, and a positive attitude toward its benefits definitely seem to be prevalent among healthcare professionals in Pakistan. However, key barriers and enablers specific to the underlying healthcare environment seem to be hindering the long-term successful implementation of ERAS across Pakistan. It is crucial for future studies to explore these barriers in further detail and involve the perspective of these key stakeholders to help enhance long-term ERAS adoption.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.001 | 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".