Barriers to Accessing Congenital Heart Surgery in Low- and Middle-Income Countries: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Congenital heart disease (CHD) is the most common major congenital anomaly. Ninety percent of children with CHD are born in low- and middle-income countries (LMICs), where over 90% of patients lack access to necessary treatments. Reports on barriers to accessing CHD care are limited. Accordingly, it is difficult to design evidence-based interventions to increase access to congenital cardiac surgical care in LMICs. OBJECTIVE: We performed a qualitative systematic review to understand barriers to accessing congenital cardiac surgical care in LMICs. METHODS: We conducted a search of Ovid MEDLINE and CINAHL databases to identify relevant articles from January 2000 to May 2021. We then used a thematic analysis to summarize qualitative data into a framework of preoperative, perioperative, and postoperative barriers. RESULTS: Our search yielded 1,585 articles, of which 67 satisfied the inclusion criteria. Notable preoperative barriers included delayed diagnosis, insufficient caregiver education, financial constraints, difficulty reaching treatment centers, sociocultural stigma of CHD, sex-based discrimination of patients with CHD, and Indigeneity. Perioperative barriers included lack of hospital resources and workforce, need for prolonged hospitalization, and strained physician-patient relationships. Many patients faced barriers postoperatively and into adulthood due to a shortage of critical care resources, inadequate caregiver counseling and patient education, lack of follow-up, and debt from hospital bills and missed work. CONCLUSION: Reducing neonatal and childhood mortality begins with recognizing barriers to accessing health care. Our systematic review identifies and classifies challenges in accessing CHD in LMICs and suggests solutions to major barriers.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 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".