Rethinking referral systems in rural chiapas: A mixed methods study.
Dialogues Health
; 3: 100156, 2023 Dec.
Article
em En
| MEDLINE
| ID: mdl-38515804
ABSTRACT
Background:
Despite the assurance of universal health coverage, large disparities exist in access to surgery in the state of Chiapas. The purpose of this study was to determine the effectiveness of the surgical referral system at hospitals operated by the Ministry of Health in Chiapas.Methods:
13 variables were extracted from surgical referrals data from three public hospitals in Chiapas over a three-year period. Interviews were performed of health care workers involved in the referral system and surgical patients. The quantitative and qualitative data was analyzed convergently and reported using a narrative approach.Findings:
In total, only 47.4% of referred patients requiring surgery received an operation. Requiring an elective, gynecological, or orthopedic surgery and each additional surgery cancellation were significantly associated with lower rates of receiving surgery. The impact of gender and surgical specialty, economic fragility of farmers, dependence upon economic resources to access care, pain leading people to seek care, and futility leading patients to abandon the public system were identified as main themes from the mixed methods analysis.Interpretation:
Surgical referral patients in Chiapas struggle to navigate an inefficient and expensive system, leading to delayed care and forcing many patients to turn to the private health system. These mixed methods findings provide a detailed view of often overlooked limitations to universal health coverage in Chiapas. Moving forward, this knowledge must be applied to improve referral system coordination and provide hospitals with the necessary workforce, equipment, and protocols to ensure access to guaranteed care.Funding:
Harvard University and the Abundance Fund provided funding for this project. Funding sources had no role in the writing of the manuscript or decision to submit it for publication.
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Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article