Affiliation:
1. Department of Surgery University of Washington 1959 NE Pacific St. 98195 Seattle WA USA
2. Global Injury Control Section Harborview Injury Prevention and Research Center Seattle WA USA
3. Department of Environmental Health Sciences University of California Berkeley Berkeley CA USA
4. Health Science Library University of Washington Seattle WA USA
5. Stanford University School of Medicine Stanford CA USA
Abstract
AbstractBackgroundNo validated perioperative risk assessment models currently exist for use in humanitarian settings. To inform the development of a perioperative mortality risk assessment model applicable to humanitarian settings, we conducted a scoping review of the literature to identify reports that described perioperative risk assessment in surgical care in humanitarian settings and LMICs.MethodsWe conducted a scoping review of the literature to identify records that described perioperative risk assessment in low‐resource or humanitarian settings. Searches were conducted in databases including: PubMed, Embase, Cumulative Index to Nursing and Allied Health Literature, Web of Science, World Health Organization Catalog, and Google Scholar.ResultsOur search identified 1582 records. After title/abstract and full text screening, 50 reports remained eligible for analysis in quantitative and qualitative synthesis. These reports presented data from over 37 countries from public, NGO, and military facilities. Data reporting was highly inconsistent: fewer than half of reports presented the indication for surgery; less than 25% of reports presented data on injury severity or prehospital data. Most elements of perioperative risk models designed for high‐resource settings (e.g., vital signs, laboratory data, and medical comorbidities) were unavailable.ConclusionAt present, no perioperative mortality risk assessment model exists for use in humanitarian settings. Limitations in consistency and quality of data reporting are a primary barrier, however, can be addressed through data‐driven identification of several key variables encompassed by a minimum dataset. The development of such a score is a critical step toward improving the quality of care provided to populations affected by conflict and protracted humanitarian crises.
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