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Identifying quality indicators for prehospital emergency care services in the low to middle income setting: The South African perspective
INTRODUCTION: Historically, performance within the Prehospital Emergency Care (PEC) setting has been assessed primarily based on response times. While easy to measure and valued by the public, overall, response time targets are a poor predictor of quality of care and clinical outcomes. Over the last...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
African Federation for Emergency Medicine
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6933208/ https://www.ncbi.nlm.nih.gov/pubmed/31890482 http://dx.doi.org/10.1016/j.afjem.2019.07.003 |
Sumario: | INTRODUCTION: Historically, performance within the Prehospital Emergency Care (PEC) setting has been assessed primarily based on response times. While easy to measure and valued by the public, overall, response time targets are a poor predictor of quality of care and clinical outcomes. Over the last two decades however, significant progress has been made towards improving the assessment of PEC performance, largely in the form of the development of PEC-specific quality indicators (QIs). Despite this progress, there has been little to no development of similar systems within the low- to middle-income country setting. As a result, the aim of this study was to identify a set of QIs appropriate for use in the South African PEC setting. METHODS: A three-round modified online Delphi study design was conducted to identify, refine and review a list of QIs for potential use in the South African PEC setting. Operational definitions, data components and criteria for use were developed for 210 QIs for inclusion into the study. RESULTS: In total, 104 QIs reached consensus agreement including, 90 clinical QIs, across 15 subcategories, and 14 non-clinical QIs across two subcategories. Amongst the clinical category, airway management (n = 13 QIs; 14%); out-of-hospital cardiac arrest (n = 13 QIs; 14%); and acute coronary syndromes (n = 11 QIs; 12%) made up the majority. Within the non-clinical category, adverse events made up the significant majority with nine QIs (64%). CONCLUSION: Within the South Africa setting, there are a multitude of QIs that are relevant and appropriate for use in PEC. This was evident in the number, variety and type of QIs reaching consensus agreement in our study. Furthermore, both the methodology employed, and findings of this study may be used to inform the development of PEC specific QIs within other LMIC settings. |
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