Working Against the Clock: A Model for Rural STEMI Triage.
Rob E CarpenterRochell McWhorterShirl DonaldsonDave SilbermanSteve MaffeiPublished in: Health services insights (2021)
Residents in rural communities have a higher incidence of cardiac death and risk factors associated with cardiac disease. Living in a rural region can add precious time that amplifies cardiac death during an ST-elevated myocardial infarction (STEMI) episode. The consensus is that improved efficiencies can increase myocardial salvage and decrease STEMI mortality rates. This article identifies issues that may impact pre-hospital STEMI triage of patients in a rural region of the United States (U.S.). A qualitative research design was chosen to gain insight into emergency personnel perceptions of pre-hospital STEMI triage. The participants (n = 18) were obtained from a convenience sample in rural Northeast Texas, U.S. Data were gathered by individual and group semi-structured interviews. Themes were identified, synthesized, and oriented to offer a basis for understanding opportunities to improve the delivery of rural STEMI care. This study demonstrated that quality improvement initiatives aimed at achieving pre-hospital STEMI triage efficiencies have dependencies on teamwork, technology, and training in the context of 3 stages (a) pre-transport, (b) door-to-door, and (c) post-transport. A pre-hospital STEMI triage model is offered based on the findings. By incorporating this model, emergency medical coordinators in rural communities have a better opportunity to facilitate timely reperfusion therapy for this high-risk population.
Keyphrases
- percutaneous coronary intervention
- south africa
- st elevation myocardial infarction
- emergency department
- st segment elevation myocardial infarction
- healthcare
- quality improvement
- left ventricular
- acute myocardial infarction
- chronic kidney disease
- end stage renal disease
- coronary artery disease
- ejection fraction
- risk factors
- adverse drug
- newly diagnosed
- primary care
- genome wide
- machine learning
- gene expression
- dna methylation
- cerebral ischemia
- deep learning
- electronic health record