BACKGROUND: Advanced decision-support capabilities for prehospital trauma care may prove effective at improving patient care. Such functionality would be possible if an analysis platform were connected to a transport vital-signs monitor. In practice, there are technical challenges to implementing such a system. Not only must each individual component be reliable, but, in addition, the connectivity between components must be reliable. OBJECTIVE: We describe the development, validation, and deployment of the Automated Processing of Physiologic Registry for Assessment of Injury Severity (APPRAISE) platform, intended to serve as a test bed to help evaluate the performance of decision-support algorithms in a prehospital environment. METHODS: We describe the hardware selected and the software implemented, and the procedures used for laboratory and field testing. RESULTS: The APPRAISE platform met performance goals in both laboratory testing (using a vital-sign data simulator) and initial field testing. After its field testing, the platform has been in use on Boston MedFlight air ambulances since February of 2010. CONCLUSION: These experiences may prove informative to other technology developers and to healthcare stakeholders seeking to invest in connected electronic systems for prehospital as well as in-hospital use. Our experiences illustrate two sets of important questions: are the individual components reliable (e.g., physical integrity, power, core functionality, and end-user interaction) and is the connectivity between components reliable (e.g., communication protocols and the metadata necessary for data interpretation)? While all potential operational issues cannot be fully anticipated and eliminated during development, thoughtful design and phased testing steps can reduce, if not eliminate, technical surprises.
BACKGROUND: Advanced decision-support capabilities for prehospital trauma care may prove effective at improving patient care. Such functionality would be possible if an analysis platform were connected to a transport vital-signs monitor. In practice, there are technical challenges to implementing such a system. Not only must each individual component be reliable, but, in addition, the connectivity between components must be reliable. OBJECTIVE: We describe the development, validation, and deployment of the Automated Processing of Physiologic Registry for Assessment of Injury Severity (APPRAISE) platform, intended to serve as a test bed to help evaluate the performance of decision-support algorithms in a prehospital environment. METHODS: We describe the hardware selected and the software implemented, and the procedures used for laboratory and field testing. RESULTS: The APPRAISE platform met performance goals in both laboratory testing (using a vital-sign data simulator) and initial field testing. After its field testing, the platform has been in use on Boston MedFlight air ambulances since February of 2010. CONCLUSION: These experiences may prove informative to other technology developers and to healthcare stakeholders seeking to invest in connected electronic systems for prehospital as well as in-hospital use. Our experiences illustrate two sets of important questions: are the individual components reliable (e.g., physical integrity, power, core functionality, and end-user interaction) and is the connectivity between components reliable (e.g., communication protocols and the metadata necessary for data interpretation)? While all potential operational issues cannot be fully anticipated and eliminated during development, thoughtful design and phased testing steps can reduce, if not eliminate, technical surprises.
Authors: Brian J Eastridge; Robert L Mabry; Peter Seguin; Joyce Cantrell; Terrill Tops; Paul Uribe; Olga Mallett; Tamara Zubko; Lynne Oetjen-Gerdes; Todd E Rasmussen; Frank K Butler; Russ S Kotwal; Russell S Kotwal; John B Holcomb; Charles Wade; Howard Champion; Mimi Lawnick; Leon Moores; Lorne H Blackbourne Journal: J Trauma Acute Care Surg Date: 2012-12 Impact factor: 3.313
Authors: E Kyriacou; S Pavlopoulos; A Berler; M Neophytou; A Bourka; A Georgoulas; A Anagnostaki; D Karayiannis; C Schizas; C Pattichis; A Andreou; D Koutsouris Journal: Biomed Eng Online Date: 2003-03-24 Impact factor: 2.819
Authors: Yeongho Choi; Jeong Ho Park; Ki Jeong Hong; Young Sun Ro; Kyoung Jun Song; Sang Do Shin Journal: BMJ Open Date: 2022-01-12 Impact factor: 2.692