Master of Science (MS)
Sharon J Meaker-Medcalf
Philip Welsch Smith
Theodore J Cieslak
Long Term Care facilities preparedness for disasters has been questioned, and evacuation before or during disasters is crucial for life saving. This thesis attempted to develop a systematic triage methodology based on the use of the Minimum Data Set (MDS), which is a powerful resource for gathering residents’ vital information including physical ability, cognitive functioning, and other health related conditions. Our assumption was that 90% of caregivers’ triage categorization will match with the categorization generated from the MDS dataset. To achieve our objectives and aims, we compared the triage categorization carried out by residents’ caregivers versus the MDS generated triage categories. Overall we did not found a strong agreement between caregivers and MDS triage categorization. However, the triage categorization of both homemakers and cooks versus CNAs yield a substantial correlation. Also we found that the work experience was closely related to the agreement between RN and CNAs versus MDS. In conclusion we think that MDS can be used to generate triage categories for long term care residents to facilitate the systematic evacuation of buildings in the case of mass casualty event. But before that, it will be important to conduct further studies with a large sample size of caregivers and the accessibility to the MDS dataset. The validation of the use of MDS dataset to generate triage categories will hugely help long term care facilities to be prepared for evacuation, because it can be the start point for the development of triage application which can be use on both portable and mobile electronic devices.
Traore, Zoumana I., "Using the Minimum Data Set (MDS) to Triage Long Term Care Facilities’ Residents for a Systematic Evacuation in the Case of Mass Casualty Disaster Events" (2016). Theses & Dissertations. 91.