Sundar S Shrestha1, Daniel M Sosin, Martin I Meltzer. 1. Office of Public Health Preparedness and Response (Drs Shrestha and Sosin) and National Center for Emerging and Zoonotic Infectious Diseases (Dr Meltzer), Centers for Disease Control and Prevention, Atlanta, GA 30329-4018, USA. gqm2@cdc.gov
Abstract
OBJECTIVE: To build a tool to assist disaster response planning and estimate the numbers of displaced persons that will require special medical care during a disaster. METHODS: We developed a tool, titled MedCon:PreEvent, which incorporates data from the 2006 National Health Interview Survey, 2005 National Hospital Discharge Survey, and 2004 National Nursing Home Survey to calculate numbers of emergency room/emergency department (ER/ED) visits, surgeries, health care home visits, overnight hospital stays, office visits, and self-rated health status. We then used thresholds of more than 12 office visits or 6 or more ER/ED visits or 6 or more surgeries or more than 4 home visits or more than 6 overnight hospital stays within the past 12 months to calculate rates per million evacuees requiring special medical care, including daily bed hospital and nursing home bed occupancy. RESULTS: We calculated that 79 428 (95% CI = 76 940-81 770) per million evacuees would need special medical care. The daily occupation of hospital beds would be 1710 beds (95% CI = 1328-2160) per million. The occupation of nursing home beds would be 5094 beds (95% CI = 5040-5148) per million. Changing the threshold to just those who self-rated health as "poor," the demand for special medical care would be 24 348 (95% CI = 23 087-25 535) per million. Using threshold utilization values at half the original level would increase the estimate to 226 988 (95% CI = 224 444-229 384) per million. CONCLUSIONS: A substantial number of persons with preexisting conditions will need suitable medical care following a disaster. The MedCon:PreEvent tool can assist disaster planners to prepare for medical care needs of large numbers of evacuees and consider re-evaluating the approach to utilizing and augmenting medical care services.
OBJECTIVE: To build a tool to assist disaster response planning and estimate the numbers of displaced persons that will require special medical care during a disaster. METHODS: We developed a tool, titled MedCon:PreEvent, which incorporates data from the 2006 National Health Interview Survey, 2005 National Hospital Discharge Survey, and 2004 National Nursing Home Survey to calculate numbers of emergency room/emergency department (ER/ED) visits, surgeries, health care home visits, overnight hospital stays, office visits, and self-rated health status. We then used thresholds of more than 12 office visits or 6 or more ER/ED visits or 6 or more surgeries or more than 4 home visits or more than 6 overnight hospital stays within the past 12 months to calculate rates per million evacuees requiring special medical care, including daily bed hospital and nursing home bed occupancy. RESULTS: We calculated that 79 428 (95% CI = 76 940-81 770) per million evacuees would need special medical care. The daily occupation of hospital beds would be 1710 beds (95% CI = 1328-2160) per million. The occupation of nursing home beds would be 5094 beds (95% CI = 5040-5148) per million. Changing the threshold to just those who self-rated health as "poor," the demand for special medical care would be 24 348 (95% CI = 23 087-25 535) per million. Using threshold utilization values at half the original level would increase the estimate to 226 988 (95% CI = 224 444-229 384) per million. CONCLUSIONS: A substantial number of persons with preexisting conditions will need suitable medical care following a disaster. The MedCon:PreEvent tool can assist disaster planners to prepare for medical care needs of large numbers of evacuees and consider re-evaluating the approach to utilizing and augmenting medical care services.
Authors: James B Holt; Kevin A Matthews; Hua Lu; Yan Wang; Jennifer M LeClercq; Kurt J Greenlund; Craig W Thomas Journal: Am J Public Health Date: 2019-09 Impact factor: 9.308