Introduction: Hurricane Harvey made landfall in southeast Texas in August 2017, causing unprecedented flooding throughout the Texas coastal region. Residents of affected regions were forced to evacuate to nearby unaffected areas including Dallas, TX where a large shelter operation was opened for 23 days to care for those evacuees. Retrospective evaluation of pharmaceutical prescribing patterns for the evacuees who self-presented to the Megashelter Medical Clinic (MMC) established in the shelter contributes to developing evidence-based planning strategies for healthcare delivery in the post-disaster setting.
Aim: To describe pharmacy needs of a displaced population following a largescale evacuation after a hurricane
Method: Deidentified prescription records written and filled at a shelter pharmacy were reviewed, looking both at cost and category of medications dispensed over time.
Results: Approximately 41% of evacuees with a total of 2,654 visits utilized the MMC clinic resulting in 1,590 prescriptions filled with an associated cost of $78,039. The most commonly prescribed drug categories were cardiovascular (21.2%), neuropsychotropic (15.6%), infectious disease (12.5%), and endocrine (9.6%). While the most commonly dispensed were antihypertensives, diabetes treatmentrelated prescriptions, antibacterials, antidepressants, and NSAIDs; the costliest individual prescriptions were antiretrovirals and antipsychotics.
Discussion: Prescribing patterns for the MMC differed from normal prescribing pattern of a general population. Of the prescriptions dispensed at the MMC, pharmaceutical prescription patterns suggest the immediate needs of evacuees differ from later needs. There is a greater need for chronic disease management in the early phase of shelter operations, and an increasing need for neuropsychotropic and infectious disease prescriptions over time. Understanding overall patterns of drug utilization over the duration of the shelter provides valuable insight on postdisaster medical resource utilization in evacuee populations.