Using standard clinical assessments for home care to identify vulnerable populations before, during, and after disasters

TitleUsing standard clinical assessments for home care to identify vulnerable populations before, during, and after disasters
Publication TypeJournal Article
Year of Publication2017
Authorsvan Solm A.IT, Hirdes J.P, Eckel L.A, Heckman G.A, Bigelow P.L
JournalJournal of emergency management
Volume15
Issue6
Pagination355-366
Keywords*disaster planning, *frailty/di [Diagnosis], *statistics and numerical data, Aged, algorithm, Canada, clinical decision support system, disaster, emergency health service, Female, Geriatric Assessment, home care, Human, Independent Living, Kaplan Meier method, Male, mortality, organization and management, procedures, proportional hazards model, Risk Assessment, vulnerable population
Abstract

OBJECTIVES: Several studies have shown the increased vulnerability of and disproportionate mortality rate among frail community-dwelling older adults as a result of emergencies and disasters. This article will discuss the applicability of the Vulnerable Persons at Risk (VPR) and VPR Plus decision support algorithms designed based on the Resident Assessment Instrument-Home Care (RAI-HC) to identify the most vulnerable community-dwelling (older) adults., DESIGN: A sample was taken from the Ontario RAI-HC database by selecting unique home care clients with assessments closest to December 31, 2014 (N = 275,797). Statistical methods used include cross tabulation, bivariate logistic regression as well as Kaplan-Meier survival plotting and Cox proportional hazards ratios calculations., RESULTS: The VPR and VPR Plus algorithms, were highly predictive of mortality, long-term care admission and hospitalization in ordinary circumstances. This provides a good indication of the strength of the algorithms in identifying vulnerable persons at times of emergencies., CONCLUSIONS: Access to real-time person-level information of persons with functional care needs is a vital enabler for emergency responders in prioritizing and allocating resources during a disaster, and has great utility for emergency planning and recovery efforts. The development of valid and reliable algorithms supports the rapid identification and response to vulnerable community-dwelling persons for all phases of emergency management.

DOI10.5055/jem.2017.0344