공공의료 빅데이터 기반 반려동물 위탁 돌봄 수요 추정에 관한 연구

Predicting and Analyzing Pet Care Gaps Using Public Health Big Data on Owner Illness and Injury

This study uses the National Patient Sample (NPS) as public healthcare big data to operationalize periods of pet owners’ hospitalization due to illness or injury as a ‘care gaps’ and to examine their risk patterns by integrating life-cycle stage, disease severity, and level of medical institution. The results indicate that young adults experience acute and short-term care gaps primarily driven by mild diseases and injuries, while middle-aged adults transition toward longer-term and recurring gaps centered on disease-related admissions. Older adults exhibit the highest concentration of intense care gaps, with simultaneous increases in both mild and severe conditions. These findings underscore the need for life-cycle-specific policies and targeted support systems to support companion-animal care during owners’ hospitalization.