Authors:
Waqar Haque
1
;
Shannon Freeman
2
and
Piper Jackson
3
Affiliations:
1
Department of Computer Science, University of Northern British Columbia, Prince George, Canada
;
2
School of Nursing, University of Northern British Columbia, Prince George, Canada
;
3
Department of Computing Science, Thompson Rivers University, Kamloops, Canada
Keyword(s):
Visual Analytics, Predictive Analytics, Geriatrics, Long-term Care, interRAI Assessment Tools.
Abstract:
Healthcare data for older adults is often collected through globally standardized instruments and resides in multiple disparate database systems. For gaining insights into this data, an interactive platform has been developed which allows visualization of several actionable key performance indicators along multiple dimensions. The health assessment data was collected from persons receiving community home care services as well as from persons residing in long-term care facilities. The top-level reports provide aggregations across geographical regions at the health service delivery area level with capability to drill down to finer granularity for metrics of interest. By revealing hidden patterns embedded in data, the stakeholders can make informed decisions pertaining to resource allocation and better patient care. The drill-down and drill-through reports include demographics, quality of life, medications, health conditions and disease diagnoses, comorbidities, health service usage, an
d patient journey across care settings. A predictive model to accurately estimate resource requirements at the time of admission was also developed for data-driven triaging.
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