An Analytics-based Decision Support System for Resource Planning under Heterogeneous Service Demand of Nursing Home Residents

TL;DR

This paper introduces an analytics-based decision support system that models heterogeneous service demands of nursing home residents to improve resource planning and care quality.

Contribution

It presents a novel integrated framework combining statistical modeling, simulation, and optimization for resource planning under demand heterogeneity.

Findings

Effective modeling of demand heterogeneity improves resource allocation.

Case study demonstrates superior performance over existing methods.

Heterogeneity impacts resource planning decisions significantly.

Abstract

Nursing homes (NHs) are critical healthcare infrastructures for caring frail older adults with 24/7 formal care and personal assistance. Adequate NH resource planning is of great importance to ensure desired quality of care and resident outcomes yet challenging. The challenge lies in the heterogeneous service demand of NH residents, due to the varied individual characteristics, the diverse dwelling duration with multiple competing discharge dispositions, and the diverse service need. Existing healthcare staffing literature often assumed a homogeneous population of NH residents and neglected the complexity of service demand heterogeneity. This work proposes an analytics-based modeling framework with a user-friendly decision support platform for NH resource planning. The proposed framework characterizes the heterogeneous service demand of NH residents via novel integration of advanced statistical modeling, computer simulation and optimization techniques. We further provide a case study using real data from our industrial collaborator to demonstrate the effectiveness and superior performance of the proposed work. The impacts of service utilization heterogeneity and service need heterogeneity on resource planning decisions are investigated as well.