Drone-Aided Healthcare Services for Patients with Chronic Diseases in Rural Areas

TARGET GROUP: PATIENTS WITH CHRONIC DISEASES

OBJECTIVES

·        To address the drone-aided delivery and pickup planning of medication and test kits for patients with chronic diseases.

·        To provide routine healthcare services.

·        To find the optimal number of drone center locations using the set covering approach.

·        To improve computational performance of the proposed models, a preprocessing algorithm, a Partition method, and a Lagrangian Relaxation (LR) method.

·        To analyze the benefits of drone-aided healthcare service. The work is tested on a numerical example to show its applicability.

SUMMARY

According to the Centres for Disease Control and Prevention (CDC), chronic diseases are a major concern in terms of their economic and social aspects among the government and patients. The cost of chronic diseases is an overwhelming component of overall healthcare expenses. In the United States (US), about 117 million people have had one or more chronic diseases in 2012, which means that about half of all adults are carrying chronic diseases that include heart disease, diabetes, arthritis and obesity. Patients with chronic diseases are required to visit medical institutions for routine checkups or medicine refills. These periodic visits incur out-of-pocket expenses and medical costs that can be several times higher compared to patients without chronic diseases. This study proposes two planning models: strategic planning (SP) and operational planning (OP). The purpose of the SP model is to find the optimal locations for drone centers to provide its services to all patients in a given area. In the OP model, taking service range from centers into consideration, the optimal number of drones per drone center and their optimal delivery and pickup schedules are determined to satisfy the specific demands of patients within possible flying times. This study also suggests a cost-benefit ratio method for sensitivity analysis to help decision makers in providing an economically viable healthcare delivery service to patients using drones.

REFERENCE: https://www.ie.uh.edu/sites/ie/files/faculty/glim/Drone-healthcare-JIRS(2017).pdf