A Study of Operations Research in Healthcare


Authors : Nandan Shah, Ninad Thawait, Pranav Kohli, Prithika Kharwar, Priti Bhatt

Volume/Issue : Volume 2 - 2017, Issue 10 - October

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://goo.gl/raQamV

Thomson Reuters ResearcherID : https://goo.gl/3bkzwv

For more than 30 years, Operations Research teams have shown great interest in the field of healthcare and medical delivery systems and how they function around the globe. In the past few years, the birth rates have been decreasing considerably, especially in developed countries. Along with that, the average global lifespan and longevity has also been rising. Healthcare has obviously proven to be an important aspect in today’s modern and fast paced world, where optimization of scarce resources is the utmost need of the hour. The attention has gradually expanded from merely resource allocation and has moved forward towards strategic planning, in order to include operational issues, namely- resource scheduling and treatment planning.This research paper studies the various application and uses of Operations Research in the area of healthcare delivery systems and their effectiveness. This paper reviews and assesses the major contributions involving contemporary optimisation issues in this particular area of study. The study highlights the research activities in current use, throwing light on the optimisation issues faced by the industry, along with the methods used to find solutions to the optimisation problems and putting them into practice.

Keywords : used in the analysis:Location selection, P-medium models, demand forecasting, network models, demographic groupings, scheduling, simulations, optimization, diminishment, hybrid, crises, constrains, logistics, stock level, drug allocation, disease diagnostics. Specialised healthcare, preventive healthcare, organ allocation, medical simulation, vaccine algorithm, HIV prevention program, medical screening programmes, treatment planning, medical therapeutics, diabetes complications, healthcare cost, dynamic programming algorithm, linear formulations, non-linear formulations.

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