Today's health care industry is multidisciplinary with many players and levels each with its own set of complex behaviors. Better planning and management of these complexities can help improve the efficacy of health care. The constant ageing of the population as well as the decrease in public expenditure in most countries all over the world have increased the number of challenges facing healthcare policy makers and managers every day. These challenges are all very diverse, from improving patient experience to maintaining high levels of hygiene or optimizing the budget while ensuring a high quality of service and staff. As a healthcare systems designer and analyst, I am extremely happy that by applying my knowledge in Healthcare Systems Engineering, I can help to improve the welfare and happiness of people of all kind around the world.
- Healthcare providers are trained to take care of individual patients.
- Healthcare delivery is a complex system.
- Engineers are trained to improve complex systems.
- Healthcare and Systems Engineering have lived in separate worlds.
APPLY SYSTEMS ENGINEERING TO HEALTHCARE !!!
My Helicopter View on Healthcare – A Healthier Tomorrow
According to WHO, health is a dynamic state of complete physical, mental, spiritual and social well-being and not merely the absence of disease or infirmity.
Current healthcare systems mainly focus on treatment of physical illnesses, often ignoring other related aspects. Even though we are increasingly spending money on healthcare, we do not achieve the desired results.
A perfect healthcare system must protect and promote our health comprehensively, including all physical, mental, spiritual and social aspects as its first responsibility. We need to design integrated healthcare systems, which are able to effectively deliver high quality prevention, early detection, diagnoses and treatment, rehabilitation and palliative care services to bring a healthier tomorrow for our children.
Thesis: A stochastic approach to appointment sequencing
Thesis: Integrated Procurement Production and Distribution Planning in Multi-Echelon Supply Chains
First Class Honours
- Post Doctoral Fellow, Healthcare Systems Design, Joint program of Iran National Elites Foundation and Isfahan University of Medical Sciences.
- Visiting Assistant Professor, Teaching Operations Research for Healthcare, Department of Health Information Technology, Faculty of Healthcare Management, Isfahan University of Medical Sciences.
- Visiting Assistant Professor, Department of Industrial & Systems Engineering, Isfahan University of Technology.
- Vice President for System Design & Head of Home care Network, ALA Cancer Prevention & Control Center, An Iranian NGO offering free cancer palliative care, accomplished more than 25000 home visits yet.
- Head of None-Governmental Palliative Care working group, Islamic Republic of Iran Ministry of Health and Medical Education.
- Chief Executive Officer, Masstec medical Co., a medical device manufacturing company.
- Chief Strategic Officer, Isfahan Healthcare City , The first healthcare city in Iran, 2017-2018
- Assistant Professor, Department of Industrial Engineering, Abdullah Gul University, Turkey, 2016-2017.
- Assistant Professor - Knowledge Management, University of Isfahan, Iran, 2016-2017.
- Head of Customer Relationship Management Department, Emersun Co., Iran, 2007-2009.
- Production Planning Manager, Farman Khodro Co., 2005-2006.
- Healthcare Operations Management
- Systems Analysis & Design
- Stochastic Orders
- Queueing Theory
- Game Theory
- Combinatorial Optimization and Meta-heuristics
- Mathematical Finance
- US INFORMS - Applied Probability Society
- US INFORMS - Computational Optimization and Software
- US INFORMS - Transportation Science and Logistics Society
- US INFORMS - Decision Analysis Society
- US INFORMS - Health Applications Society
- US - Manufacturing and Service Operations Management Society (MSOM)
- MSOM Healthcare Operations Management
- MSOM Supply Chain Management
- MSOM Service Managemen
Current Semester (Educational Materials for My Students)
Isfahan University of Technology:
Introduction of Operations Research - Industrial Engineering Students
Introduction of Operations Research - Engineering Students except Industrial Eng.
Isfahan University of Medical Science:
Operations Research for Healthcare - Health Information Technology Post Graduate Students
Operations Research for Healthcare - Healthcare Operations Management Post Graduate Students
National University of Singapore (Graduate Tutor), Singapore
Probability Models with Applications - 3 semesters
Introduction to industrial systems - 4 Semesters)
Operations Research - 1 Semester
Supply Chain Modeling - 1 Semester
University of Isfahan (Visiting Assistant Professor), Iran
Knowledge Management - 1 Semester
Mathematical Finance - 1 Semester
A. R. Pourghaderi, S. A. Torabi, S. Sekhavat (2009) Scatter search for a real-life fleet size and mix Vehicle routing problem with time windows in Iran”, Proceedings of the 2009 IEEE IEEM, IEEE, Hong Kong, pp. 306-310
S. A. Torabi, A. R. Pourghaderi, S. Sekhavat (2009) A two-step approach including Scatter Search Algorithm for the integrated procurement, production and distribution Planning, Proceedings of the 2009 IEEE IEEM, IEEE, Hong Kong, pp. 354-359
A. R. Pourghaderi, S. A. Torabi, J. Talebi (2008) Scatter search for multi-mode resource constrained project scheduling problems, Proceedings of the 2008 IEEE IEEM, IEEE, Singapore, pp. 163–167
A. R. Pourghaderi, R. Tavakkoli-Moghaddam, M. Alinaghian, B. Beheshtipour (2008) A New simple and effective heuristic algorithm for periodic vehicle routing problems, Proceedings of the 2008 IEEE IEEM, IEEE, Singapore, pp. 133–137.
A. R. Pourghaderi, B. Huang (2013) Sequencing heterogeneous punctual patients, INFORMS Annual Meeting, Minneapolis.
A. R. Pourghaderi, B. Huang (2013) Appointment sequencing: Evaluation of the smaller variance first rule in an appointment system with Equally spaced appointment times, 26th European Conference on Operational Research, Rome.
M. Ghiasi-Moaser, A. Azadeh, A. R. Pourghaderi (2007) Investigation of the effects of critical parameters on rankings of DEA and PCA, Int. Annual Scientific Conf. on Operations Research in the Service Industry, Germany.
R. Tavakkoli-Moghaddam, A. R. Pourghaderi, M. Alinaghian (2007) A new heuristic algorithm for periodic vehicle routing problems, Int. Annual Scientific Conf. on Operations Research in the Service Industry, Germany.
Optimization Model for Ambulance Location Relocation Problem
One of the most important services in today’s societies is the Emergency Medical Service (EMS) which involves many managerial challenges. A very crucial problem which affects the response time of an EMS is the ambulance location problem. This project is dedicated to establish a dynamic data-driven optimization model to optimally locate and relocate over the 50 ambulances in about 220 candidate locations based on the real-time traffic and demand conditions in Isfahan city with about 1.6 million populations, Iran.
Optimization Model for Home Healthcare Planning and Scheduling
Operations management in home care services is complex especially when these services are provided for the patients with life-threatening illnesses like cancer. A very important source of managerial complexity is high demand variation in such services. The weekly demand size for medical care home visits for a typical cancer patient will be at least tripled in the last few weeks of the patient’s life. Hence, when a significant portion of your patients are unexpectedly going to death, your system will face a significant increase in demand, and immediately after the death of the patient, the system's workload drops sharply. This research provides a mathematical programming model to optimize important operational decisions making such as:
- How many doctors, nurses, etc., a service provider must supply for each week based on the number and conditions of the patients covered?
- In each working day, how many medical home care teams should be formed?
- What is the optimal daily working plan for each team (the sequence of patients should be visited by each team)?
- How to deal with uncertainties like emergency unscheduled visits and late cancellations?
Healthcare System Design: An Effective Integrated Model for Cancer Palliative Care Service Delivery Enhanced with an Optimization Decision Support System
Palliative care is an interdisciplinary approach to specialized medical and nursing care for people with life-limiting illnesses. It focuses on providing relief from the symptoms, pain, physical stress, and mental stress at any stage of illness. The goal is to improve quality of life for both the person and their family. Palliative care programs have grown dramatically across the world in last two decades. However, there exists a considerable variation in delivery models. Five major palliative care delivery models are ambulatory clinics, home-based programs, inpatient palliative care units, hospices, and inpatient consultation services.
This project is supported by the Iranian Ministry of Health and Medical Education, to develop an effective cancer palliative care service delivery management model. The model consists of six main components including in-patient palliative care unit, home care network, cancer rehabilitation center, hospice, call center and cancer supportive social network.
Although, every of the aforementioned components has been relatively well designed separately in many researches, an integrated centralized management model which optimally manipulate all the components simultaneously has been paid less attention so far in the literature. This model presents how comprehensive palliative care can be provided for every cancer patients and their families by a single multidisciplinary expert team in different service centers. In our model, the patient does not face by different unknown clinicians at different stage of the diseases and in various palliative care centers, and a dedicated coordinator keeps in touch with him/her, who plans the care from the beginning to the end. The service starts when the cancer is just detected along the continuum from breaking bad news to cure or bereavement, and provides easy to access care for the patients and their families in customized different settings based on their needs and abilities.
The proposed model shows dramatic positive effects on the patient’s satisfaction and quality of life. The optimal decision making is very difficult because of the complexity of the management system. Hence, an advanced Decision Support System (DSS) is developed to synchronize the data from different service centers and intelligently manage the whole system.
Cancer Patient-Specific Survival Prediction
The most commonly used approach for predicting survival times is to create a survival curve for each category of patient (often using the Kaplan-Meier estimator). The problem with this approach is that it aggregates individual patient characteristics.
Using Data Mining approaches, this project is to provide personalized predictions of patient survival times for patients with cancer. When looking at many patient survival curves, we have found that an aggregate approach would obscure the wide range of patient-specific survival curves.
Mobarakeh Steel Company: Comprehensive Employee Health Promotion System Design
Mobarakeh Steel Company (MSC) is the largest steel maker of MENA (Middle East & Northern Africa) region, and one of the largest industrial complexes operating in Iran. The healthcare costs for the company to support its more than 16000 employees and their over 60000 family members has been increasing considerably during the last decade. This project started last year, to answer is it optimal for MSC to establish its own healthcare system? After some analysis, the project upgraded to design a comprehensive employee health promotion system for MSC to provide an effective care at different levels of prevention, early detection, diagnosis and treatment, rehabilitation and palliative care for its employees and their family members. The psychological and social aspects of health is also considered along with the physical aspect in the proposed system.