[DMANET] Ph. D. position in Health Care Management, LIMOS France

The LIMOS (Laboratoire d'Informatique, de Modélisation et d'Optimisation
des Systèmes) CNRS UMR 6158 seeking candidates for a doctoral position
in Operations Research and Industrial Engineering at the Health Care
Management department of the Ecole des Mines de Saint-Etienne.

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Title: Demand modeling and operation management of complex cares

Host lab: LIMOS CNRS UMR 6158, ROGI-CIS team,
http://cis.mines-stetienne.fr/content/610-i4s-lab

Location: Ecole des Mines de Saint-Etienne, France

Supervisor: Professor Xiaolan Xie

Funds: Grant from the Ecole des Mines de Saint-Etienne.


Duration: 3 years, starting October 2013

Candidate profile: Master of science in operations research or
industrial engineering, optimization, combinatorial optimization,
stochastic modeling.

How to apply: Email to xie@emse.fr the followings : CV, letter of
motivation, notes and ranking of the three past years, letters of
recommendation.


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Description of the research activities:

Complex cares such as oncology cares are subject to various care
protocols and cover a long period of time. Rich information about health
condition of patients is gathered along the health care process by blood
tests before each chemotherapy session. Care protocols should be adapted
according to the health condition of patients. Integrate explicitly data
concerning patient health condition and care protocols in modeling and
optimization of demand for complex cares is crucial for patient-centered
health care. The goal of this research is to develop quantitative
methods for demand forecasting and operation management of complex cares.

This research relies on our on-going work on optimization of oncology
cares within the framework of the PhD thesis of Abdellah Saki [1, 2].
This on-going research focuses on planning and scheduling of
chemotherapy treatments at an outpatient unit. It is observed that huge
amount of medical data on patient's health conditions are available and
used empirically by oncologists for medical decisions such as change of
care protocols. There are scarcely any research initiatives for
exploiting these data for forecasting complex cares. However, recent
research on medical decisions and disease screening policies [3-7] show
that it is possible to forecast the evolution of patient's health
condition and use it for better decision making.

This thesis will address two related issues. It will first address the
forecasting of demand for complex cares at mid-term (over years) and at
short-term (over weeks or months). It aims at developing quantitative
models such as Markov chains for modeling the dynamic evolution of
patient's health condition. It will be based on medical data on patient
health condition and results of epidemiological research.

Starting from the model of patient health condition, the second goal of
this thesis is the development of optimal strategies for planning of
health care resources in order to meet the changing demand for complex
cares. Both strategy and operational decisions will be addressed.
Mid-term demand forecast over years will be used for planning human
resource capacity. Short-term forecast on evolution of patient's health
condition will be used in operational decisions such as appointment
scheduling and working time scheduling of physicians. The main
difficulty of this second part is the need to take into account
uncertainties related to patient flow, the evolution of patient's health
condition and the integration of medical data of patients. Monte Carlo
optimization and Markov decision process will be exploited to
investigate the underlying stochastic models.


[1] Abdellah SADKI, Xiaolan XIE, Franck CHAUVIN, " Planning Oncologists
of Ambulatory Care Units", en revision for
Decision Support Systems.
[2] Abdellah Sadki, Xiaolan Xie, Franck Chauvin. "Patients assignment
for an Oncology Outpatient Unit ". Proc. IEEE Conf.
Automation Science & Engineering (CASE'10), Toronto, Canada, 2010.
[3] J. Chhatwal, O. Alagoz, E.S. Burnside, "Optimal Breast Biopsy
Decision-Making Based on Mammographic Features and
Demographic Factors", Operations Research, 58/6, 1577-1591, 2010.
[4] M.S. Rauner, W.J. Gutjahr, K. Heidenberger, J. Wagner, J. Pasia , "
Dynamic Policy Modeling for Chronic Diseases:
Metaheuristic-Based Identification of Pareto-Optimal Screening
Strategies," Operations Research, 58/5, 1269-1286, 2010.
[5] Kurt, M., Denton, B.T., Schaefer, A., Shah, N., Smith, S., "The
Optimal Timing of Statin Initiation for Patients with Type 2
Diabetes", submitted to Management Science , 2011.
[6] M.S. Lavieri, M.L. Puterman, S. Tyldesley, W.J. Morris. When to
Treat Prostate Cancer Patients Based on their PSA
Dynamics, manuscript under revision
[7] P.T Vanberkel, M.L Puterman, P. Santibanez , S. Tyldesley, " Panel
Sizing in Oncology", under revision


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--
Garaix Thierry
Associate Professor at Healthcare Management Department
Center of Health Engineering (LIMOS CNRS UMR 6158, ROGI)
École Nationale Supérieure des Mines de Saint-Étienne (ENSMSE)
158, cours Fauriel
42023 Saint-Etienne cedex 2 France
Tel. +33 (0)4 77 42 66 41
Fax +33 (0)4 77 42 02 49
garaix@emse.fr
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