P. Allotey, D. Reidpath, S. Yasin, and C. Chan, Rethinking health-care systems: a focus on chronicity, The Lancet, vol.377, issue.9764, pp.450-451, 2011.
DOI : 10.1016/S0140-6736(10)61856-9

A. Mariotto, K. Yabroff, Y. Shao, E. Feuer, and M. Brown, Projections of the Cost of Cancer Care in the United States: 2010-2020, JNCI Journal of the National Cancer Institute, vol.103, issue.2, pp.117-128, 2011.
DOI : 10.1093/jnci/djq495

D. Gill, D. Bruce, and P. Tan, Controlling the cost of breast cancer, European Journal of Cancer Care, vol.26, issue.6, pp.703-707
DOI : 10.1111/j.1365-2354.2011.01289.x

J. Lund, K. Yabroff, Y. Ibuka, L. Russell, P. Barnett et al., Inventory of Data Sources for Estimating Health Care Costs in the United States, Medical Care, vol.47, issue.Supplement, pp.47127-142, 2009.
DOI : 10.1097/MLR.0b013e3181a55c3e

K. Yabroff, J. Warren, J. Banthin, D. Schrag, A. Mariotto et al., Comparison of Approaches for Estimating Prevalence Costs of Care for Cancer Patients, Medical Care, vol.47, issue.Supplement, pp.4764-69, 2009.
DOI : 10.1097/MLR.0b013e3181a23e25

M. Beckowski, A. Goyal, R. Goetzel, C. Rinehart, K. Darling et al., Developing Alternative Methods for Determining the Incidence, Prevalence, and Cost Burden of Coronary Heart Disease in a Corporate Population, Journal of Occupational and Environmental Medicine, vol.54, issue.8, pp.541026-1038
DOI : 10.1097/JOM.0b013e318256f636

K. Dombkowski, K. Lamarand, S. Dong, W. Perng, and S. Clark, Using Medicaid Claims to Identify Children With Asthma, Journal of Public Health Management and Practice, vol.18, issue.3, pp.196-203
DOI : 10.1097/PHH.0b013e31821a3fa7

H. Bauer, G. Wright, and J. Chow, Evidence of Human Papillomavirus Vaccine Effectiveness in Reducing Genital Warts: An Analysis of California Public Family Planning Administrative Claims Data, 2007???2010, American Journal of Public Health, vol.102, issue.5, pp.833-835
DOI : 10.2105/AJPH.2011.300465

C. Van-walraven, P. Austin, D. Manuel, G. Knoll, A. Jennings et al., The usefulness of administrative databases for identifying disease cohorts is increased with a multivariate model, Journal of Clinical Epidemiology, vol.63, issue.12, pp.631332-1341, 2010.
DOI : 10.1016/j.jclinepi.2010.01.016

C. Aboa-eboulé, D. Mengue, E. Benzenine, M. Hommel, M. Giroud et al., How accurate is the reporting of stroke in hospital discharge data? A pilot validation study using a population-based stroke registry as control, Journal of Neurology, vol.69, issue.2, pp.605-613, 2013.
DOI : 10.1007/s00415-012-6686-0

C. Quantin, E. Benzenine, C. Ferdynus, M. Sediki, B. Auverlot et al., Advantages and limitations of using national administrative data on obstetric blood transfusions to estimate the frequency of obstetric hemorrhages, Journal of Public Health, vol.35, issue.1, pp.147-156, 2013.
DOI : 10.1093/pubmed/fds057
URL : https://hal.archives-ouvertes.fr/hal-01194204

C. Quantin, E. Benzenine, M. Hägi, B. Auverlot, M. Abrahamowicz et al., Danzon A: Estimation of national colorectal-cancer incidence using claims databases, J Cancer Epidemiol, p.298369, 2012.

M. Husain, S. Brophy, S. Macey, L. Pinder, M. Atkinson et al., HERALD (Health Economics using Routine Anonymised Linked Data), BMC Medical Informatics and Decision Making, vol.10, issue.3, p.24, 2012.
DOI : 10.1002/sim.4780100406

R. Fetter, Y. Shin, J. Freeman, R. Averill, and J. Thompson, Case mix definition by diagnosis-related groups, Med Care, vol.18, issue.2, pp.1-53, 1980.

U. Fayyad, G. Piatetsky-shapiro, and P. Smyth, The KDD process for extracting useful knowledge from volumes of data, Communications of the ACM, vol.39, issue.11, pp.2927-2961, 1996.
DOI : 10.1145/240455.240464

R. Wille, Restructuring lattice theory: an approach based on hierarchies of concepts, Ordered Sets. NATO Advanced Study Institutes Series, 1982.

R. Agrawal, T. Imielski, and A. Swami, Mining association rules between sets of items in large databases, Proceedings of the ACM SIGMOD Int'l Conference on Management of Data, pp.207-216, 1993.

N. Pasquier, Y. Bastide, R. Taouil, and L. Lakhal, Efficient mining of association rules using closed itemset lattices, Information Systems, vol.24, issue.1, pp.25-46, 1999.
DOI : 10.1016/S0306-4379(99)00003-4

M. Zaki, C. Hsiao, R. Grossman, J. Han, V. Kumar et al., CHARM: An Efficient Algorithm for Closed Itemset Mining, SDM, 2002.
DOI : 10.1137/1.9781611972726.27

J. Wang, J. Han, and P. J. , CLOSET+, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '03, pp.236-245
DOI : 10.1145/956750.956779

P. Valtchev, R. Missaoui, and R. Godin, Formal Concept Analysis for Knowledge Discovery and Data Mining: The New Challenges, In ICFCA Lecture Notes in Computer Science, vol.2961, pp.352-371, 2004.
DOI : 10.1007/978-3-540-24651-0_30

R. Cole and P. Eklund, Scalability in Formal Concept Analysis, Computational Intelligence, vol.15, issue.1, pp.11-27, 1999.
DOI : 10.1111/0824-7935.00079

G. Jiang, K. Ogasawara, A. Endoh, and T. Sakurai, Context-based ontology building support in clinical domains using formal concept analysis, International Journal of Medical Informatics, vol.71, issue.1
DOI : 10.1016/S1386-5056(03)00092-3

N. Jay, F. Kohler, A. Napoli, S. Yahia, E. Nguifo et al., Using Formal Concept Analysis for Mining and Interpreting Patient Flows within a Healthcare Network, Concept Lattices and Their Applications, pp.263-268
DOI : 10.1007/978-3-540-78921-5_19
URL : https://hal.archives-ouvertes.fr/inria-00109863

A. Kumar, C. Srinivas, and S. , MINING ASSOCIATIONS IN HEALTH CARE DATA USING FORMAL CONCEPT ANALYSIS AND SINGULAR VALUE DECOMPOSITION, Journal of Biological Systems, vol.18, issue.04, pp.787-807, 2010.
DOI : 10.1142/S0218339010003512

M. Kaytoue, S. Kuznetsov, A. Napoli, and S. Duplessis, Mining gene expression data with pattern structures in formal concept analysis, Information Sciences, vol.181, issue.10, pp.1811989-2001, 2011.
DOI : 10.1016/j.ins.2010.07.007
URL : https://hal.archives-ouvertes.fr/hal-00541100

C. Kumar, FUZZY CLUSTERING-BASED FORMAL CONCEPT ANALYSIS FOR ASSOCIATION RULES MINING, Applied Artificial Intelligence, vol.21, issue.21, pp.274-301
DOI : 10.1080/08839514.2012.648457

G. Stumme, R. Taouil, Y. Bastide, N. Pasquier, and L. Lakhal, Computing iceberg concept lattices with Titanic, Data & Knowledge Engineering, vol.42, issue.2, pp.189-222, 2002.
DOI : 10.1016/S0169-023X(02)00057-5
URL : https://hal.archives-ouvertes.fr/hal-00578830

S. Kuznetsov, S. Obiedkov, R. C. Polovina, S. Hill, and R. , Reducing the Representation Complexity of Lattice-Based Taxonomies, Proc. of ICCS 15th Intl Conf Conceptual Structures, pp.241-254
DOI : 10.1007/978-3-540-73681-3_18

N. Jay, F. Kohler, and A. Napoli, Analysis of Social Communities with Iceberg and Stability-Based Concept Lattices, International Conference on Formal Concept Analysis (ICFCA'08, pp.258-272
DOI : 10.1007/978-3-540-78137-0_19
URL : https://hal.archives-ouvertes.fr/hal-00608180

L. Breiman, J. Friedman, C. Stone, and R. Olshen, Classification and Regression Trees, 1984.

T. Therneau, B. Atkinson, and R. B. , Rpart: Recursive Partitioning R package version 4.1-3, 2013.

. Ministère-des-affaires-sociales-et-de-la-santé, Guide méthodologique de production des informations relatives à l'activité médicale et à sa facturation en médecine, chirurgie, obstétrique et odontologie, Bulletin officiel, p.6, 2012.

C. Couris, A. Schott, R. Ecochard, E. Morgon, and C. C. , A literature review to assess the use of claims databases in identifying incident cancer cases, Health Services and Outcomes Research Methodology, vol.4, issue.1, pp.49-63, 2003.
DOI : 10.1023/A:1025828911298
URL : https://hal.archives-ouvertes.fr/hal-00427396

N. Mitton, M. Colonna, B. Trombert, F. Olive, F. Gomez et al., A Suitable Approach to Estimate Cancer Incidence in Area without Cancer Registry, Journal of Cancer Epidemiology, vol.28, issue.4, p.418968, 2011.
DOI : 10.1016/j.healthplace.2005.08.005
URL : https://hal.archives-ouvertes.fr/hal-00698065

C. Quantin, E. Benzenine, M. Fassa, M. Hägi, E. Fournier et al., DanzonA:Evaluation of the interest of using discharge abstract databases to estimate breast cancer incidence in two french departments, Stat J IAOS: J Int Assoc Official Stat, vol.2012, issue.281, pp.73-85

B. Starfield, J. Weiner, L. Mumford, and D. Steinwachs, Ambulatory care groups: a categorization of diagnoses for research and management, Health Serv Res, vol.26, issue.1, pp.53-74, 1991.

T. Grubinger, C. Kobel, and K. Pfeiffer, Regression tree construction by bootstrap: Model search for DRG-systems applied to Austrian health-data, BMC Medical Informatics and Decision Making, vol.8, issue.3, p.9, 2010.
DOI : 10.1186/1472-6947-8-6

M. Smidth, I. Sokolowski, L. Kaersvang, and P. Vedsted, Developing an algorithm to identify people with Chronic Obstructive Pulmonary Disease (COPD) using administrative data, BMC Medical Informatics and Decision Making, vol.364, issue.1, p.38
DOI : 10.1016/S0140-6736(04)16855-4

E. Benchimol, D. Manuel, T. To, A. Griffiths, L. Rabeneck et al., Development and use of reporting guidelines for assessing the quality of validation studies of health administrative data, Journal of Clinical Epidemiology, vol.64, issue.8
DOI : 10.1016/j.jclinepi.2010.10.006