×

Multi-criteria and medical diagnosis for application to health insurance systems: a general approach through non-additive measures. (English) Zbl 1465.91091

Summary: In this contribution, we propose a healthcare decision support system. Nowadays, it is commonly recognized that quantitative tools and decision support can increase the benefits and the performances of healthcare systems, and for this, different multiple criteria methods were proposed in many branches of medicine. The approach we propose is based on non-additive measures and the Choquet integral. This methodology has been intensively applied in many real-world applications, given its capability to represent interactions among criteria, and thus to model a wide range of preference structures. Considering that the diagnosis procedure needs also to take the clinical expertise into account, this method appears particularly tailored for a diagnosis support, mainly when statistical models cannot be applied and/or available data are scarce and knowledge can be inferred by physicians’ opinions. In particular, we propose a disease risk evaluation and compute some associated indicators. Furthermore, an error estimation is performed. As an application, a cardiovascular risk diagnosis model is presented. The proposed methodology, that allows to quantify the disease risk taking into account individual’s medical conditions, can be used for improving healthcare service quality or for pricing and reserving health insurance policies. An application to health insurance pricing is provided.

MSC:

91G05 Actuarial mathematics
92C50 Medical applications (general)
91B06 Decision theory
62C86 Statistical decision theory and fuzziness
Full Text: DOI

References:

[1] Angilella, S.; Corrente, S.; Greco, S., Stochastic multiobjective acceptability analysis for the Choquet integral preference model and the scale construction problem, Eur. J. Oper. Res., 240, 1, 172-182 (2015) · Zbl 1339.90163
[2] Anzilli, L., Giove, S.: Cardiovascular disease risk assessment using the Choquet integral. In: International Workshop on Fuzzy Logic and Applications, pp. 45-53. Springer (2016)
[3] Baione, F.; Levantesi, S., A health insurance pricing model based on prevalence rates: application to critical illness insurance, Insur. Math. Econ., 58, 174-184 (2014) · Zbl 1304.91089
[4] Baltussen, R.; Niessen, L., Priority setting of health interventions: the need for multi-criteria decision analysis, Cost Eff. Resour. Alloc., 4, 1, 14 (2006)
[5] Bennis, I.; Janah, S.; Benajiba, M., Improvement and process optimization transfusion in Morocco: proposal of a new organization, Transfusion clinique et biologique: journal de la Societe francaise de transfusion sanguine, 20, 1, 21-29 (2013)
[6] Bordley, R.; LiCalzi, M., Decision analysis using targets instead of utility functions, Decis. Econ. Finance, 23, 1, 53-74 (2000) · Zbl 1051.91503
[7] Calvo, T.; Mayor, G.; Mesiar, R., Aggregation Operators: New Trends and Applications (2012), Heidelberg: Physica, Heidelberg
[8] Carvalho, D.; Pinheiro, PR; Pinheiro, MCD, A hybrid model to support the early diagnosis of breast cancer, Procedia Comput. Sci., 91, 927-934 (2016)
[9] Chiclana, F.; Tapia García, JM; del Moral, MJ; Herrera-Viedma, E., A statistical comparative study of different similarity measures of consensus in group decision making, Inf. Sci., 221, 110-123 (2013)
[10] Choquet, G.: Theory of capacities. In: Annales de l’institut Fourier, vol. 5, pp. 131-295. Institut Fourier (1954) · Zbl 0064.35101
[11] Cordeiro, IMF, Transition intensities for a model for Permanent Health Insurance 1, ASTIN Bull. J. IAA, 32, 2, 319-346 (2002) · Zbl 1091.91517
[12] Dash, A.; Grimshaw, D., Dread disease cover—an actuarial perspective, J. Staple Inn Actuar. Soc., 33, 1, 149-193 (1993)
[13] de Andrés-Sánchez, J., Puchades, L.G.V., Zhang, A.: Incorporating fuzzy information in pricing substandard annuities. Comput. Ind. Eng. 145, (2020). doi:10.1016/j.cie.2020.106475
[14] Deza, M.M., Deza, E.: Encyclopedia of distances. In: Encyclopedia of Distances, pp. 1-583. Springer (2009) · Zbl 1167.51001
[15] Diaby, V.; Campbell, K.; Goeree, R., Multi-criteria decision analysis (MCDA) in health care: a bibliometric analysis, Oper. Res. Health Care, 2, 1-2, 20-24 (2013)
[16] Dolan, JG; Boohaker, E.; Allison, J.; Imperiale, TF, Can streamlined multicriteria decision analysis be used to implement shared decision making for colorectal cancer screening?, Med. Decis. Mak., 34, 6, 746-755 (2014)
[17] Dujmović, J.J., Ralph, J.W., Dorfman, L.J.: Evaluation of disease severity and patient disability using the lsp method. In: Proceedings of the 12th Information Processing and Management of Uncertainty International Conference (IPMU 2008), pp. 1398-1405 (2008)
[18] Feinstein, AR, Clinimetric perspectives, J. Chronic Dis., 40, 6, 635-640 (1987)
[19] Gatzert, N.; Klotzki, U., Enhanced annuities: drivers of and barriers to supply and demand, Geneva Pap. Risk Insur. Issues Pract., 41, 1, 53-77 (2016)
[20] Giove, S., Nordio, M., Zorat, A.: An adaptive fuzzy control module for automatic dialysis. In: Austrian Conference on Fuzzy Logic in Artificial Intelligence, pp. 146-156. Springer (1993)
[21] Giove, S., Azar, A.T., Nordio, M.: Fuzzy logic control for dialysis application. In: Modeling and Control of Dialysis Systems, pp. 1181-1222. Springer (2013)
[22] Glaize, A.; Duenas, A.; Di Martinelly, C.; Fagnot, I., Healthcare decision-making applications using multicriteria decision analysis: a scoping review, J. Multi-Criteria Decis. Anal., 26, 1-2, 62-83 (2019)
[23] Grabisch, M., Alternative representations of discrete fuzzy measures for decision making, Int. J. Uncertain. Fuzziness Knowl. Based Syst., 5, 5, 587-607 (1997) · Zbl 1232.28019
[24] Grabisch, M., K-order additive discrete fuzzy measures and their representation, Fuzzy Sets Syst., 92, 2, 167-189 (1997) · Zbl 0927.28014
[25] Grabisch, M.; Labreuche, C., A decade of application of the Choquet and Sugeno integrals in multi-criteria decision aid, Ann. Oper. Res., 175, 1, 247-286 (2010) · Zbl 1185.90118
[26] Grabisch, M., Labreuche, C.: Fuzzy measures and integrals in MCDA. In: Multiple Criteria Decision Analysis, pp. 553-603. Springer (2016) · Zbl 1072.90533
[27] Grabisch, M.; Sugeno, M.; Murofushi, T., Fuzzy Measures and Integrals: Theory and Applications (2000), New York: Springer, New York · Zbl 1113.91313
[28] Grabisch, M., Marichal, J.L., Mesiar, R., Pap, E.: Aggregation functions. In: Encyclopedia of Mathematics and Its Applications, vol. 127 (2009) · Zbl 1196.00002
[29] Haberman, S.; Pitacco, E., Actuarial Models for Disability Insurance (1998), Boca Raton: CRC Press, Boca Raton · Zbl 0935.62118
[30] Horgby, PJ; Lohse, R.; Sittaro, NA, Fuzzy underwriting: an application of fuzzy logic to medical underwriting, J. Actuar. Pract. 1993-2006, 5, 1, 79-104 (1997) · Zbl 1061.91502
[31] Kianifard, F., Evaluation of clinimetric scales: basic principles and methods, J. R. Stat. Soc. Ser. D (Stat.), 43, 4, 475-482 (1994)
[32] Klement, EP; Mesiar, R.; Pap, E., Triangular Norms (2013), Berlin: Springer, Berlin
[33] Kojadinovic, I., An axiomatic approach to the measurement of the amount of interaction among criteria or players, Fuzzy Sets Syst., 152, 3, 417-435 (2005) · Zbl 1142.91327
[34] Kuo, RJ; Wu, YH; Hsu, TS, Integration of fuzzy set theory and topsis into hfmea to improve outpatient service for elderly patients in taiwan, J. Chin. Med. Assoc., 75, 7, 341-348 (2012)
[35] Labreuche, C.; Grabisch, M., The choquet integral for the aggregation of interval scales in multicriteria decision making, Fuzzy Sets Syst., 137, 1, 11-26 (2003) · Zbl 1052.91031
[36] Lazzari, LL; Moulia, PI, Fuzzy sets application to healthcare systems, Fuzzy Econ. Rev., 17, 2, 43 (2012)
[37] Lee, YC; Chung, PH; Shyu, JZ, Performance evaluation of medical device manufacturers using a hybrid fuzzy MCDM, J. Sci. Ind. Res., 76, 1, 28-31 (2017)
[38] Lesot, MJ; Rifqi, M.; Benhadda, H., Similarity measures for binary and numerical data: a survey, Int. J. Knowl. Eng. Soft Data Paradigms, 1, 1, 63-84 (2009)
[39] Lu, C.; You, JX; Liu, HC; Li, P., Health-care waste treatment technology selection using the interval 2-tuple induced topsis method, Int. J. Environ. Res. Public Health, 13, 6, 562 (2016)
[40] Mardani, A.; Hooker, RE; Ozkul, S.; Yifan, S.; Nilashi, M.; Sabzi, HZ; Fei, GC, Application of decision making and fuzzy sets theory to evaluate the healthcare and medical problems: a review of three decades of research with recent developments, Expert Syst. Appl., 137, 202-231 (2019)
[41] Marichal, JL, An axiomatic approach of the discrete Choquet integral as a tool to aggregate interacting criteria, IEEE Trans. Fuzzy Syst., 8, 6, 800-807 (2000)
[42] Marichal, J.L.: Aggregation of interacting criteria by means of the discrete Choquet integral. In: Aggregation Operators, pp. 224-244. Springer (2002) · Zbl 1041.28015
[43] Marichal, JL, Tolerant or intolerant character of interacting criteria in aggregation by the Choquet integral, Eur. J. Oper. Res., 155, 3, 771-791 (2004) · Zbl 1044.90074
[44] Marsh, K.; Goetghebeur, M.; Thokala, P.; Baltussen, R., Multi-criteria Decision Analysis to Support Healthcare Decisions (2017), Berlin: Springer, Berlin
[45] Murofushi, T., Soneda, S.: Techniques for reading fuzzy measures (III): interaction index. In: 9th Fuzzy System Symposium, pp. 693-696. Sapporo, Japan (1993)
[46] Nunes, L.C., Pinheiro, P.R., Pequeno, T.C., Pinheiro, M.C.D.: Toward an application to psychological disorders diagnosis. In: Software Tools and Algorithms for Biological Systems, pp. 573-580. Springer (2011)
[47] Nutt, DJ; King, LA; Phillips, LD, Drug harms in the UK: a multicriteria decision analysis, Lancet, 376, 9752, 1558-1565 (2010)
[48] Pedrycz, W., Direct and inverse problem in comparison of fuzzy data, Fuzzy Sets Syst., 34, 2, 223-235 (1990)
[49] Pedrycz, W., Neurocomputations in relational systems, IEEE Trans. Pattern Anal. Mach. Intell., 13, 3, 289-297 (1991)
[50] Pinar, M.; Cruciani, C.; Giove, S.; Sostero, M., Constructing the feem sustainability index: a Choquet integral application, Ecol. Ind., 39, 189-202 (2014)
[51] Pitacco, E.: Life annuities. Products, guarantees, basic actuarial models. CEPAR Working Paper 2017/6 (2017)
[52] Pitacco, E., Health Insurance. Basic Actuarial Models (2014), Cham: Springer, Cham · Zbl 1300.91002
[53] Pitacco, E., Heterogeneity in mortality: a survey with an actuarial focus, Eur. Actuar. J., 9, 1, 3-30 (2019) · Zbl 1422.91373
[54] Polat, K.; Güneş, S.; Tosun, S., Diagnosis of heart disease using artificial immune recognition system and fuzzy weighted pre-processing, Pattern Recognit., 39, 11, 2186-2193 (2006)
[55] Sanz, JA; Galar, M.; Jurio, A.; Brugos, A.; Pagola, M.; Bustince, H., Medical diagnosis of cardiovascular diseases using an interval-valued fuzzy rule-based classification system, Appl. Soft Comput., 20, 103-111 (2014)
[56] Siskos, Y., Grigoroudis, E., Matsatsinis, N.F.: UTA methods. In: Multiple Criteria Decision Analysis, pp. 315-362. Springer (2016) · Zbl 1072.90547
[57] Smith, RL, Efficient monte carlo procedures for generating points uniformly distributed over bounded regions, Oper. Res., 32, 6, 1296-1308 (1984) · Zbl 0552.65004
[58] Staessen, J., Petrov, V., Fagard, R.: Cardiovascular risk associated with hypertension; interactions with other risk indicators. In: Practical Management of Hypertension, pp. 59-69. Springer (1996)
[59] Streiner, DL; Norman, GR; Cairney, J., Health Measurement Scales: A Practical Guide to Their Development and Use (2015), Oxford: Oxford University Press, Oxford
[60] Sun, L.; Dong, H.; Liu, AX, Aggregation functions considering criteria interrelationships in fuzzy multi-criteria decision making: state-of-the-art, IEEE Access, 6, 68104-68136 (2018)
[61] Tervonen, T.; van Valkenhoef, G.; Baştürk, N.; Postmus, D., Hit-and-run enables efficient weight generation for simulation-based multiple criteria decision analysis, Eur. J. Oper. Res., 224, 3, 552-559 (2013) · Zbl 1292.91057
[62] Timonin, M., Robust optimization of the Choquet integral, Fuzzy Sets Syst., 213, 27-46 (2013) · Zbl 1291.90339
[63] Tsipouras, MG; Voglis, C.; Fotiadis, DI, A framework for fuzzy expert system creation-application to cardiovascular diseases, IEEE Trans. Biomed. Eng., 54, 11, 2089-2105 (2007)
[64] Vahidnia, MH; Alesheikh, AA; Alimohammadi, A., Hospital site selection using fuzzy AHP and its derivatives, J. Environ. Manag., 90, 10, 3048-3056 (2009)
[65] van Valkenhoef, G.; Tervonen, T.; Postmus, D., Notes on hit-and-run enables efficient weight generation for simulation-based multiple criteria decision analysis, Eur. J. Oper. Res., 239, 3, 865-867 (2014) · Zbl 1339.90331
[66] Yager, RR, The power average operator, IEEE Trans. Syst. Man Cybern. Part A Syst. Hum., 31, 6, 724-731 (2001)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.