A new health classification scheme based on fuzzy hesitant information

The evaluation of the health status of a population is a key question in Health Policy. The measurement of the health status is a relevant process to keep and improve the countries’ level of economic development. In spite of this relevance, the current evaluation methodologies are not suciently well-defined either designed due to the fact that health is an inherently subjective notion. In order to overcome these drawbacks, first of all we propose a newer way to manage such uncertainty by means of the Fuzzy Logic Theory. Regarding the methodology, we develop a new approach to classify populations according to their health status based on hesitant fuzzy information. Additionally, we apply the proposed mechanism on real health data from 15 European countries.

[1]  Hsing Hung Chen,et al.  Prioritization and operations NPD mix in a network with strategic partners under uncertainty , 2007, Expert Syst. Appl..

[2]  Zeshui Xu,et al.  The TODIM analysis approach based on novel measured functions under hesitant fuzzy environment , 2014, Knowl. Based Syst..

[3]  Suman Seth,et al.  Inequality, Interactions, and Human Development , 2009 .

[4]  Francisco Herrera,et al.  Hesitant Fuzzy Sets: State of the Art and Future Directions , 2014, Int. J. Intell. Syst..

[5]  Carmen Herrero,et al.  Multidimensional Social Evaluation: An Application to the Measurement of Human Development , 2010 .

[6]  J. Ware,et al.  Choosing measures of health status for individuals in general populations. , 1981, American journal of public health.

[7]  Na Chen,et al.  Correlation coefficients of hesitant fuzzy sets and their applications to clustering analysis , 2013 .

[8]  D. Hausman.  Valuing health: a new proposal. , 2010, Health economics.

[9]  James E Foster,et al.  Measuring health inequality using qualitative data. , 2004, Journal of health economics.

[10]  Ivor Grattan-Guinness,et al.  Fuzzy Membership Mapped onto Intervals and Many-Valued Quantities , 1976, Math. Log. Q..

[11]  P Rao,et al.  Measurement of trends in health status. , 1990, World health forum.

[12]  Satya R. Chakravarty,et al.  A Generalized Human Development Index , 2003 .

[13]  Lotfi A. Zadeh,et al.  Outline of a New Approach to the Analysis of Complex Systems and Decision Processes , 1973, IEEE Trans. Syst. Man Cybern..

[14]  V. Torra,et al.  A framework for linguistic logic programming , 2010 .

[15]  Miguel Szekely,et al.  Please Scroll down for Article Journal of Human Development Measuring the Distribution of Human Development: Methodology and an Application to Mexico , 2022 .

[16]  Zeshui Xu,et al.  Satisfaction Degree Based Interactive Decision Making under Hesitant Fuzzy Environment with Incomplete Weights , 2014, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[17]  Frank de Charro,et al.  The Measurement and Valuation of Health Status Using EQ-5D: A European Perspective , 2003, Springer Netherlands.

[18]  B. Farhadinia,et al.  A Novel Method of Ranking Hesitant Fuzzy Values for Multiple Attribute Decision‐Making Problems , 2013, Int. J. Intell. Syst..

[19]  Carmen Herrero,et al.  A Newer Human Development Index , 2012 .

[20]  Carmen Herrero,et al.  On the Comparison of Group Performance with Categorical Data , 2013, PloS one.

[21]  Marc Roubens,et al.  Fuzzy Preference Modelling and Multicriteria Decision Support , 1994, Theory and Decision Library.

[22]  Zeshui Xu,et al.  Hesitant Fuzzy Sets Theory , 2014, Studies in Fuzziness and Soft Computing.

[23]  Mark Oppe,et al.  EQ-5D value sets : inventory, comparative review, and user guide , 2007 .

[24]  A. Williams.  EuroQol : a new facility for the measurement of health-related quality of life , 1990 .

[25]  Zeshui Xu,et al.  Hesitant fuzzy information aggregation in decision making , 2011, Int. J. Approx. Reason..

[26]  N. Beaulieu.  Quality information and consumer health plan choices. , 2002, Journal of health economics.

[27]  Janusz Kacprzyk,et al.  Group decision making under fuzziness , 1999 .

[28]  T. Tanino.  Fuzzy preference orderings in group decision making , 1984 .