Abstract
Multi-criteria decision making (MCR) has a rich history, employed since the early 1950s to mathematically model decision problems and identify optimal solutions from a set of alternatives. Recently, MCR has found applications in biomedical engineering and healthcare big data. The healthcare domain, characterized by a multi-stakeholder perspective involving patients, doctors, medical device manufacturers, and insurers, presents complex decision-making challenges. With diverse criteria and extensive healthcare records, it becomes challenging to make fair decisions. This paper outlines the requirements for a fair decision-making algorithm, highlighting the limitations of MCR in meeting fairness criteria. An algorithmic framework incorporating fairness criteria is presented, employing a similarity-based approach for decision-making on Electronic Health Records (EHR) to predict prospective cohort groups for a target patient.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Schey, C., Postma, M.J., Krabbe, P.F.M., Topachevskyi, O., Volovyk, A., Connolly, M.: Assessing the preferences for criteria in multi-criteria decision analysis in treatments for rare diseases. Front. Public Health 8, 1–10 (2020)
Piniazhoko, O., Ne´meth, B.: Practical issues of determining weights for criteria to be used in an MCDA framework - based on a case study. In: ISPOR 22nd Annual International Meeting, Boston, MA, USA, p. 1 (2017)
Ozsahin, I., Ozsahin, D.U., Uzun, B., Mustapha, M.T.: Introduction - chapter 1. In: Applications of Multi-Criteria Decision-Making Theories in Healthcare and Biomedical Engineering, Elsivier - Academic Press, pp. 1–2 (2021)
Taherdoost, H., Madanchian, M.: Multi-criteria decision making (MCDM) methods and concepts. Encyclopedia 2023, 77–87 (2023)
Dehe, B., Bamford, D.: Development, test and comparison of two multiple criteria decision analysis (MACDA) models: a case of healthcare infrastructure location. Expert Syst. Appl. 2015, 1–11 (2021)
Barkaoui, H., Rejeb, H. B., Barkaoui, A., Tavares, J.M.R.: Multi-criteria decision making for medical device development. Eng. Manag. J. 35, 1–18 (2022)
Stevi´c´, Z., Pamuc˘ar, D., Pus˘ka, A., Chatterjee, P.: Sustainable supplier selection in health-care industries using a new MCDM method: measurement of alternatives and ranking according to compromise solution (MARCOS). Comput. Ind. Eng. 140, 106231 (2020)
Anvari, A.S.: The application of MCDM methods in covid-19 pandemic: a state of the art review. Appl. Soft Comput.Comput. 126, 1–40 (2022)
Angelis, A., Kanavos, P.: Multiple criteria decision analysis (MCDA) for evaluating new medicines in health technology assessment and beyond: the advance value framework. Soc Sci Medoc. Sci. Med. 188, 137–156 (2017)
Zhao, J., Gao, S., Wang, J., Liu, X., Hao, Y.: Differentiation between two healthcare concepts: person-centered and patient-centered care. Int. J. Nurs. Sci. 3, 398–402 (2016)
Barry, M.J., Edgman-Levitan, S.: Shared decision making - the pinnacle of patient-centered care. N. Engl. J. Med. 366(9), 78–781 (2012)
Constand, M.K., Macdermid, J.C., Bello-Has, V.D., Law, M.: Scoping review of patient- centered care approaches in healthcare. BMC Health Serv. Res. 14(271), 1–9 (2014)
Jayadevappa, R., Chhatre, S.: Patient centered care - a conceptual model and review of the state of the art. Open Health Serv. Policy J. 4, 15–25 (2011)
Kaltoft, M., Cunich, M., Salkeld, G., Dowie, J.: Assessing decision quality in patient- centered care requires a preference-sensitive measure. J. Health Serv. Res. Policy 19(2), 110–117 (2014)
Ogden, K., Barr, J., Greenfield, D.: Determining requirements for patient-centered care: a participatory concept making study. BMC Health Serv. Res. 17(780), 1–11 (2017)
Wan, K., Alagar, V.: Context-aware, knowledge-intensive, and patient-centric mobile health care model. In: 12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD), Zhangjiajie, China, pp. 2253–2260 (2015)
Ottawa Hospital Research Institute, Patient decision aids (2022)
Hsu, C.C., Sandford, B.A.: The delphi technique: making sense of consensus. Pract. Assess. Res. Eval. Assess. Res. Eval. 12(1), 1–10 (2007)
Okoli, C., Pawlowski, S.D.: The delphi method as a research tool: an example, design considerations and applications. Inf. Manag. 42(1), 15–29 (2004)
Strozyna, M., Elden, G., Filipiak, W.A.D., Malyszko, J., Wecel, K.: A framework for the quality-based selection and retrieval of open data - a use case from the maritime domain. Electr. Markets 28, 219–233 (2018)
Alsaig, A., Alagar, V., Mohammad, M., Alhalabi, W.: A user-centric semantic-based algorithm for ranking services: design and analysis. Serv. Oriented Comput. Appli. 11(1), 101–120 (2017)
Liu, Y.: A family of algorithms for patient similarity based on electronic health records, Master’s thesis, Concordia University, Montreal, Canada (2022). http://spectrum.library.concordia.ca
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Alsaig, A., Alsaig, A., Alagar, V. (2024). A Critical Review of Multi Criteria Decision Analysis Method for Decision Making and Prediction in Big Data Healthcare Applications. In: Huang, DS., Premaratne, P., Yuan, C. (eds) Applied Intelligence. ICAI 2023. Communications in Computer and Information Science, vol 2015. Springer, Singapore. https://doi.org/10.1007/978-981-97-0827-7_8
Download citation
DOI: https://doi.org/10.1007/978-981-97-0827-7_8
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-97-0826-0
Online ISBN: 978-981-97-0827-7
eBook Packages: Computer ScienceComputer Science (R0)