Abstract
This paper explores preferences towards cardiological e-health services, assessed on a representative quota sample of potential users in Sardinia, Italy. By a mixture model approach, it is possible to observe individual response behaviour expressed in terms of agreement and heterogeneity. While a substantial heterogeneity emerges for modes of consultation, the ranking of respondents’ preferences is clearly depicted for the location. The findings highlight a strong preference for a cardiological consultation at the family doctor and for the province of residence as a location. Notably, education and age are the covariates that most importantly affect choice processes.
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Agresti, A.: Analysis of Ordinal Categorical Data, 2nd edn. Wiley, Hoboken (2010)
Aneja, S., Ross, J.S., Wang, Y., Matsumoto, M., Rodgers, G.P., Bernheim, S.M., Rathore, S.S., Krumholz, H.M.: US cardiologist workforce from 1995 to 2007: modest growth, lasting geographic maldistribution especially in rural areas. Health Aff. 30(12), 2301–09 (2011)
Basoglu, N., Daim, T.U., Topacan, U.: Determining patient preferences for remote monitoring. J. Med. Syst. 36(3), 1389–401 (2012)
Capecchi, S., Iannario, M.: Gini heterogeneity index for detecting uncertainty in ordinal data surveys. METRON 74(2), 223–232 (2016)
Capecchi, S., Piccolo, D.: Dealing with heterogeneity in ordinal responses. Qual. Quant. 51(5), 2375–2393 (2017)
Cowie, M.R., Bax, J., Bruining, N., Cleland, J.G., Koehler, F., Malik, M., Pinto, F., van der Velde, E., Vardas, P.: E-Health: a position statement of the European Society of Cardiology. Eur. Heart J. 37(1), 63–66 (2016)
CRENoS: Economia della Sardegna. \(24^{\circ }\) Rapporto, CUEC, Cagliari (2017)
D’Elia, A., Piccolo, D.: A mixture model for preference data analysis. Comput. Stat. Data Anal. 49(3), 917–934 (2005)
Dávalos, M.E., French, M.T., Burdick, A.E., Simmons, S.C.: Economic evaluation of telemedicine: review of the literature and research guidelines for benefit–cost analysis. Telemed. e Health 15(10), 933–948 (2009)
de Bekker-Grob, E.W., Ryan, M., Gerard, K.: Discrete choice experiments in health economics: a review of the literature. Health Econ. 21(2), 145–172 (2012)
European Commission: Europa 2020, a European strategy for smart, sustainable and inclusive growth. http://ec.europa.eu/eu2020/pdf (2010). Accessed 15 Feb 2018
GeoNue: Le regioni storiche della Sardegna. https://geonue.com/le-regioni-storiche-della-sardegna (2017). Accessed 15 Feb 2018
Gini, C.: Variabilità e mutabilità. Studi economico-giuridici, Facoltà di Giurisprudenza, Università di Cagliari, A, III, parte II (1912)
Iannario, M.: Modelling shelter choices in a class of mixture models for ordinal responses. Stat. Methods Appl. 21(1), 1–22 (2012)
Iannario, M., Piccolo, D.: A generalized framework for modelling ordinal data. Stat. Methods Appl. 25(2), 163–189 (2016a)
Iannario, M., Piccolo, D.: A comprehensive framework of regression models for ordinal data. METRON 74(2), 233–252 (2016b)
Iannario, M., Piccolo, D., Simone, R.: CUB: a class of mixture models for ordinal data. R package version 1.2.0. http://CRAN.R-project.org/package=CUB (2018). Accessed 15 Feb 2018
ISTAT: GeoDemo. http://demo.istat.it/pop2014/index.html (2017). Accessed 15 Feb 2018
Laakso, M., Taagepera, R.: Effective number of parties: a measure with application to West Europe. Comp. Political Stud. 12(1), 3–27 (1989)
Mahmud, N., Rodriguez, J., Nesbit, J.: A text message-based intervention to bridge the healthcare communication gap in the rural developing world. Technol. Health Care 18(2), 137–144 (2010)
Peterson, L.T., Ford, E.W., Eberhardt, J., Huerta, T.R., Menachemi, M.: Assessing differences between physicians’ realized and anticipated gains from electronic health record adoption. J. Med. Syst. 35(2), 151–161 (2011)
Piccolo, D.: On the moments of a mixture of uniform and shifted binomial random variables. Quad. Stat. 5, 85–104 (2003)
Tutz, G.: Regression for Categorical Data. Cambridge University Press, Cambridge (2012)
Yin, S., Huang, K., Shieh, J., Liu, Y., Wu, H.: Telehealth services evaluation: a combination of SERVQUAL model and importance–performance analysis. Qual. Quant. 50(2), 751–766 (2016)
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M. Pulina and M. Meleddu acknowledge the Fondazione Banco di Sardegna (FBS) for financing the project Prot.U823.2013-A1.747.MGB- Prat.2013.1441 - “La telemedicina: quantificazione della disponibilitá a pagare dei potenziali fruitori ed intermediar”. This work has been partially supported by CUBREMOT project at University of Naples Federico II.
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Capecchi, S., Meleddu, M. & Pulina, M. Quality evaluation and preferences of healthcare services: the case of telemedicine in Sardinia. Qual Quant 53, 2339–2351 (2019). https://doi.org/10.1007/s11135-018-0743-4
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DOI: https://doi.org/10.1007/s11135-018-0743-4