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Coordination between hospitals and insurers in developing economies: an interpretive structural modeling approach

Coordination between hospitals and insurers in developing economies: an interpretive structural... The purpose of this paper is to identify the factors that influence hospitals’ selection by health-care insurers in India and to establish a hierarchical model representing the relationship among different factors and their influence on the entire scenario.Design/methodology/approachA survey with a set of questionnaires was conducted with different health-care insurer executives of reputed health insurance companies. The data has been gathered by using a five-point Likert scale. Their opinions were converted into a reachability matrix and an interpretive structural modeling was constructed. The final results obtained were verified by using fuzzy Matriced Impacts Croises-Multiplication Applique and Classement analysis.FindingsThe results suggested three key driving factors, National Accreditation Board for Hospitals & Healthcare Providers accreditation of the hospital, purchasing power of people in the region and national and international recognition of the hospital among the eleven factors selected for the study.Research limitations/implicationsThe research mainly focuses on the health insurance benefits provided by privately owned insurance companies and do not comment on any government’s mass health insurance scheme.Practical implicationsWith a small proportion of people under the umbrella of health insurance in India, these factors will assist and expedite insurer’s effort to penetrate deep into rural and urban areas enhancing availability and escalating affordability.Originality/valueThis paper presents key factors responsible for better coordination between health-care systems and insurance companies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Pharmaceutical and Healthcare Marketing Emerald Publishing

Coordination between hospitals and insurers in developing economies: an interpretive structural modeling approach

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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1750-6123
DOI
10.1108/ijphm-10-2019-0068
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to identify the factors that influence hospitals’ selection by health-care insurers in India and to establish a hierarchical model representing the relationship among different factors and their influence on the entire scenario.Design/methodology/approachA survey with a set of questionnaires was conducted with different health-care insurer executives of reputed health insurance companies. The data has been gathered by using a five-point Likert scale. Their opinions were converted into a reachability matrix and an interpretive structural modeling was constructed. The final results obtained were verified by using fuzzy Matriced Impacts Croises-Multiplication Applique and Classement analysis.FindingsThe results suggested three key driving factors, National Accreditation Board for Hospitals & Healthcare Providers accreditation of the hospital, purchasing power of people in the region and national and international recognition of the hospital among the eleven factors selected for the study.Research limitations/implicationsThe research mainly focuses on the health insurance benefits provided by privately owned insurance companies and do not comment on any government’s mass health insurance scheme.Practical implicationsWith a small proportion of people under the umbrella of health insurance in India, these factors will assist and expedite insurer’s effort to penetrate deep into rural and urban areas enhancing availability and escalating affordability.Originality/valueThis paper presents key factors responsible for better coordination between health-care systems and insurance companies.

Journal

International Journal of Pharmaceutical and Healthcare MarketingEmerald Publishing

Published: Dec 10, 2020

Keywords: Fuzzy MICMAC; Interpretive structural modeling (ISM); Health-care insurance; Health-care system modeling

References