Modeling Cesarean Versus Natural Birth Data with Suspicious Zero Counts Should Be a Prelude to Healthcare Cost Analysis.

Anwar Hassan; Peer Bilal Ahmad; Ramalingam Shanmugam

Author(s)

Anwar Hassan Department of Statistics & Operations Research, King Saud University Riyadh, Saudi Arabia

Peer Bilal Ahmad Department of Mathematical Sciences, Islamic University of Science & Technology, Awantipora (J&K), India

Ramalingam Shanmugam School of Health Administration, Texas State University-San Marcos San Marcos, TX 78666, USA

Abstract

Skyrocketing healthcare cost is an alarming concern not only in the United States of America but also in many developing and developed nations. A prelude to any discussions of financial matters of healthcare is to secure the best fitting probability pattern of the data. For an example, why not consider and compare the probability patterns in the random number of cesarean ( X ) versus the random number of natural (Y ) childbirths in a day of the hospital data. A public opinion is that all cesarean births are really warranted and the healthcare cost could be considerably reduced if it can be eliminated. Their aggregate N = X + Y denotes the total number of births in a day of the chosen hospital. The general expression for the correlation coefficient, r , between X and Y reveals when N , follows a Zero Inflated Modified Power Series Distribution (ZIMPSD) introduced by Gupta, et al. (1995). Special expressions for Zero Inflated Generalized Negative Binomial Distribution (ZIGNBD) and Zero Inflated Generalized Poisson Distribution (ZIGPD) are obtained as particular cases.

Publication Details

Page(s) 33-46

DOI DOI not available

Published Journal: Pakistan Journal of Statistics, Volume: 34, Issue: 1, Year: 2018

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