scholarly journals The Fixed-Effects Zero-Inflated Poisson Model with an Application to Health Care Utilization

Author(s):  
Maria Cristina Majo ◽  
Arthur H. O. van Soest
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Changle Li ◽  
Zhengzhong Mao ◽  
Caixia Yu

Abstract Background Preventive risk factors such as smoking, drinking, and unhealthy weight have contributed to the accelerated rise in noncommunicable chronic diseases, which are dominant drivers of health care utilization and spending in China. However, few studies have been conducted using a large longitudinal dataset to explore the impact of such preventive risk factors on health care utilization. Therefore, this study aimed to ascertain the effects of smoking, regular drinking, and unhealthy weight on health care utilization in China. Methods This research was a longitudinal study using data from five waves of the China Family Panel Studies (CFPS) conducted between 2010 and 2018, and the final sample consisted of 63,260 observations (12,652 participants) across all five waves of data collection. Health care utilization was measured from two perspectives: outpatient utilization and inpatient utilization. Smoking status was categorized as never smoker, former smoker, or current smoker. Unhealthy weight was classified based on the participants’ body mass index. A fixed effects logistic regression model was used for the analysis. Results The results of fixed effects logistic regression showed that current and former smokers were approximately 1.9 times and 2.0 times more likely to use outpatient care than those who never smoked, respectively (odds ratio (OR) = 1.88, p < 0.05; OR = 2.03, p < 0.05). Obese people were approximately 1.3 times more likely to use outpatient care than healthy weight people (OR = 1.26, p < 0.05). Moreover, the results show that compared to those who never smoked, for current and former smokers, the odds of being hospitalized increased by 42.2 and 198.2%, respectively (OR = 1.42; p < 0.1, OR = 2.98; p < 0.05). Compared to healthy weight people, overweight and obese people were also more likely to be hospitalized (OR = 1.11; p < 0.1, OR = 1.18; p < 0.1, respectively). Conclusion Among Chinese adults, current and former smokers were more likely to use outpatient and inpatient care than those who had never smoked. Moreover, compared to healthy weight people, obese people were more likely to use outpatient and inpatient care, and overweight people were more likely to use inpatient care. These results may have important implications that support the government in making health care resource allocation decisions.


2021 ◽  
Vol 16 (2) ◽  
pp. 2767-2788
Author(s):  
Konan Jean Geoffroy Kouakou ◽  
Ouagninia Hili ◽  
Jean-Etienne Ouindllassida Dupuy

Data on the demand for medical care is usually measured by a number of different counts. These count data are most often correlated and subject to high proportions of zeros. However, excess zeros and the dependence between these data can jointly affect several utilization measures.In this paper, the zero-inflated bivariate Poisson regression model (ZIBP) was used to analyze health-care utilization data. First, the asymptotic properties of the maximum likelihood estimator (MLE) of this model were investigated theoretically. Then, a simulation study is conducted to evaluate the behaviour of the estimator in finite samples. Finally, an application of the ZIBP model to health care demand data is provided by way of illustration.


2019 ◽  
Vol 13 (4) ◽  
pp. 724-731 ◽  
Author(s):  
Troy Quast ◽  
Lijuan Feng

ABSTRACTObjectiveWhile the short-term effects of disasters on health care utilization are well documented, less is known regarding potential longer-term effects. This study investigates the effects of Hurricane Katrina on the health care utilization of older individuals with diabetes.MethodsWe examined Medicare claims and enrollment data for the 2002-2004 and 2006-2008 time periods for older individuals with diabetes. Our quasi-experimental design analyzed utilization across 2 treated and 3 control groups. We compared the proportion of individuals who received a screen related to diabetes before and after Katrina in the treated groups to the proportions in the control groups. Our regression analysis employs individual and year fixed effects to control for factors specific to a given individual or to a given year.ResultsWe found that utilization rates in the 2002-2004 period exhibited roughly parallel trends for the treated and control groups, which provides support for our research design. The 2006-2008 utilization rates were generally lower for the treated groups than they were for the control groups. The differences were especially pronounced for older age cohorts.ConclusionsOur study suggests that the effects of disasters on health care utilization may persist for years after the event. Recovery efforts may be improved by addressing both short-term and long-term health care interruptions. (Disaster Med Public Health Preparedness. 2019;13:724–731)


2021 ◽  
Vol 16 (2) ◽  
pp. 2763-2784
Author(s):  
Konan Jean Geoffroy Kouakou ◽  
Ouagninia Hili ◽  
Jean-François DUPUY

Data on the demand for medical care is usually measured by a number of different counts. These count data are most often correlated and subject to high proportions of zeros. However, excess zeros and the dependence between these data can jointly affect several utilization measures.In this paper, the zero-inflated bivariate Poisson regression model (ZIBP) was used to analyze health-care utilization data. First, the asymptotic properties of the maximum likelihood estimator (MLE) of this model were investigated theoretically.Then, a simulation study is conducted to evaluate the behaviour of the estimator in finite samples. Finally, an application of the ZIBP model to health care demand data is provided by way of illustration.


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