scholarly journals Modeling Hospitalization Decision and Utilization for the Elderly in China

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Xin Xu ◽  
Dongxiao Chu
Keyword(s):  
Negative Binomial ◽  
Hospital Readmissions ◽  
Poisson Model ◽  
Medical Insurance ◽  
The Elderly ◽  
Negative Binomial Model ◽  
Binomial Model ◽  
Factors Affecting ◽  
Basic Medical Insurance ◽  
Basic Medical

Getting medical services has become more difficult and expensive in China, which led to a problem of illness not being treated and a large number of zeros in the statistics of being hospitalized for the elderly. Traditional classic models such as the Poisson model and the negative binomial model cannot fit this kind of data well. One aim of this study was to use zero-inflated and hurdle models to better solve the problem of excess zeros. Another aim was to discover the factors affecting the decision-making behavior of the elderly being hospitalized and hospitalization service utilization. Therefore, the XGBoost model was firstly introduced to rank the importance of influencing factors in this paper. It was found that the zero-inflated negative binomial model performed best. The results showed that the elderly who had enjoyed NRCM or ERBMI/URBMI were more likely to have a higher number of hospitalizations. This indicated that the high cost of hospitalization had prevented the willingness of the elderly being hospitalized, but the basic medical insurance had increased the times of their repeated hospital readmissions. Policy efforts should be made to improve the level of basic medical insurance.

scholarly journals Factors Affecting Under-Five Mortality in Ethiopia: A Multilevel Negative Binomial Model

2020 ◽  
Vol Volume 11 ◽  
pp. 525-534
Author(s):  
Bisrat Misganew Geremew ◽  
Kassahun Alemu Gelaye ◽  
Alemakef Wagnew Melesse ◽  
Temesgen Yihunie Akalu ◽  
Adhanom Gebreegziabher Baraki
Keyword(s):  
Negative Binomial ◽  
Negative Binomial Model ◽  
Binomial Model ◽  
Factors Affecting ◽  
Under Five ◽  
Multilevel Negative Binomial Model

Estimating Rates of Recurrent Peritonitis for Patients on CAPO

1985 ◽  
Vol 5 (1) ◽  
pp. 59-65 ◽  
Author(s):  
Edward F. Vonesh
Keyword(s):  
Risk Factors ◽  
Medical Devices ◽  
Negative Binomial ◽  
Survival Curve ◽  
Probability Model ◽  
Major Complication ◽  
Poisson Model ◽  
Negative Binomial Model ◽  
Binomial Model ◽  
The Mean

Recurrent peritonitis is a major complication of Continuous Ambulatory Peritoneal Dialysis (CAPD). As a therapy for patients with end stage renal disease, CAPD entails a continuous interaction between patient and various medical devices. The assumptions one makes regarding this interaction play an essential role when estimating the rate of recurrent peritonitis for a given patient population. Assuming that each patient has a constant rate of peritonitis, two models for evaluating the risk of recurrent peritonitis are considered. One model, the Poisson probability model, applies when the rate of peritonitis is the same from patient to patient. When this occurs, the frequency of peritoneal infections will be randomly distributed among patients (Corey, 1981). A second model, the negative binomial probability model, applies when the rate of peritonitis varies from one patient to another. In this event, the distribution of peritoneal infections will differ from patient to patient. The poisson model would be applicable when, for example, patients behave similarly with respect to their interactions with the medical devices and with potential risk factors. The negative binomial model, on the other hand, makes allowances for patient differences both in terms of their handling of routine exchanges and in their exposure to various risk factors. This paper provides methods for estimating the mean peritonitis rate under each model. In addition, “survival” curve estimates depicting the probability of remaining peritonitis free (i.e. “surviving”) over time are provided. It is shown, using data from a multi-center clinical trial, that the risk of peritonitis is best described in terms of survival curves rather than the mean peritonitis rate. For both models, the mean peritonitis rate was found to be 0.85 episodes per year. However, under the negative binomial model, the one-year survival rate, expressed as the percentage of patients remaining free of peritonitis, is 52% as compared with only 42% under the Poisson model. Moreover, the negative binomial model provided a significantly better fit to the observed frequency of peritonitis. These findings suggest that the negative binomial model provides a more realistic and accurate portrayal of the risk of peritonitis and that this risk is not nearly as high as would otherwise be indicated by a Poisson analysis.

scholarly journals Random Parameter Negative Binomial Model of Signalized Intersections

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Minho Park ◽  
Dongmin Lee ◽  
Jinwoo Jeon
Keyword(s):  
Negative Binomial ◽  
Random Parameter ◽  
Signalized Intersections ◽  
Negative Binomial Model ◽  
Marginal Effect ◽  
Binomial Model ◽  
Random Parameters ◽  
Factors Affecting ◽  
Independent Variables ◽  
Insight Into

Factors affecting accident frequencies at 72 signalized intersections in the Gyeonggi-Do (province) over a four-year period (2007~2010) were explored using the random parameters negative binomial model. The empirical results from the comparison with fixed parameters binomial model show that the random parameters model outperforms its fixed parameters counterpart and provides a fuller understanding of the factors which determine accident frequencies at signalized intersections. In addition, elasticity and marginal effect were estimated to gain more insight into the effects of one-percent and one-unit changes in the dependent variable from changes in the independent variables.

scholarly journals Inequity in healthcare needs, health service use and financial burden of medical expenditures in China: results from a consecutive household monitoring study in Jiangsu Province

2019 ◽  
Author(s):  
Weixi Jiang ◽  
Xiaolin Xu ◽  
Shenglan Tang ◽  
Ling Xu ◽  
Yaoguang Zhang ◽  
...  
Keyword(s):  
Health Expenditure ◽  
Service Use ◽  
Negative Binomial ◽  
Medical Insurance ◽  
Factors Associated ◽  
Logit Regression ◽  
Healthcare Needs ◽  
Basic Medical Insurance ◽  
Rural And Urban ◽  
Basic Medical

Abstract Background: Although public medical insurance covers over 95% of the population in China, disparities in health service use and out-of-pocket (OOP) health expenditure across income groups are still widely observed. This study aims to investigate the socio-economic disparities in perceived healthcare needs, informal care, formal care and payment for healthcare and explore their equity implication. Methods: We assessed healthcare needs, service use and payment in 400 households in rural and urban areas in Jiangsu, China, and included only the adult sample (N=925). One baseline survey and 10 follow-up surveys were conducted during the 7-month monitoring period, and the Affordability Ladder Program (ALP) framework was adopted for data analysis. Negative binomial/zero-inflated negative binomial and logit regression models were used to explore factors associated with perceived needs of care and with the use of self-treatment, outpatient and inpatient care respectively. Two-part model and logit regression modeling were conducted to explore factors associated with OOP health expenditure and with the likelihood of incurring catastrophic health expenditure (CHE). Results : After adjusting for covariates, rural residence was significantly associated with more perceived healthcare needs, more self-treatment, higher probability of using outpatient and inpatient service, more OOP health expenditure and higher likelihood of incurring catastrophic expenditure ( P <0.05). Compared to the Urban Employee Basic Medical Insurance (UEBMI), enrollment in the New Rural Cooperative Medical Scheme (NRCMS) or in the Urban Resident Basic Medical Insurance (URBMI) was correlated with lower probability of ever using outpatient services, but with more outpatient visits when people were at risk of using outpatient service ( P <0.05). NRCMS/URBMI enrollment was also associated with higher likelihood of incurring CHE compared to UEBMI enrollment (OR=2.02, P <0.05); in stratified analysis of the rural and urban sample this effect was only significant for the rural population. Conclusions: The rural population in Jiangsu perceived more healthcare needs, had a higher probability of using both informal and formal healthcare services, and had more OOP health expenditure and a higher likelihood of incurring CHE. The inequity mainly exists in health care financing, and may be partially addressed through improving the benefit packages of NRCMS/URBMI.

scholarly journals Inequity in healthcare needs, health service use and financial burden of medical expenditures in China: results from a consecutive household monitoring study in Jiangsu Province

2019 ◽  
Author(s):  
Weixi Jiang ◽  
Xiaolin Xu ◽  
Shenglan Tang ◽  
Ling Xu ◽  
Yaoguang Zhang ◽  
...  
Keyword(s):  
Health Expenditure ◽  
Service Use ◽  
Negative Binomial ◽  
Medical Insurance ◽  
Factors Associated ◽  
Logit Regression ◽  
Healthcare Needs ◽  
Basic Medical Insurance ◽  
Rural And Urban ◽  
Basic Medical

Abstract Background: Although public medical insurance covers over 95% of the population in China, disparities in health service use and out-of-pocket (OOP) health expenditure across income groups are still widely observed. This study aims to investigate the socio-economic disparities in perceived healthcare needs, informal care, formal care and payment for healthcare and explore their equity implication. Methods: We assessed healthcare needs, service use and payment in 400 households in rural and urban areas in Jiangsu, China, and included only the adult sample (N=925). One baseline survey and 10 follow-up surveys were conducted during the 7-month monitoring period, and the Affordability Ladder Program (ALP) framework was adopted for data analysis. Negative binomial/zero-inflated negative binomial and logit regression models were used to explore factors associated with perceived needs of care and with the use of self-treatment, outpatient and inpatient care respectively. Two-part model and logit regression modeling were conducted to explore factors associated with OOP health expenditure and with the likelihood of incurring catastrophic health expenditure (CHE). Results : After adjusting for covariates, rural residence was significantly associated with more perceived healthcare needs, more self-treatment, higher probability of using outpatient and inpatient service, more OOP health expenditure and higher likelihood of incurring catastrophic expenditure ( P <0.05). Compared to the Urban Employee Basic Medical Insurance (UEBMI), enrollment in the New Rural Cooperative Medical Scheme (NRCMS) or in the Urban Resident Basic Medical Insurance (URBMI) was correlated with lower probability of ever using outpatient services, but with more outpatient visits when people were at risk of using outpatient service ( P <0.05). NRCMS/URBMI enrollment was also associated with higher likelihood of incurring CHE compared to UEBMI enrollment (OR=2.02, P <0.05); in stratified analysis of the rural and urban sample this effect was only significant for the rural population. Conclusions: The rural population in Jiangsu perceived more healthcare needs, had a higher probability of using both informal and formal healthcare services, and had more OOP health expenditure and a higher likelihood of incurring CHE. The inequity mainly exists in health care financing, and may be partially addressed through improving the benefit packages of NRCMS/URBMI.

scholarly journals How Individual Characters Affect the Ex ante Moral Hazard of Basic Medical Insurance: Evidence from China

2019 ◽  
Vol 6 (5) ◽  
pp. 53
Author(s):  
Ji Luo ◽  
Yuanxiang Zhou
Keyword(s):  
Health Insurance ◽  
Moral Hazard ◽  
Medical Insurance ◽  
Basic Health Insurance ◽  
Factors Affecting ◽  
Basic Health ◽  
Basic Medical Insurance ◽  
Ex Ante Moral Hazard ◽  
Ex Ante ◽  
Basic Medical

How individual characters affect the ex ante moral hazard of basic medical insurance still remain academically debatable. This paper based on divergent individual characters of insurers to analyze the roles of basic health insurance on the ex ante moral hazard. It found health level, marital status, income level and age are the key individual factors affecting ex ante moral hazard of basic health insurance. But the roles of rural-urban difference and gender are not obvious. It gives supplementary explanations to the medical service expenditure, waste of medical resources and other issues, and also put forward the corresponding policy recommendations.

scholarly journals Leaf count overdispersion in coffee seedlings

2019 ◽  
Vol 49 (4) ◽  
Author(s):  
Edilson Marcelino Silva ◽  
Thais Destefani Ribeiro Furtado ◽  
Jaqueline Gonçalves Fernandes ◽  
Marcelo Ângelo Cirillo ◽  
Joel Augusto Muniz
Keyword(s):  
Count Data ◽  
Negative Binomial ◽  
Block Design ◽  
Poisson Model ◽  
Relevant Information ◽  
Relative Increase ◽  
Negative Binomial Model ◽  
Binomial Model ◽  
Coffee Bean ◽  
Number Of Leaves

ABSTRACT: Coffee crops play an important role in Brazilian agriculture, with a high level of social and economic participation resulting from the jobs created in the supply chain and from the income obtained by producers and the revenue generated for the country from coffee bean export. In coffee plant growth, leaves have a determinant role in higher production; therefore, the leaf count per plant provides relevant information to producers for adequate crop management, such as foliar fertilizer applications. To describe count data, the Poisson model is the most commonly employed model; when count data show overdispersion, the negative binomial model has been determined to be more adequate. The objective of this study was to compare the fitness of the Poisson and negative binomial models to data on the leaf count per plant in coffee seedlings. Data were collected from an experiment with a randomized block design with 30 treatments and three replicates and four plants per plot. Data from only one treatment, in which the number of leaves was counted over time, were employed. The first count was conducted on 8 April 2016, and the other counts were performed 18, 32, 47, 62, 76, 95, 116, 133, and 153 days after the first evaluation, for a total of ten measurements. The fitness of the models was assessed based on deviance values and simulated envelopes for residuals. Results of fitness assessment indicated that the Poisson model was inadequate for describing the data due to overdispersion. The negative binomial model adequately fitted the observations and was indicated to describe the number of leaves of coffee plants. Based on the negative binomial model, the expected relative increase in the number of leaves was 0.9768% per day.

scholarly journals Inequity in healthcare needs, health service use and financial burden of medical expenditures in China: results from a consecutive household monitoring study in Jiangsu Province

2019 ◽  
Author(s):  
Weixi Jiang ◽  
Xiaolin Xu ◽  
Shenglan Tang ◽  
Ling Xu ◽  
Yaoguang Zhang ◽  
...  
Keyword(s):  
Health Expenditure ◽  
Service Use ◽  
Negative Binomial ◽  
Medical Insurance ◽  
Factors Associated ◽  
Logit Regression ◽  
Healthcare Needs ◽  
Basic Medical Insurance ◽  
Rural And Urban ◽  
Basic Medical

Abstract Background: Although public medical insurance covers over 95% of the population in China, disparities in health service use and out-of-pocket (OOP) health expenditure across income groups are still widely observed. This study aims to investigate the socio-economic disparities in perceived healthcare needs, informal care, formal care and payment for healthcare and explore their equity implication. Methods: We assessed healthcare needs, service use and payment in 400 households in rural and urban areas in Jiangsu, China, and included only the adult sample (N=925). One baseline survey and 10 follow-up surveys were conducted during the 7-month monitoring period, and the Affordability Ladder Program (ALP) framework was adopted for data analysis. Negative binomial/zero-inflated negative binomial and logit regression models were used to explore factors associated with perceived needs of care and with the use of self-treatment, outpatient and inpatient care respectively. Two-part model and logit regression modeling were conducted to explore factors associated with OOP health expenditure and with the likelihood of incurring catastrophic health expenditure (CHE). Results : After adjusting for covariates, rural residence was significantly associated with more perceived healthcare needs, more self-treatment, higher probability of using outpatient and inpatient service, more OOP health expenditure and higher likelihood of incurring catastrophic expenditure ( P <0.05). Compared to the Urban Employee Basic Medical Insurance (UEBMI), enrollment in the New Rural Cooperative Medical Scheme (NRCMS) or in the Urban Resident Basic Medical Insurance (URBMI) was correlated with lower probability of ever using outpatient services, but with more outpatient visits when people were at risk of using outpatient service ( P <0.05). NRCMS/URBMI enrollment was also associated with higher likelihood of incurring CHE compared to UEBMI enrollment (OR=2.02, P <0.05); in stratified analysis of the rural and urban sample this effect was only significant for the rural population. Conclusions: The rural population in Jiangsu perceived more healthcare needs, had a higher probability of using both informal and formal healthcare services, and had more OOP health expenditure and a higher likelihood of incurring CHE. The inequity mainly exists in health care financing, and may be partially addressed through improving the benefit packages of NRCMS/URBMI.

scholarly journals Inequity in healthcare needs, health service use and financial burden of medical expenditures in China: results from a consecutive household monitoring study in Jiangsu Province

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Weixi Jiang ◽  
Xiaolin Xu ◽  
Shenglan Tang ◽  
Ling Xu ◽  
Yaoguang Zhang ◽  
...  
Keyword(s):  
Health Expenditure ◽  
Service Use ◽  
Negative Binomial ◽  
Medical Insurance ◽  
Factors Associated ◽  
Logit Regression ◽  
Healthcare Needs ◽  
Basic Medical Insurance ◽  
Rural And Urban ◽  
Basic Medical

Abstract Background Although public medical insurance covers over 95% of the population in China, disparities in health service use and out-of-pocket (OOP) health expenditure across income groups are still widely observed. This study aims to investigate the socio-economic disparities in perceived healthcare needs, informal care, formal care and payment for healthcare and explore their equity implication. Methods We assessed healthcare needs, service use and payment in 400 households in rural and urban areas in Jiangsu, China, and included only the adult sample (N = 925). One baseline survey and 10 follow-up surveys were conducted during the 7-month monitoring period, and the Affordability Ladder Program (ALP) framework was adopted for data analysis. Negative binomial/zero-inflated negative binomial and logit regression models were used to explore factors associated with perceived needs of care and with the use of self-treatment, outpatient and inpatient care respectively. Two-part model and logit regression modeling were conducted to explore factors associated with OOP health expenditure and with the likelihood of incurring catastrophic health expenditure (CHE). Results After adjusting for covariates, rural residence was significantly associated with more perceived healthcare needs, more self-treatment, higher probability of using outpatient and inpatient service, more OOP health expenditure and higher likelihood of incurring catastrophic expenditure (P < 0.05). Compared to the Urban Employee Basic Medical Insurance (UEBMI), enrollment in the New Rural Cooperative Medical Scheme (NRCMS) or in the Urban Resident Basic Medical Insurance (URBMI) was correlated with lower probability of ever using outpatient services, but with more outpatient visits when people were at risk of using outpatient service (P < 0.05). NRCMS/URBMI enrollment was also associated with higher likelihood of incurring CHE compared to UEBMI enrollment (OR = 2.02, P < 0.05); in stratified analysis of the rural and urban sample this effect was only significant for the rural population. Conclusions The rural population in Jiangsu perceived more healthcare needs, had a higher probability of using both informal and formal healthcare services, and had more OOP health expenditure and a higher likelihood of incurring CHE. The inequity mainly exists in health care financing, and may be partially addressed through improving the benefit packages of NRCMS/URBMI.

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