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首页> 外文期刊>BMC Medical Informatics and Decision Making >Modeling count data for health care utilization: an empirical study of outpatient visits among Vietnamese older people
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Modeling count data for health care utilization: an empirical study of outpatient visits among Vietnamese older people

机译：营业保健利用率建模数据：越南老年人门诊观察的实证研究

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Vietnam is undergoing a fast-aging process that poses potential critical issues for older people and central among those is demand for healthcare utilization. However, healthcare utilization, here measured as count data, creates challenges for modeling because such data typically has distributions that are skewed with a large mass at zero. This study compares empirical econometric strategies for the modeling of healthcare utilization (measured as the number of outpatient visits in the last 12?months) and identifies the determinants of healthcare utilization among Vietnamese older people based on the best-fitting model identified. Using the Vietnam Household Living Standard Survey in 2006 (N?=?2426), nine econometric regression models for count data were examined to identify the best-fitting one. We used model selection criteria, statistical tests and goodness-of-fit for in-sample model selection. In addition, we conducted 10-fold cross-validation checks to examine reliability of the in-sample model selection. Finally, we utilized marginal effects to identify the factors associated with the number of outpatient visits among Vietnamese older people based on the best-fitting model identified. We found strong evidence in favor of hurdle negative binomial model 2 (HNB2) for both in-sample selection and 10-fold cross-validation checks. The marginal effect results of the HNB2 showed that ethnicity, region, household size, health insurance, smoking status, non-communicable diseases, and disability were significantly associated with the number of outpatient visits. The predicted probabilities for each count event revealed the distinct trends of healthcare utilization among specific groups: at low count events, women and people in the younger age group used more healthcare utilization than did men and their counterparts in older age groups, but a reverse trend was found at higher count events. The high degree of skewness and dispersion that typically characterizes healthcare utilization data affects the appropriateness of the econometric models that should be used in modeling such data. In the case of Vietnamese older people, our study findings suggest that hurdle negative binomial models should be used in the modeling of healthcare utilization given that the data-generating process reflects two different decision-making processes.
机译：越南正在进行一个快速老化的过程，对老年人和中央的潜在关键问题造成潜在的关键问题，其中包括医疗保健利用的需求。然而，这里测量的医疗保健利用率为计数数据，为建模创造了挑战，因为这种数据通常具有偏置大质量为零的分布。本研究比较了医疗保健利用的建模的经济计量策略（在过去12个月内的门诊访问数量），并确定了基于所确定的最佳拟合模型的越南老年人在越南老年人中的医疗利用决定因素。在2006年使用越南家庭生活标准调查（n？=？2426），检查了九个计量数据的计量数据模型，以确定最合适的计数。我们使用了模型选择标准，统计测试和适合于样本模型选择。此外，我们进行了10倍的交叉验证检查，以检查采样内模型选择的可靠性。最后，我们利用了边际效应来确定基于所确定的最佳拟合模型的越南老年人在越南老年人之间存在的因素。我们发现了强有力的证据，有利于对样品中的选择和10倍交叉验证检查的障碍负二项式模型2（HNB2）。 HNB2的边际效应结果表明，种族，地区，家庭规模，健康保险，吸烟状况，非传染性疾病和残疾与门诊次数显着相关。每个计数事件的预测概率揭示了特定群体中医疗利用的明显趋势：在低计数事件中，年龄较小的妇女和人民使用比较大年龄群体中的男性和同行更多的医疗保健利用率，但逆转被发现在更高的计数事件中。通常表征医疗利用数据的高度偏斜和色散影响了应在这些数据建模中使用的计量计量模型的适当性。在越南老年人的情况下，我们的研究结果表明，如果数据生成过程反映了两种不同的决策过程，则应在医疗利用率的建模中使用障碍负二项式模型。

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