城乡医保一体化制度对农村居民就医行为的影响

本文利用Charls 2008-2012年两期数据,采用双重差分DID方法对城乡医保一体化制度的政策效果进行实证分析.研究表明:城乡医保一体化制度显著提高了农村居民过去一个月门诊次数和医疗费用;但在住院方面,目前尚无证据显示医保一体化政策对过去一年是否住院和最近一次住院费用有显著的影响.在考虑了样本损耗问题、户籍转换、政策非随机等问题后,本文结论依然稳健.     

老年人居家照料服务利用的影响因素及城乡差异分析

文章以服务利用行为模型为分析框架,运用二元logistic回归模型,从老年人的倾向因素、使能因素以及需要因素三个方面考察老年人居家照料服务利用的影响因素及其表现出的城乡差异.结果表明,居家照料服务供给、户籍类型、是否认为自己是家庭的负担、年龄、IADL总分对老年人居家照料服务的利用具有显著影响.同时,城乡老年人在居家照料服务利用的影响因素上存在显著差异.     

基于分位数分解的城乡收入差距研究

文章基于中国家庭金融调查(CHFS)的调查数据,分别利用分位数回归和分布函数分解的方法,检验了城乡居民收入水平的主要影响因素,分解比较城乡收入差距中城乡居民禀赋特征构成差异和个体特征回报率差异的相对贡献.根据实证结果可以看到,受教育程度、职业性质等对城乡居民收入有显著影响,禀赋特征构成差异和个体特征回报率差异都扩大了城乡居民收入,其中城乡居民禀赋特征构成差异的影响更大.     

城市化、城乡收入差距对城乡医疗支出差异影响的实证检验

文章利用两部门模型,从理论上推导出了城市化和城乡收入差距均对城乡医疗支出差异具有正向影响,实证结果支持了这一结论,同时实证结果表明,1990～2006年间,一方面城乡收入差距的提高能够显著的拉大城乡医疗支出差异;另一方面,由于农村优秀资源的流失和政府财政补贴的城市倾向,城市化进程中,农村居民的医疗欲望受到抑制,医疗需求不足,导致了城乡医疗支出差异的进一步拉大。在此基础上,文章就如何缩小城乡医疗支出差异提出了简要的政策建议。     

基尼系数的分解:收入增长能否降低收入不平等

本文首先将基尼系数的变化分解为收入增长效应和家庭排序变化效应,再分别将居民按城乡分组、居民家庭收入按来源构成进行分解,构建了基尼系数变化的三层分解模型.在此模型的基础上,采用2006-2011年中国健康调查数据(CHNS)讨论了各项收入增长对城镇、农村、城乡间及整体收入不平等的影响,并给出了一些政策建议.     

我国居民家庭教育支出的影响因素分析

文章基于2006年CHNS数据，采用分层模型对我国居民家庭教育支出进行实证分析。在对家庭教育支出的变异进行分解时，我们发现社区间家庭的教育支出存在着显著的差异。研究还发现社区居民的收入水平是影响家庭教育支出的重要因素之一。此外，户主教育水平的提高有利于增加对子女教育的支出，并且城乡户主的教育水平对家庭教育支出的影响没有显著性差异。     

中国教育获得差距：基于泰尔系数分解的分析

利用教育泰尔系数对中国人口教育获得总差异及各省区差异进行测算.将总差异按省区进行分解,结果显示全国总差异主要来源于各省内部差异.进一步比较省内城镇和农村的教育泰尔系数,指出改善城乡教育不平等状况要着重搞好九年义务教育的推广和普及、农村进城人口子女的教育.     

公共医疗服务效率的时空演化与影响因素分析

文章借助超效率SBM模型、ESDA模型、Malmquist指数模型、固定效应模型分析了我国中医医院公共医疗服务效率的时空演化特征和影响因素。结果显示,我国中医医院医疗服务综合效率整体处于中等水平,地区间差异较大,TFP年均下降1.9%,效率值呈现空间集聚。医师日均担负诊疗人次数、日均担负住院床日、病床使用率和人均GDP对医疗服务综合效率有正向影响。应推进中医医疗资源均衡布局,推动医疗服务和管理模式创新,强化政府投入保障,加强优势专科建设。     

中国城乡多维贫困的测度及比较

传统的仅用收入或消费来衡量贫困的方法只能提供单一的信息,从多维角度则能够较全面地认识贫困。本文利用CHNS数据库中2000年和2009年数据,借鉴了多维贫困指数的构造及分解方法,对近十年来中国城乡多维贫困进行了测度、分解及分析,认为总体上城乡贫困程度均有所减轻,农村贫困严重于城市,应重视医疗健康保险、卫生设施、城市住房、做饭燃料等维度上的贫困,同时降低中西部省份的贫困。     

家庭因素对学生成绩影响的实证分析

文章从教育质量和影响教育质量的因素两个方面对已有的研究进行拓展,在控制公共教育资源影响的前提下,利用问卷调查数据,着重分析了家庭因素对城乡成绩型教育质量的影响,结果表明,县域内学生个体间、城乡之间的教育质量差异较为明显;传统的家庭因素在成绩型教育质量上依然保持着着显著的影响,非传统家庭因素对学生学业成绩的影响较大.     

中国各地区医疗卫生服务的生产效率分析

医疗卫生是与国民密切相关的一个问题,所以医疗卫生服务的生产效率如何倍受人们的关注。运用DEA模型可以对中国各地区的医疗卫生服务生产效率进行研究,分析不同地区效率高低的原因。结果显示,虽然总体上中国的医疗卫生服务的生产效率处于一个较低水平,但地区之间还是存在着很大的区别,并且地区间即便都是高效率或者低效率的地区,其投入和产出水平也不尽相同。     

中国人口年龄结构与居民医疗保健消费

本文借助中国2001—2010年的省级面板数据,运用动态面板GMM估计方法,考察了中国人口年龄结构(少儿和老年抚养系数)变化对居民医疗保健消费支出的影响。结果发现,中国少儿抚养系数对居民医疗保健消费支出的影响不显著;老年抚养系数对居民医疗保健消费支出有正影响,即老年抚养系数的上升会带动居民人均医疗保健消费支出的增加。此外,本文还发现,医疗保健消费支出的滞后一期系数都为正,系统GMM两步估计系数为0.51,表明居民医疗保健消费支出存在较强的惯性;人均收入增长对居民医疗保健消费支出有正向的显著影响。     

Regression analysis of health care charges with heteroscedasticity

We examine the effects of a prospective drug utilization review and patients' characteristics on total in-patient and out-patient health care charges. Our analysis of charges is complicated by the fact that the total health care charges are skewed. A log-transformation of these charges can normalize their distribution but may not stabilize their variance. To handle these problems, we propose a linear regression model with a non-constant variance (heteroscedasticity). Using results from a fitted linear regression model for log-transformed charges, we also discuss interpreting the regression coefficients in the original scale and estimating the total health care charges to individual patients. Employing these methods, we analyse total health care charges for drug utilization review patients with hypertension and identify patients' factors that are related to their total health care charges.     

Evaluation of adjustments for partial non-response bias in the US National Immunization Survey

Summary.  Many health surveys conduct an initial household interview to obtain demographic information and then request permission to obtain detailed information on health outcomes from the respondent's health care providers. A 'complete response' results when both the demographic information and the detailed health outcome data are obtained. A 'partial response' results when the initial interview is complete but, for one reason or another, the detailed health outcome information is not obtained. If 'complete responders' differ from 'partial responders' and the proportion of partial responders in the sample is at least moderately large, statistics that use only data from complete responders may be severely biased. We refer to bias that is attributable to these differences as 'partial non-response' bias. In health surveys it is customary to adjust survey estimates to account for potential differences by employing adjustment cells and weighting to reduce bias from partial response. Before making these adjustments, it is important to ask whether an adjustment is expected to increase or decrease bias from partial non-response. After making these adjustments, an equally important question is 'How well does the method of adjustment work to reduce partial non-response bias?'. The paper describes methods for answering these questions. Data from the US National Immunization Survey are used to illustrate the methods.     

照护还是医疗:老年人健康支出的产出效率比较

老龄化尤其是高龄失能老人增多对我国现有的以疾病治疗为核心的健康保障体系提出了挑战。本文基于CLHLS2011年数据的结构方程模型估计结果表明,家庭的照料护理支出显著提高了老人的健康自评、健康他评、生活满意度等生活质量指标,并且还能降低老人的小病发病率、患慢性病种类数以及两年内的患重病次数;而家庭的医疗费用支出则显著降低了老人对自身健康水平和生活状况的主观评价,对降低老人患小病、重病和慢性病等也没有贡献。相比医疗支出,照护支出具有更优的健康产出效率,并且通过增进老人的身体功能和生活自理能力、提高老人主观健康评价等途径起到更积极的健康促进作用。最后建议我国应将更多的健康支出用于照料护理,建立基于家庭和社区的老人照护体系。     

Statistical aspects in comparative benefit-risk assessment: challenges and opportunities for pharmaceutical statisticians

Benefit-risk assessment is a fundamental element of drug development with the aim to strengthen decision making for the benefit of public health. Appropriate benefit-risk assessment can provide useful information for proactive intervention in health care settings, which could save lives, reduce litigation, improve patient safety and health care outcomes, and furthermore, lower overall health care costs. Recent development in this area presents challenges and opportunities to statisticians in the pharmaceutical industry. We review the development and examine statistical issues in comparative benefit-risk assessment. We argue that a structured benefit-risk assessment should be a multi-disciplinary effort involving experts in clinical science, safety assessment, decision science, health economics, epidemiology and statistics. Well planned and conducted analyses with clear consideration on benefit and risk are critical for appropriate benefit-risk assessment. Pharmaceutical statisticians should extend their knowledge to relevant areas such as pharmaco-epidemiology, decision analysis, modeling, and simulation to play an increasingly important role in comparative benefit-risk assessment.     

环境质量、居民收入与医疗健康支出关系研究——基于截面相关的省际面板数据模型

准确测度环境质量、居民收入对医疗健康支出的影响有利于完善环境保护与医疗改革政策。基于医疗技术进步、医疗政策等不可观测性,构建了截面相关的面板数据模型,采用了迭代GMM估计方法,分析了环境质量、居民收入对医疗健康支出的效应以及医疗支出的区域差异性。研究表明：环境质量的恶化导致居民医疗健康支出的增长,环境保护政策制定应以人为本;医疗保健支出的收入弹性略小于1,提高城镇居民收入水平能显著地改善居民健康状况;医疗支出上涨压力与地区经济发展水平呈负相关性,政府应重视西部欠发达地区的医疗健康支出压力,给西部欠发达地区更多的政策扶持。     

中国卫生行业发展的现状与特点

摘　　要:本文利用2004年第一次全国经济普查的数据资料,从中国卫生行业的发展现状出发,利用聚类分析、非参数统计、生产函数等方法,对卫生行业发展规模与结构、从业人员文化素质、企业法人卫生单位与事业法人卫生单位发展特点、卫生机构的地区分布状况等进行了分析,揭示了各类卫生投入对GDP的影响因素,总结了卫生行业与区域经济发展的关系。     

Limitations of P-Values and R-squared for Stepwise Regression Building: A Fairness Demonstration in Health Policy Risk Adjustment

ABSTRACT

Stepwise regression building procedures are commonly used applied statistical tools, despite their well-known drawbacks. While many of their limitations have been widely discussed in the literature, other aspects of the use of individual statistical fit measures, especially in high-dimensional stepwise regression settings, have not. Giving primacy to individual fit, as is done with p-values and R², when group fit may be the larger concern, can lead to misguided decision making. One of the most consequential uses of stepwise regression is in health care, where these tools allocate hundreds of billions of dollars to health plans enrolling individuals with different predicted health care costs. The main goal of this “risk adjustment” system is to convey incentives to health plans such that they provide health care services fairly, a component of which is not to discriminate in access or care for persons or groups likely to be expensive. We address some specific limitations of p-values and R² for high-dimensional stepwise regression in this policy problem through an illustrated example by additionally considering a group-level fairness metric.     

Evaluation of long-term health care services through a latent Markov model with covariates

We focus on the evaluation of the long-term health care services provided to elderly patients by nursing homes of four different health districts in the Umbria region (Italy). To this end, we analyze data coming from a longitudinal survey aimed at assessing several aspects of patient health conditions and develop an extended version of the latent Markov model with covariates, which allows us to deal with dropout and intermittent missing data patterns that are common in longitudinal studies. Maximum likelihood estimates are obtained by a two-step approach that allows for fast estimation of model parameters and prevents some drawbacks of the standard maximum likelihood method encountered in the presence of many response variables and covariates. In the application to the observed data, we show how to obtain indicators of the effectiveness of the health care services delivered by each health district, by means of a resampling procedure.