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An empirical model to estimate the demand for primary care in urban settings.

机译：一种用于估计城市环境中初级保健需求的经验模型。

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摘要

Objective. To measure the demand for primary care and its associated factors by building and estimating a demand model of primary care in urban settings.;Data source. Secondary data from 2005 California Health Interview Survey (CHIS 2005), a population-based random-digit dial telephone survey, conducted by the UCLA Center for Health Policy Research in collaboration with the California Department of Health Services, and the Public Health Institute between July 2005 and April 2006.;Study design. A literature review was done to specify the demand model by identifying relevant predictors and indicators. CHIS 2005 data was utilized for demand estimation.;Analytical methods. The probit regression was used to estimate the use/non-use equation and the negative binomial regression was applied to the utilization equation with the non-negative integer dependent variable.;Results. The model included two equations in which the use/non-use equation explained the probability of making a doctor visit in the past twelve months, and the utilization equation estimated the demand for primary conditional on at least one visit. Among independent variables, wage rate and income did not affect the primary care demand whereas age had a negative effect on demand. People with college and graduate educational level were associated with 1.03 (p 0.05) and 1.58 (p 0.01) more visits, respectively, compared to those with no formal education. Insurance was significantly and positively related to the demand for primary care (p 0.01). Need for care variables exhibited positive effects on demand (p 0.01). Existence of chronic disease was associated with 0.63 more visits, disability status was associated with 1.05 more visits, and people with poor health status had 4.24 more visits than those with excellent health status.;Conclusions. The average probability of visiting doctors in the past twelve months was 85% and the average number of visits was 3.45. The study emphasized the importance of need variables in explaining healthcare utilization, as well as the impact of insurance, employment and education on demand. The two-equation model of decision-making, and the probit and negative binomial regression methods, was a useful approach to demand estimation for primary care in urban settings.
机译：目的。通过建立和估计城市环境中的初级保健需求模型来衡量对初级保健的需求及其相关因素。数据源。 UCLA卫生政策研究中心与加利福尼亚州卫生服务部和公共卫生研究所合作在2005年进行的基于人口的随机数字拨号电话调查（2005年加州健康访问调查，CHIS 2005）的辅助数据。 2005年和2006年4月；研究设计。通过确定相关的预测因素和指标，进行了文献综述以指定需求模型。利用CHIS 2005数据进行需求估算。概率回归用于估计使用/不使用方程，负二项式回归用于具有非负整数因变量的利用率方程。该模型包括两个方程式，其中使用/不使用方程式解释了过去十二个月内看医生的可能性，而利用方程式估计了至少一次就诊的基本条件需求。在自变量中，工资率和收入不影响初级保健需求，而年龄对需求有负面影响。与没有接受正规教育的人相比，具有大学和研究生以上文化程度的人的访问量分别多1.03（p <0.05）和1.58（p <0.01）。保险与基层医疗需求显着正相关（p <0.01）。需要照料变量对需求显示出积极影响（p <0.01）。慢性病的存在使探视次数增加了0.63次，残疾状态与探视次数增加了1.05次相关，健康状况较差的人的访问比健康状况良好的人多了4.24次。在过去的12个月中，看望医生的平均概率为85％，平均就诊次数为3.45。该研究强调了需求变量在解释医疗保健利用以及保险，就业和教育对需求的影响方面的重要性。决策的两等式模型以及概率和负二项式回归方法，是估算城市环境中初级保健需求的有用方法。

著录项

  • 作者

    Le, Phuc Hong.;

  • 作者单位

    The University of Texas School of Public Health.;

  • 授予单位 The University of Texas School of Public Health.;
  • 学科 Health Sciences Public Health.;Health Sciences Health Care Management.
  • 学位 M.P.H.
  • 年度 2009
  • 页码 40 p.
  • 总页数 40
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 预防医学、卫生学;预防医学、卫生学;
  • 关键词

  • 入库时间 2022-08-17 11:38:24

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