The Effects of Health Sector Market Factors and Vulnerable Group Membership on Access to Alcohol, Drug, and Mental Health Care
本研究改编Andersen行为模型，利用社区调查数据，分析健康市场条件如何影响不同弱势群体（如非白人、穷人、无保险者、老年人）使用酒精、药物和精神健康服务，发现社区层面的促进因素部分解释了弱势地位的影响，但除HMO渗透率与保险类型的交互作用外，其他因素未改变个体层面的弱势效应。
OBJECTIVE: This study adapts Andersen's Behavioral Model to determine if health sector market conditions affect vulnerable subgroups' use of alcohol, drug, and mental health services (ADM) differently than the general population, focusing specifically on community-level predisposing and enabling characteristics. DATA SOURCES: Wave 2 data (2000-2001) from the Health Care for Communities study, supplemented with cases from wave 1 (1997-1998), were merged with area characteristics taken from Census, Area Resource File (ARF), and other data sources. STUDY DESIGN: The study used four-level hierarchical logistic regression to examine access to ADM care from any provider and specialty ADM access. Interactions between community-level predisposing and enabling vulnerability characteristics with individual race/ethnicity, age, income category, and insurance type were explored. PRINCIPAL FINDINGS: Nonwhites, the poor, uninsured, and elderly had lower likelihoods of service use, but interactions between race/ethnicity, income, age and insurance status with community-level vulnerability factors were not statistically significant for any service use. For ADM specialty care, those with Medicare, Medicaid, private fully managed, and private partially managed insurance, the likelihood of utilization was higher in areas with higher HMO penetration. However, for those with other insurance or no insurance plan, the likelihood of utilization was lower in areas with higher HMO penetration. CONCLUSIONS: Community-level enabling factors explain part of the effect of disadvantaged status but, with the exception of the effect of HMO penetration on the relationship between insurance and specialty care use, do not modify any of the residual individual-level effects of disadvantage. Interventions targeting both structural and individual levels may be necessary to address the problem of health disparities. More research with longitudinal data is necessary to sort out the causal direction of social context and ADM access outcomes, and whether policy interventions to change health sector market conditions can shift ADM treatment utilization.