Oral Health Disparities Among Medicaid Beneficiaries

描述（由申请人提供）：关于特殊需要人群的口腔癌和咽癌负担的信息非常有限，包括年老体弱、残疾人和艾滋病/艾滋病毒感染者。此外，存在明显的种族差异，黑人男性的5年生存率远低于白人男性。医疗补助是低收入种族和少数民族以及特殊需要人群的重要保险来源。与癌症登记数据相关联的医疗补助管理数据可以为了解这些亚组之间的健康差异提供强大的数据源。本研究将分析1999年至2004年医疗补助管理数据和全州范围内所有付款人出院数据（以确定比较组，包括私人付款人和医疗保险）与癌症登记数据库相关联，以解决三个具体目标：(1)评估研究特殊需要人群的能力，并将相关数据库中的口腔癌和咽癌队列进行比较；(2)生成关于重点人群的癌症发病率、诊断阶段和癌症死亡率的描述性统计数据（基于目标1下进行的数据质量评估的结果），并与其他人群进行比较；(3)评估链接数据库在研究优先人群治疗模式方面的效用。来自乔治亚州、伊利诺伊州、南卡罗来纳州和德克萨斯州的数据是根据特定的选择标准选择的，包括大量的医疗补助收费人群和口腔癌和咽癌的高负担。为了实现目标1，我们将通过癌症登记数据评估医疗补助索赔和全州出院数据之间联系的质量，确定特定亚组的能力，以及进行评估的足够样本量的可用性。对于目标2，我们将编制未经调整和年龄调整的发病率和死亡率。我们还将生成年度百分比变化，并进行连接点回归分析，以确定趋势线性斜率发生显著变化的点。对于目标3，我们将评估医疗补助计划中可用的连续登记月数，评估缺失值索赔的百分比，并评估使用ICD-9和CPT-4代码识别相关程序和治疗的能力。如果本研究表明索赔数据具有足够的质量，可以系统地研究口腔癌治疗并解决健康差异，则将提交后续申请，使用与医疗补助、医疗保险和私人付款人索赔数据相关的癌症登记数据对治疗模式进行比较评估。

DESCRIPTION (provided by applicant): There is very limited information on the burden of oral and pharyngeal cancers for specials needs populations, including the frail elderly, the disabled, and those with AIDS/HIV. In addition, significant racial disparities exist, as black males have a much lower 5-year survival rate compared with white males. Medicaid is an important source of insurance coverage for low-income racial and ethnic minorities, and also for the special needs populations. Medicaid administrative data linked with cancer registry data can provide a powerful data source to understand health disparities among these subgroups. This study will analyze 1999 through 2004 Medicaid administrative data and statewide all-payer discharge data (to identify comparison groups, including those insured by private payers and Medicare) linked with cancer registry databases to address three specific objectives: (1) assess the ability to study the special needs population and comparison cohorts with oral and pharyngeal cancers in the linked databases; (2) generate descriptive statistics on the incidence of cancer, stage at diagnosis, and cancer mortality among priority populations (based on findings from the data quality assessment performed under objective 1) and compare with other populations; and (3) assess the utility of the linked database to study treatment patterns among priority populations. Data from the states of Georgia, Illinois, South Carolina, and Texas were selected based on specific selection criteria, including large Medicaid fee-for-serve populations and a high burden of oral and pharyngeal cancers. To address objective 1, we will assess the quality of linkage between Medicaid claims and the statewide discharge data with the cancer registry data, the ability to identify specific subgroups, and availability of adequate sample sizes to perform assessments. For objective 2, we will produce unadjusted and age-adjusted incidence and mortality rates. We will also generate the annual percentage change and perform joinpoint regression analysis to identify points where a significant change in the linear slope of the trend occurs. For objective 3, we will assess the number of months of continuous enrollment available in Medicaid, evaluate the percentage of claims with missing values, and assess the ability to identify relevant procedures and treatments using ICD-9 and CPT-4 codes. If this proposed study shows that claims data are of adequate quality to systematically study oral cancer treatments and address health disparities, a follow-on application will be submitted to perform comparative assessments of treatment patterns using cancer registry data linked with Medicaid, Medicare, and private payer claims data. PUBLIC HEALTH RELEVANCE: Medicaid is an important source of insurance coverage for low-income racial and ethnic minorities, as well as special needs populations, including the frail elderly, the disabled, and those with HIV/AIDS. Medicaid administrative data linked with cancer registry data can provide a powerful data source to understand health disparities among these subgroups. In this study, the utility of this linked database will be evaluated to assess disparities related to oral and pharyngeal cancers, and incidence, stage of diagnosis, and mortality rates will be derived for the special needs population enrolled in Medicaid and compared with non-Medicaid cohorts.