Completeness of cohort-linked U.S. Medicare data: An example from the Agricultural Health Study (1999-2016).
Completeness of cohort-linked U.S. Medicare data: An example from the Agricultural Health Study (1999-2016).
复制标题
队列与美国Medicare数据的完整性：农业健康研究（1999-2016）的一个例子。
DOI：
10.1016/j.pmedr.2022.101766
复制
发表时间：
2022-06
影响因子：
2.8
通讯作者：
Sandler DP
中科院分区：
文献类型：
--
作者：
Parks CG;Shrestha S;Long S;Flottemesch T;Woodruff S;Chen H;Andreotti G;Hofmann JN;Beane Freeman LE;Sandler DP
我们在农业健康研究中描述了相关的美国联邦医疗保险索赔数据。不完整的索赔数据与地理、人口和健康状况有关。我们看到了杀虫剂使用和死亡率带来的潜在信息缺失。与联邦医疗保险相关的队列中的不完整数据可能会影响样本大小和有效性。医疗保险服务费(FFS)索赔数据，包括住院(A部分)和门诊(B部分)服务，为相关美国队列中的老年人研究(每年≥65)提供了宝贵的资源。在这里，我们描述了我们将农业健康研究队列(包括来自北卡罗来纳州(北卡罗来纳州)和爱荷华州(IA)的47,501名有执照的农药施用者和配偶)与1999至2016年的联邦医疗保险索赔数据联系起来的经验。鉴于此期间C部分(即管理式医疗保健/联邦医疗保险优势)的投保人数增加，以及2015年之前缺乏可用的C部分索赔数据，我们还探讨了信息缺失的可能性。我们在根据年龄、性别、种族、教育程度和吸烟进行调整的Logistic回归模型中，比较了部分或有限/无FFS覆盖的人和完全FFS覆盖的人(即，在整个医疗保险参保期间，≥每年11个月AB部分，但不是C部分)与基线农场规模、一般杀虫剂使用和死亡率的关系。虽然46,689名参与者(98%)与联邦医疗保险ID有关，但只有33,487人(70%)有完整的FFS，9,353人(20%)有部分FFS(≥1年FFS但不完全)，3,849(8%)有限制/没有FFS(仅限A部分或C部分)。不完全FFS在NC中更常见，主要是由于C部分，并与农场特征、杀虫剂使用和死亡率有关。这些发现表明，除了在限于完全FFS的分析中减少样本大小之外，错配可能不是随机的。在规划关联分析和解释结果时，需要考虑FFS数据不完整和覆盖类型变化的潜在影响。
We describe linked U.S. Medicare claims data in the Agricultural Health Study. Incomplete claims data were related to geographic, demographic, and health. We saw potential informative missingness by pesticide use and mortality. Incomplete data in Medicare-linked cohorts may impact sample size and validity. Medicare Fee for Service (FFS) claims data, including inpatient (Part A) and outpatient (Part B) services, provide a valuable resource for research on older adults (≥65 year) in linked U.S. cohorts. Here we describe our experience linking the Agricultural Health Study cohort, including 47,501 licensed pesticide applicators and spouses from North Carolina (NC) and Iowa (IA) to Medicare claims data from 1999 to 2016. Given increased Part C (i.e., managed care/Medicare Advantage) enrollment during this period, and a resulting lack of available Part C claims data prior to 2015, we also explored potential for informative missingness. We compared those with partial or limited/no FFS to those with complete FFS coverage (i.e., ≥11 months per year parts AB, but not C, throughout Medicare enrollment) in relation to baseline farm size, general pesticide use, and mortality, in logistic regression models adjusted for age, sex, race, education, and smoking, and stratified by state. While 46,689 participants (98%) were linked to Medicare IDs, only 33,487 (70%) had complete FFS, 9353 (20%) had partial FFS (≥1 year FFS but not complete), and 3849 (8%) had limited/no FFS (Part A or Part C-only). Incomplete FFS was more common in NC, mostly due to Part C, and was associated with farm characteristics, pesticide use, and mortality. These findings indicate that, in addition to reduced sample size in analyses limited to complete FFS, missingness may not be random. The potential impact of incomplete FFS data and changes in coverage type need to be considered when planning linked analyses and interpreting results.
登录
查看更多内容
影响因子：
3.9
作者：
Mues KE;Liede A;Liu J;Wetmore JB;Zaha R;Bradbury BD;Collins AJ;Gilbertson DT
通讯作者：
Gilbertson DT
影响因子：
9.7
作者：
Newhouse, Joseph P.;Price, Mary;Landon, Bruce E.
通讯作者：
Landon, Bruce E.
影响因子：
5
作者：
Jain, Samay;Himali, Jayandra;Frank, Samuel A
通讯作者：
Frank, Samuel A
影响因子：
3.4
作者：
Bergquist, Savannah L.;McGuire, Thomas G.;Rose, Sherri
通讯作者：
Rose, Sherri
影响因子：
6.6
作者：
McGuire, Thomas G.;Newhouse, Joseph P.;Sinaiko, Anna D.
通讯作者：
Sinaiko, Anna D.