Administrative claims data to support pragmatic clinical trial outcome ascertainment on cardiovascular health
Administrative claims data to support pragmatic clinical trial outcome ascertainment on cardiovascular health
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DOI：
10.1177/1740774519846853
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发表时间：
2019-08-01
期刊：
影响因子：
2.7
通讯作者：
Haynes, Kevin
中科院分区：
文献类型：
--
作者：
Ma, Qinli;Chung, Haechung;Haynes, Kevin
背景/目的健康计划行政索赔数据提供了一种具有成本效益的补充，传统的临床事件的特定试验确定通常通过患者报告或单一卫生系统的电子健康记录进行。我们的目标是证明健康计划索赔数据在改善纵向实用临床试验中终点捕获方面的价值。方法本回顾性队列研究平行于适应性试验（阿司匹林剂量：以患者为中心评估获益和长期有效性的试验）的设计，该试验旨在比较两种剂量阿司匹林的有效性。我们在美国健康保险公司Anthem的索赔数据中应用了adaptive识别查询，并识别出符合adaptive试验标准的健康计划成员。在符合条件的适应性成员中，我们选择了在索引日期（2014年4月1日）前2年内与PCORnet临床数据研究网络重叠的成员。PCORnet临床数据研究网络由网络合作伙伴（或医疗保健系统）组成，这些合作伙伴以相同的格式存储其电子健康记录数据，以支持多机构研究。适应性结局事件——心血管住院，包括因心肌梗死、中风或心脏手术入院；因大出血住院；在2年的随访期间对住院死亡进行了评估。使用与每次住院相关的设施标识符，将事件分类为PCORnet临床数据研究网络内部或外部。用描述性统计检查患者特征，并根据可用的临床数据研究网络和索赔数据报告发病率。结果884,311名符合条件的健康计划成员中，有11,101名患者与PCORnet临床数据研究网络重叠。平均年龄70岁，男性71%，平均随访20.7个月。1521例心血管住院（571例（37.5%）发生在PCORnet临床数据研究网络之外），710例大出血（296例（41.7%）发生在PCORnet临床数据研究网络之外），196例院内死亡（67例（34.2%）发生在PCORnet临床数据研究网络之外）。可获得的网络合作伙伴和索赔数据之间的发病率（每1000患者-月的事件）不同：心血管住院，4.1（95%置信区间：3.9,4.4）对6.6(95%置信区间：6.3,7.0)，大出血，1.8（95%置信区间：1.6,2.0）对3.1(95%置信区间：2.9,3.3)，院内死亡，分别为0.56（95%置信区间：0.47,0.67）对0.85（95%置信区间：0.74,0.98）。结论本研究证明了利用行政索赔数据补充纵向现场临床研究的价值。我们的研究结果表明，索赔数据与网络合作伙伴的电子健康记录数据构成了捕获患者结果的有效工具，因为bbbb30 %的患者在注册站点之外发生了非致命和致命事件。
Background/aims Health plan administrative claims data present a cost-effective complement to traditional trial-specific ascertainment of clinical events typically conducted through patient report or a single health system electronic health record. We aim to demonstrate the value of health plan claims data in improving the capture of endpoints in longitudinal pragmatic clinical trials. Methods This retrospective cohort study paralleled the design of the ADAPTABLE (Aspirin Dosing: A Patient-centric Trial Assessing Benefits and Long-Term Effectiveness) trial designed to compare the effectiveness of two doses of aspirin. We applied the ADAPTABLE identification query in claims data from Anthem, an American health insurance company, and identified health plan members who met the ADAPTABLE trial criteria. Among the ADAPTABLE eligible members, we selected overlapping members with PCORnet Clinical Data Research Networks in the 2 years prior to the index date (1 April 2014). PCORnet Clinical Data Research Networks consist of network partners (or healthcare systems) that store their electronic health record data in the same format to support multi-institutional research. ADAPTABLE outcome events-cardiovascular hospitalizations including admissions for myocardial infarction, stroke, or cardiac procedures; hospitalizations for major bleeding; and in-hospital deaths-were evaluated for a 2-year follow-up period. Events were classified as within or outside PCORnet Clinical Data Research Networks using facility identifiers affiliated with each hospital stay. Patient characteristics were examined with descriptive statistics, and incidence rates were reported for available Clinical Data Research Networks and claims data. Results Among 884,311 ADAPTABLE eligible health plan members, 11,101 patients overlapped with PCORnet Clinical Data Research Networks. Average age was 70 years, 71% were male, and average follow-up was 20.7 months. Patients had 1521 cardiovascular hospitalizations (571 (37.5%) occurred outside PCORnet Clinical Data Research Networks), 710 for major bleeding (296 (41.7%) outside PCORnet Clinical Data Research Networks), and 196 in-hospital deaths (67 (34.2%) outside PCORnet Clinical Data Research Networks). Incidence rates (events per1000 patient-months) differed between available network partners and claims data: cardiovascular hospitalizations, 4.1 (95% confidence interval: 3.9, 4.4) versus 6.6 (95% confidence interval: 6.3, 7.0), major bleeding, 1.8 (95% confidence interval: 1.6, 2.0) versus 3.1 (95% confidence interval: 2.9, 3.3), and in-hospital death, 0.56 (95% confidence interval: 0.47, 0.67) versus 0.85 (95% confidence interval: 0.74, 0.98), respectively. Conclusion This study demonstrated the value of supplementing longitudinal site-based clinical studies with administrative claims data. Our results suggest that claims data together with network partner electronic health record data constitute an effective vehicle to capture patient outcomes since >30% of patients have non-fatal and fatal events outside of enrolling sites.