1 Camden Coalition of Healthcare Providers , Camden, New Jersey.
Popul Health Manag. 2013;16 Suppl 1:S20-5. doi: 10.1089/pop.2013.0037.
Developing data-driven local solutions to address rising health care costs requires valid and reliable local data. Traditionally, local public health agencies have relied on birth, death, and specific disease registry data to guide health care planning, but these data sets provide neither health information across the lifespan nor information on local health care utilization patterns and costs. Insurance claims data collected by local hospitals for administrative purposes can be used to create valuable population health data sets. The Camden Coalition of Healthcare Providers partnered with the 3 health systems providing emergency and inpatient care within Camden, New Jersey, to create a local population all-payer hospital claims data set. The combined claims data provide unique insights into the health status, health care utilization patterns, and hospital costs on the population level. The cross-systems data set allows for a better understanding of the impact of high utilizers on a community-level health care system. This article presents an introduction to the methods used to develop Camden's hospital claims data set, as well as results showing the population health insights obtained from this unique data set.
为了解决医疗成本不断上升的问题,需要制定以数据为基础的地方解决方案,而这需要有效且可靠的本地数据。传统上,地方公共卫生机构依赖于出生、死亡和特定疾病登记数据来指导医疗保健规划,但这些数据集既不能提供整个生命周期的健康信息,也不能提供有关当地医疗保健利用模式和成本的信息。当地医院为管理目的而收集的保险索赔数据可用于创建有价值的人口健康数据集。新泽西州卡姆登市的医疗服务提供商联盟与为该地区提供急诊和住院服务的 3 家医疗系统合作,创建了一个本地全民支付医院索赔数据集。合并后的索赔数据为了解人口层面的健康状况、医疗利用模式和医院成本提供了独特的见解。跨系统数据集有助于更好地了解高利用率者对社区级医疗保健系统的影响。本文介绍了开发卡姆登医院索赔数据集所使用的方法,以及从这个独特的数据集中获得的人口健康见解的结果。