PDF(Pubmed)
Abstract：
BACKGROUND: Trauma registries and their quality improvement programs only collect data from the acute hospital admission, and no additional information is captured once the patient is discharged. This lack of long-term data limits these programs\' ability to affect change. The goal of this study was to create a longitudinal patient record by linking trauma registry data with third party payer claims data to allow the tracking of these patients after discharge.
METHODS: Trauma quality collaborative data (2018-2019) was utilized. Inclusion criteria were patients age ≥18, ISS ≥5 and a length of stay ≥1 d. In-hospital deaths were excluded. A deterministic match was performed with insurance claims records based on the hospital name, date of birth, sex, and dates of service (±1 d). The effect of payer type, ZIP code, International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis specificity and exact dates of service on the match rate was analyzed.
RESULTS: The overall match rate between these two patient record sources was 27.5%. There was a significantly higher match rate (42.8% versus 6.1%, P < 0.001) for patients with a payer that was contained in the insurance collaborative. In a subanalysis, exact dates of service did not substantially affect this match rate; however, specific International Classification of Diseases, Tenth Revision, Clinical Modification codes (i.e., all 7 characters) reduced this rate by almost half.
CONCLUSIONS: We demonstrated the successful linkage of patient records in a trauma registry with their insurance claims. This will allow us to the collect longitudinal information so that we can follow these patients\' long-term outcomes and subsequently improve their care.
METHODS: Trauma quality collaborative data (2018-2019) was utilized. Inclusion criteria were patients age ≥18, ISS ≥5 and a length of stay ≥1 d. In-hospital deaths were excluded. A deterministic match was performed with insurance claims records based on the hospital name, date of birth, sex, and dates of service (±1 d). The effect of payer type, ZIP code, International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis specificity and exact dates of service on the match rate was analyzed.
RESULTS: The overall match rate between these two patient record sources was 27.5%. There was a significantly higher match rate (42.8% versus 6.1%, P < 0.001) for patients with a payer that was contained in the insurance collaborative. In a subanalysis, exact dates of service did not substantially affect this match rate; however, specific International Classification of Diseases, Tenth Revision, Clinical Modification codes (i.e., all 7 characters) reduced this rate by almost half.
CONCLUSIONS: We demonstrated the successful linkage of patient records in a trauma registry with their insurance claims. This will allow us to the collect longitudinal information so that we can follow these patients\' long-term outcomes and subsequently improve their care.
摘要：
背景：创伤登记处及其质量改进计划仅收集急性入院的数据，一旦患者出院，就不会捕获其他信息。缺乏长期数据限制了这些程序影响变化的能力。这项研究的目的是通过将创伤登记数据与第三方付款人索赔数据相关联来创建纵向患者记录，以允许在出院后跟踪这些患者。
方法：使用创伤质量协作数据（2018-2019年）。纳入标准为患者年龄≥18，ISS≥5，住院时间≥1d。排除院内死亡。根据医院名称与保险索赔记录进行了确定性匹配，出生日期,性别,和服务日期(±1d)。付款人类型的影响，邮政编码,国际疾病分类,第十次修订,分析了临床修改诊断的特异性和确切的服务日期对匹配率的影响。
结果：这两个患者记录来源之间的总匹配率为27.5%。匹配率明显较高（42.8％对6.1％，P<0.001）对于保险合作中包含付款人的患者。在子分析中，确切的服务日期对这一匹配率没有实质性影响；然而，特定的国际疾病分类，第十次修订,临床修改代码(即，所有7个字符）将此速率降低了近一半。
结论：我们证明了创伤登记处患者记录与保险索赔之间的成功关联。这将使我们能够收集纵向信息，以便我们可以跟踪这些患者的长期结果，并随后改善他们的护理。
方法：使用创伤质量协作数据（2018-2019年）。纳入标准为患者年龄≥18，ISS≥5，住院时间≥1d。排除院内死亡。根据医院名称与保险索赔记录进行了确定性匹配，出生日期,性别,和服务日期(±1d)。付款人类型的影响，邮政编码,国际疾病分类,第十次修订,分析了临床修改诊断的特异性和确切的服务日期对匹配率的影响。
结果：这两个患者记录来源之间的总匹配率为27.5%。匹配率明显较高（42.8％对6.1％，P<0.001）对于保险合作中包含付款人的患者。在子分析中，确切的服务日期对这一匹配率没有实质性影响；然而，特定的国际疾病分类，第十次修订,临床修改代码(即，所有7个字符）将此速率降低了近一半。
结论：我们证明了创伤登记处患者记录与保险索赔之间的成功关联。这将使我们能够收集纵向信息，以便我们可以跟踪这些患者的长期结果，并随后改善他们的护理。
