Abstract：
BACKGROUND: To recreate the in-hospital healthcare pathway for patients treated with coronary angiography or percutaneous coronary intervention, we linked the interventional cardiology registry (ACIRA) and the pseudonymized French hospital medical information system database (PMSI) in the Aquitaine region. The objective of this study was to develop and validate a deterministic merging algorithm between these exhaustive and complementary databases.
METHODS: After a pre-treatment phase of the databases to standardize the 11 identified linking variables, a deterministic linking algorithm was developed on ACIRA hospital stays between December 2011 and December 2014 in nine interventional cardiology centers as well as the data from the consolidated PMSI databases of the Aquitaine region from 2011 to 2014. Merging was carried out through 12 successive steps, the first consisting in strict linking of the 11 variables. The performance of the algorithm was analyzed in terms of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Strategies complementary to the initial algorithm (change in the order of variables and base preprocessing) were tested. Comparative analysis of merged/unmerged patients explored potential causes of mismatch.
RESULTS: The algorithm found 97.2% of the 31,621 ACIRA stays to have sensitivity of 99.9% (95% CI [99.9; 99.9]), specificity of 97.9% (95% CI [97.7; 98.1]), PPV of 99.9% (95% CI [99.9; 99.9]) and NPV of 96.9% (95% CI [96.7; 97.1]). Complementary strategies did not yield better results. The unmerged patients were older, and hospitalized mostly in 2012 in two interventional cardiology centers.
CONCLUSIONS: This study underscored the feasibility and validity of an indirect deterministic pairing to routinely link a registry of practices using hospital data to pseudonymized medico-administrative databases. This method, which can be extrapolated to other health events leading to hospitalization, renders it possible to effectively reconstruct patients\' hospital healthcare pathway.
METHODS: After a pre-treatment phase of the databases to standardize the 11 identified linking variables, a deterministic linking algorithm was developed on ACIRA hospital stays between December 2011 and December 2014 in nine interventional cardiology centers as well as the data from the consolidated PMSI databases of the Aquitaine region from 2011 to 2014. Merging was carried out through 12 successive steps, the first consisting in strict linking of the 11 variables. The performance of the algorithm was analyzed in terms of sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Strategies complementary to the initial algorithm (change in the order of variables and base preprocessing) were tested. Comparative analysis of merged/unmerged patients explored potential causes of mismatch.
RESULTS: The algorithm found 97.2% of the 31,621 ACIRA stays to have sensitivity of 99.9% (95% CI [99.9; 99.9]), specificity of 97.9% (95% CI [97.7; 98.1]), PPV of 99.9% (95% CI [99.9; 99.9]) and NPV of 96.9% (95% CI [96.7; 97.1]). Complementary strategies did not yield better results. The unmerged patients were older, and hospitalized mostly in 2012 in two interventional cardiology centers.
CONCLUSIONS: This study underscored the feasibility and validity of an indirect deterministic pairing to routinely link a registry of practices using hospital data to pseudonymized medico-administrative databases. This method, which can be extrapolated to other health events leading to hospitalization, renders it possible to effectively reconstruct patients\' hospital healthcare pathway.
摘要：
背景：为了为接受冠状动脉造影或经皮冠状动脉介入治疗的患者重建院内医疗保健途径，我们将阿基坦地区的介入心脏病学注册(ACIRA)和假名化的法国医院医疗信息系统数据库(PMSI)联系起来.这项研究的目的是开发和验证这些穷举和互补数据库之间的确定性合并算法。
方法：在对数据库进行预处理阶段以标准化已识别的11个链接变量之后，本研究针对2011年12月至2014年12月在9个介入心脏病学中心的ACIRA住院时间以及2011年至2014年阿基坦地区合并PMSI数据库的数据,开发了确定性连接算法.通过12个连续步骤进行合并，第一个包含11个变量的严格链接。从灵敏度方面分析了算法的性能,特异性，阳性预测值(PPV)和阴性预测值(NPV)。测试了与初始算法（变量顺序和基础预处理的变化）互补的策略。合并/未合并患者的比较分析探讨了错配的潜在原因。
结果：该算法发现31,621个ACIRA中有97.2％的灵敏度为99.9％（95％CI[99.9;99.9]），特异性为97.9%（95%CI[97.7;98.1]），PPV为99.9%（95%CI[99.9;99.9]），NPV为96.9%（95%CI[96.7;97.1]）。补充策略没有产生更好的结果。未合并的患者年龄较大，2012年主要在两个介入心脏病学中心住院。
结论：本研究强调了间接确定性配对的可行性和有效性，以常规地将使用医院数据的实践注册与假名医学管理数据库联系起来。这种方法,可以推断为其他导致住院的健康事件，使得有效重建患者医院医疗保健途径成为可能。
方法：在对数据库进行预处理阶段以标准化已识别的11个链接变量之后，本研究针对2011年12月至2014年12月在9个介入心脏病学中心的ACIRA住院时间以及2011年至2014年阿基坦地区合并PMSI数据库的数据,开发了确定性连接算法.通过12个连续步骤进行合并，第一个包含11个变量的严格链接。从灵敏度方面分析了算法的性能,特异性，阳性预测值(PPV)和阴性预测值(NPV)。测试了与初始算法（变量顺序和基础预处理的变化）互补的策略。合并/未合并患者的比较分析探讨了错配的潜在原因。
结果：该算法发现31,621个ACIRA中有97.2％的灵敏度为99.9％（95％CI[99.9;99.9]），特异性为97.9%（95%CI[97.7;98.1]），PPV为99.9%（95%CI[99.9;99.9]），NPV为96.9%（95%CI[96.7;97.1]）。补充策略没有产生更好的结果。未合并的患者年龄较大，2012年主要在两个介入心脏病学中心住院。
结论：本研究强调了间接确定性配对的可行性和有效性，以常规地将使用医院数据的实践注册与假名医学管理数据库联系起来。这种方法,可以推断为其他导致住院的健康事件，使得有效重建患者医院医疗保健途径成为可能。
