Abstract：
BACKGROUND: In Iran, the Integrated Electronic Health Record system, called SEPAS, has been established to store all patient encounters of individuals referring to healthcare facilities.
OBJECTIVE: We aimed to develop a model for cleaning SEPAS and applying its data in other databases.
METHODS: We used cancer data from SEPAS as the sample. We developed a guideline to identify codes for cancer-related diagnoses and services in the database. Furthermore, we searched the SEPAS database based on ICD-10 and the diagnosis description in English and Farsi in an Excel sheet. We added codes and descriptions of pharmaceuticals and procedures to the list. We applied the above database and linked it to the patient records to identify cancer patients. A dashboard was designed based on this information for every cancer patient.
RESULTS: We selected 5,841 diagnostic codes and phrases, 9,300 cancer pharmaceutics codes, and 452 codes from cancer-specific items related to the diagnostic procedures and treatment methods. Linkage of this list to the patient list generated a database of about 197,164 cancer patients for linkage in the registry database.
CONCLUSIONS: Patient registries are one of the most important sources of information in healthcare systems. Data linkage between Electronic Health Record Systems (EHRs) and registries, despite its challenges, is profitable. EHRs can be used for case finding in any patient registry to reduce the time and cost of case finding.
OBJECTIVE: We aimed to develop a model for cleaning SEPAS and applying its data in other databases.
METHODS: We used cancer data from SEPAS as the sample. We developed a guideline to identify codes for cancer-related diagnoses and services in the database. Furthermore, we searched the SEPAS database based on ICD-10 and the diagnosis description in English and Farsi in an Excel sheet. We added codes and descriptions of pharmaceuticals and procedures to the list. We applied the above database and linked it to the patient records to identify cancer patients. A dashboard was designed based on this information for every cancer patient.
RESULTS: We selected 5,841 diagnostic codes and phrases, 9,300 cancer pharmaceutics codes, and 452 codes from cancer-specific items related to the diagnostic procedures and treatment methods. Linkage of this list to the patient list generated a database of about 197,164 cancer patients for linkage in the registry database.
CONCLUSIONS: Patient registries are one of the most important sources of information in healthcare systems. Data linkage between Electronic Health Record Systems (EHRs) and registries, despite its challenges, is profitable. EHRs can be used for case finding in any patient registry to reduce the time and cost of case finding.
摘要：
背景：在伊朗，综合电子健康记录系统，叫做SEPAS,已建立用于存储涉及医疗保健设施的个人的所有患者。
目的：我们的目标是开发一种用于清除SEPAS并将其数据应用于其他数据库的模型。
方法：我们使用来自SEPAS的癌症数据作为样本。我们制定了一个指南来识别数据库中癌症相关诊断和服务的代码。此外，我们根据ICD-10检索了SEPAS数据库,并在Excel表格中检索了英文和波斯语的诊断描述.我们在列表中添加了药品和程序的代码和说明。我们应用了上述数据库，并将其与患者记录相关联，以识别癌症患者。基于此信息为每个癌症患者设计了仪表板。
结果：我们选择了5,841个诊断代码和短语，9300个癌症药物代码，和452个代码来自与诊断程序和治疗方法相关的癌症特异性项目。该列表与患者列表的链接产生了约197,164名癌症患者的数据库,用于在注册数据库中的链接。
结论：患者登记是医疗保健系统中最重要的信息来源之一。电子健康记录系统(EHRs)和登记处之间的数据链接，尽管面临挑战,是有利可图的。EHR可用于任何患者注册表中的病例查找，以减少病例查找的时间和成本。
目的：我们的目标是开发一种用于清除SEPAS并将其数据应用于其他数据库的模型。
方法：我们使用来自SEPAS的癌症数据作为样本。我们制定了一个指南来识别数据库中癌症相关诊断和服务的代码。此外，我们根据ICD-10检索了SEPAS数据库,并在Excel表格中检索了英文和波斯语的诊断描述.我们在列表中添加了药品和程序的代码和说明。我们应用了上述数据库，并将其与患者记录相关联，以识别癌症患者。基于此信息为每个癌症患者设计了仪表板。
结果：我们选择了5,841个诊断代码和短语，9300个癌症药物代码，和452个代码来自与诊断程序和治疗方法相关的癌症特异性项目。该列表与患者列表的链接产生了约197,164名癌症患者的数据库,用于在注册数据库中的链接。
结论：患者登记是医疗保健系统中最重要的信息来源之一。电子健康记录系统(EHRs)和登记处之间的数据链接，尽管面临挑战,是有利可图的。EHR可用于任何患者注册表中的病例查找，以减少病例查找的时间和成本。
