Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
ICES, Toronto, Ontario, Canada.
PLoS One. 2018 Nov 7;13(11):e0207030. doi: 10.1371/journal.pone.0207030. eCollection 2018.
An ongoing challenge of estimating the burden of infectious diseases known to disproportionately affect migrants (e.g. malaria, enteric fever) is that many health information systems, including reportable disease surveillance systems, do not systematically collect data on migrant status and related factors. We explored whether health administrative data linked to immigration records offered a viable alternative for accurately identifying cases of hepatitis A, malaria and enteric fever in Ontario, Canada. Using linked health care databases generated by Ontario's universal health care program, we constructed a cohort of medically-attended individuals with presumed hepatitis A, malaria or enteric fever in Peel region using diagnostic codes. Immigrant status was ascertained using linked immigration data. The sensitivity and positive predictive value (PPV) of diagnostic codes was evaluated through probabilistic linkage of the cohort to Ontario's reportable disease surveillance system (iPHIS) as the reference standard. Linkage was successful in 90.0% (289/321) of iPHIS cases. While sensitivity was high for hepatitis A and enteric fever (85.8% and 83.7%) and moderate for malaria (69.0%), PPV was poor for all diseases (0.3-41.3%). The accuracy of diagnostic codes did not vary by immigrant status. A dated coding system for outpatient physician claims and exclusion of new immigrants not yet eligible for health care were key challenges to using health administrative data to identify cases. Despite this, we show that linkages of health administrative and immigration records with reportable disease surveillance data are feasible and have the potential to bridge important gaps in estimating burden using either data source independently. .
目前，在估计那些已知对移民有不成比例影响的传染病负担（例如疟疾、肠热病）方面存在一个持续的挑战，这是因为许多卫生信息系统，包括报告疾病监测系统，并没有系统地收集移民身份和相关因素的数据。我们探讨了通过与移民记录相关联的卫生行政数据，是否可以为准确识别加拿大安大略省的甲型肝炎、疟疾和肠热病病例提供一种可行的替代方法。利用安大略省全民医疗保健计划生成的相关卫生保健数据库，我们使用诊断代码，在皮尔地区构建了一个有医疗服务就诊的疑似甲型肝炎、疟疾或肠热病患者队列。利用相关移民数据确定移民身份。通过将队列与安大略省报告疾病监测系统（iPHIS）进行概率性链接，作为参考标准，评估了诊断代码的敏感性和阳性预测值（PPV）。在 iPHIS 病例中，有 90.0%（289/321）的病例成功进行了链接。虽然甲型肝炎和肠热病的敏感性很高（85.8%和 83.7%），疟疾的敏感性适中（69.0%），但所有疾病的 PPV 都很差（0.3-41.3%）。诊断代码的准确性不因移民身份而异。门诊医生索赔的陈旧编码系统和排除尚未有资格获得医疗保健的新移民，是利用卫生行政数据识别病例的主要挑战。尽管如此，我们表明，卫生行政和移民记录与报告疾病监测数据的链接是可行的，并且有可能利用任何一种数据源来弥补估计负担方面的重要差距。
