Abstract：
Cardiovascular disease is a significant cause of late morbidity and mortality in survivors of childhood cancer. Clinical informatics tools could enhance provider adherence to echocardiogram guidelines for early detection of late-onset cardiomyopathy.
Cancer registry data were linked to electronic health record data. Structured query language facilitated the construction of anthracycline-exposed cohorts at a single institution. Primary outcomes included the data quality from automatic anthracycline extraction, sensitivity of International Classification of Disease coding for heart failure, and adherence to echocardiogram guideline recommendations.
The final analytic cohort included 385 pediatric oncology patients diagnosed between July 1, 2013, and December 31, 2018, among whom 194 were classified as no anthracycline exposure, 143 had low anthracycline exposure (< 250 mg/m2), and 48 had high anthracycline exposure (≥ 250 mg/m2). Manual review of anthracycline exposure was highly concordant (95%) with the automatic extraction. Among the unexposed group, 15% had an anthracycline administered at an outside institution not captured by standard query language coding. Manual review of echocardiogram parameters and clinic notes yielded a sensitivity of 75%, specificity of 98%, and positive predictive value of 68% for International Classification of Disease coding of heart failure. For patients with anthracycline exposure, 78.5% (n = 62) were adherent to guideline recommendations for echocardiogram surveillance. There were significant association with provider adherence and race and ethnicity (P = .047), and 50% of patients with Spanish as their primary language were adherent compared with 90% of patients with English as their primary language (P = .003).
Extraction of treatment exposures from the electronic health record through clinical informatics and integration with cancer registry data represents a feasible approach to assess cardiovascular disease outcomes and adherence to guideline recommendations for survivors.
Cancer registry data were linked to electronic health record data. Structured query language facilitated the construction of anthracycline-exposed cohorts at a single institution. Primary outcomes included the data quality from automatic anthracycline extraction, sensitivity of International Classification of Disease coding for heart failure, and adherence to echocardiogram guideline recommendations.
The final analytic cohort included 385 pediatric oncology patients diagnosed between July 1, 2013, and December 31, 2018, among whom 194 were classified as no anthracycline exposure, 143 had low anthracycline exposure (< 250 mg/m2), and 48 had high anthracycline exposure (≥ 250 mg/m2). Manual review of anthracycline exposure was highly concordant (95%) with the automatic extraction. Among the unexposed group, 15% had an anthracycline administered at an outside institution not captured by standard query language coding. Manual review of echocardiogram parameters and clinic notes yielded a sensitivity of 75%, specificity of 98%, and positive predictive value of 68% for International Classification of Disease coding of heart failure. For patients with anthracycline exposure, 78.5% (n = 62) were adherent to guideline recommendations for echocardiogram surveillance. There were significant association with provider adherence and race and ethnicity (P = .047), and 50% of patients with Spanish as their primary language were adherent compared with 90% of patients with English as their primary language (P = .003).
Extraction of treatment exposures from the electronic health record through clinical informatics and integration with cancer registry data represents a feasible approach to assess cardiovascular disease outcomes and adherence to guideline recommendations for survivors.
摘要：
心血管疾病是儿童癌症幸存者晚期发病和死亡的重要原因。临床信息学工具可以增强提供者对超声心动图指南的依从性，以早期发现迟发性心肌病。
癌症登记数据与电子健康记录数据相关联。结构化查询语言有助于在单个机构中构建蒽环类抗生素暴露队列。主要结果包括自动蒽环类抗生素提取的数据质量，国际疾病分类对心力衰竭编码的敏感性，和坚持超声心动图指南建议。
最终分析队列包括在2013年7月1日至2018年12月31日之间诊断的385名儿科肿瘤患者，其中194名被归类为无蒽环类药物暴露。143例蒽环类药物暴露量较低（<250mg/m2），48例蒽环类药物暴露量较高(≥250mg/m2)。蒽环类抗生素暴露的手动检查与自动提取高度一致（95％）。在未曝光的群体中，15％的人在未通过标准查询语言编码捕获的外部机构使用蒽环类抗生素。超声心动图参数和临床记录的手动检查灵敏度为75％，特异性98%，心力衰竭的国际疾病分类编码的阳性预测值为68%。对于蒽环类药物暴露的患者，78.5％（n=62）遵守超声心动图监测的指南建议。与提供者依从性和种族和民族有显著关联（P=0.047），50％的以西班牙语为主要语言的患者与90％的以英语为主要语言的患者（P=.003）。
通过临床信息学从电子健康记录中提取治疗暴露量，并与癌症登记数据进行整合，是评估心血管疾病预后和坚持幸存者指南建议的可行方法。
癌症登记数据与电子健康记录数据相关联。结构化查询语言有助于在单个机构中构建蒽环类抗生素暴露队列。主要结果包括自动蒽环类抗生素提取的数据质量，国际疾病分类对心力衰竭编码的敏感性，和坚持超声心动图指南建议。
最终分析队列包括在2013年7月1日至2018年12月31日之间诊断的385名儿科肿瘤患者，其中194名被归类为无蒽环类药物暴露。143例蒽环类药物暴露量较低（<250mg/m2），48例蒽环类药物暴露量较高(≥250mg/m2)。蒽环类抗生素暴露的手动检查与自动提取高度一致（95％）。在未曝光的群体中，15％的人在未通过标准查询语言编码捕获的外部机构使用蒽环类抗生素。超声心动图参数和临床记录的手动检查灵敏度为75％，特异性98%，心力衰竭的国际疾病分类编码的阳性预测值为68%。对于蒽环类药物暴露的患者，78.5％（n=62）遵守超声心动图监测的指南建议。与提供者依从性和种族和民族有显著关联（P=0.047），50％的以西班牙语为主要语言的患者与90％的以英语为主要语言的患者（P=.003）。
通过临床信息学从电子健康记录中提取治疗暴露量，并与癌症登记数据进行整合，是评估心血管疾病预后和坚持幸存者指南建议的可行方法。
