Steiner Jill M, Kirkpatrick James N, Heckbert Susan R, Habib Asma, Sibley James, Lober William, Randall Curtis J
Division of Cardiology, University of Washington, Seattle, Washington, USA.
Department of Epidemiology, University of Washington, Seattle, Washington, USA.
Congenit Heart Dis. 2018 Jan;13(1):65-71. doi: 10.1111/chd.12524. Epub 2017 Jul 24.
There is relatively sparse literature on the use of administrative datasets for research in patients with adult congenital heart disease (ACHD). The goal of this analysis is to examine the accuracy of administrative data for identifying patients with ACHD who died.
A list of the International Classification of Diseases codes representing ACHD of moderate- or great-complexity was created. A search for these codes in the electronic health record of adults who received care in 2010-2016 was performed, and used state death records to identify patients who died during this period. Manual record review was completed to evaluate performance of this search strategy. Identified patients were also compared with a list of patients with moderate- or great-complexity ACHD known to have died.
About 134 patients were identified, of which 72 had moderate- or great-complexity ACHD confirmed by manual review, yielding a positive predictive value of 0.54 (95% CI 0.45, 0.62). Twenty six patients had a mild ACHD diagnosis. Thirty six patients had no identified ACHD on record review. Misidentifications were attributed to coding error for 19 patients (53%), and to acquired ventricular septal defects for 11 patients (31%). Diagnostic codes incorrect more than 50% of the time were those for congenitally corrected transposition, endocardial cushion defect, and hypoplastic left heart syndrome. Only 1 of 21 patients known to have died was not identified by the search, yielding a sensitivity of 0.95 (0.76, 0.99).
Use of administrative data to identify patients with ACHD of moderate or great complexity who have died had good sensitivity but suboptimal positive predictive value. Strategies to improve accuracy are needed. Administrative data is not ideal for identification of patients in this group, and manual record review is necessary to confirm these diagnoses.
关于使用行政数据集对成人先天性心脏病(ACHD)患者进行研究的文献相对较少。本分析的目的是检验行政数据用于识别死亡的ACHD患者的准确性。
创建了一份代表中度或高度复杂性ACHD的国际疾病分类代码列表。在2010 - 2016年接受治疗的成年人电子健康记录中搜索这些代码,并使用州死亡记录来识别在此期间死亡的患者。完成人工病历审查以评估此搜索策略的性能。还将识别出的患者与已知死亡的中度或高度复杂性ACHD患者名单进行了比较。
共识别出约134名患者,其中72名经人工审查确诊为中度或高度复杂性ACHD,阳性预测值为0.54(95%可信区间0.45, 0.62)。有26名患者诊断为轻度ACHD。36名患者在病历审查中未发现ACHD。错误识别归因于编码错误的有19名患者(53%),归因于后天性室间隔缺损的有11名患者(31%)。诊断代码错误率超过50%的是先天性矫正型大动脉转位、心内膜垫缺损和左心发育不全综合征。已知死亡的21名患者中只有1名未被搜索识别出来,灵敏度为0.95(0.76, 0.99)。
使用行政数据识别死亡的中度或高度复杂性ACHD患者具有良好的灵敏度,但阳性预测值不理想。需要提高准确性的策略。行政数据对于识别该组患者并不理想,需要人工病历审查来确认这些诊断。