Schultz S E, Rothwell D M, Chen Z, Tu K
Institute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Chronic Dis Inj Can. 2013 Jun;33(3):160-6.
To determine if using a combination of hospital administrative data and ambulatory care physician billings can accurately identify patients with congestive heart failure (CHF), we tested 9 algorithms for identifying individuals with CHF from administrative data.
The validation cohort against which the 9 algorithms were tested combined data from a random sample of adult patients from EMRALD, an electronic medical record database of primary care physicians in Ontario, Canada, and data collected in 2004/05 from a random sample of primary care patients for a study of hypertension. Algorithms were evaluated on sensitivity, specificity, positive predictive value, area under the curve on the ROC graph and the combination of likelihood ratio positive and negative.
We found that that one hospital record or one physician billing followed by a second record from either source within one year had the best result, with a sensitivity of 84.8% and a specificity of 97.0%.
Population prevalence of CHF can be accurately measured using combined administrative data from hospitalization and ambulatory care.
为了确定使用医院管理数据和门诊护理医生账单的组合能否准确识别充血性心力衰竭（CHF）患者，我们测试了9种从管理数据中识别CHF患者的算法。
用于测试这9种算法的验证队列合并了来自EMRALD（加拿大安大略省初级保健医生的电子病历数据库）的成年患者随机样本数据，以及2004/05年从初级保健患者随机样本中收集的用于高血压研究的数据。对算法进行了敏感性、特异性、阳性预测值、ROC图曲线下面积以及阳性和阴性似然比组合的评估。
我们发现，一年内一份医院记录或一份医生账单，随后再加上来自任一来源的第二份记录，结果最佳，敏感性为84.8%，特异性为97.0%。
使用住院和门诊护理的综合管理数据可以准确测量CHF的人群患病率。
