The diagnosis of heart failure (HF) is an important problem in primary care. We previously demonstrated a 74% increase in registered HF diagnoses in primary care electronic health records (EHRs) following an extended audit procedure. What remains unclear is the accuracy of registered HF pre-audit and which EHR variables are most important in the extended audit strategy. This study aims to describe the diagnostic HF classification sequence at different stages, assess general practitioner (GP) HF misclassification, and test the predictive performance of an optimized audit.

中文翻译：

---

初级保健中心力衰竭电子健康记录审计的机器学习优化

心力衰竭 (HF) 的诊断是初级保健中的一个重要问题。我们之前证明，在扩展审计程序后，初级保健电子健康记录 (EHR) 中登记的 HF 诊断增加了 74%。尚不清楚的是注册 HF 预审计的准确性以及哪些 EHR 变量在扩展审计策略中最重要。本研究旨在描述不同阶段的诊断性 HF 分类序列，评估全科医生 (GP) 的 HF 错误分类，并测试优化审计的预测性能。