發展線上醫療照護相關泌尿道感染監測系統

Developing Web-Based Information System to Detect Healthcare-Associated Urinary Tract Infections

醫療照護相關感染可能危害病人安全，且造成額外醫療資源的使用，因此醫療照護相關感染的監測是醫療機構感染管制計劃的重要任務之一。傳統的監測作業，缺乏友善電腦介面和資訊化醫療記錄的時代，依賴專業人員的經驗及警覺，不僅耗費大量人時，且延遲回饋臨床單位等，而影響品管促進之效能。多篇研究顯示電腦輔助收案相較於傳統人工收案，較有效率。醫療照護相關感染部位分布中，泌尿道感染一直都是最主要的部位之一，本研究乃針對泌尿道感染開發電腦輔助收案系統，希望能妥善運用資料庫，有效率地完整的收集到感染管制指標，對品質促進有所助益。我們成立跨專業軟體開發團隊，整合醫療資訊系統各資料庫，依定義定邏輯寫程式，系統依規則進行篩選、運算，將電腦判定的感染個案資料，使用者介面給感染管制人員優先覆核，及早完成判定作業，若有異常可爭取時間提醒臨床單位。Healthcare-associated Urinary Tract infections Surveillance and Classification System（HAUTISS）的敏感性、特異性、陽性預測值和陰性預測值分別為86.13%，99.37%，93.65%和99.65%；二者間一致性高（Cohen kappa coefficient達0.88；95%信賴區間為0.84─0.92）。HAUTISS上線前（2007年7月1日─2009年3月30日）收案延遲平均為59.9 ± 19.7天，上線後（2009年4月1日─2017年12月31日）改善為8.8 ± 3.3天。藉由資訊科技，節省下來耗時費力的監控業務時間，使感染管制進化為優質規劃發展各項專案，在品質改善活動有更多著力，間接提昇了醫療品質與病人就醫的安全，深具成本效益。

Healthcare-associated infections (HAIs) may compromise patient safety and are associated with additional costs. Continuous surveillance of HAIs is an essential element of infection prevention and control (IPC) program in the healthcare settings. Conventional HAI surveillance systems depend on well-trainted infection control personnel and are labor intensive, performance dependent, and tend to divert resources that are necessary for implementing IPC activities. Several studies have shown that computer-assisted HAI surveillance systems are more efficient than conventional methods. However, there remains difficult and may delay in tracking HAIs in the absence of an integrated interfaces of digitalized medical records. Healthcare-associated urinary tract infections (HAUTI) are a common site of HAIs. We developed a hospital-wide electronic automatic system to timely detect and conduct early intervention for HAUTIs at a medical center. A real-time information technology integrating clinical and laboratory data into a signal entry point user interface to assist infection control personnel in making decision for healthcare-associated urinary tract infections was established and applied to the clinical practice. We used web services techniques based on Service-Oriented Architecture, which is suitable for integrating heterogeneous platforms, protocols, and applications. A total of 396 HAUTI episodes were identified between June 1, 2015 and November 30, 2015 by qualified infection control personnel. The ''HAUTI'' episodes detected by the IT system correlated well to the reference standard with the sensitivity, specificity, positive predictive value and negative predictive value of 86.13%, 99.37%, 93.65%, and 99.65%, respectively. The system shortened the delay in confirmation of HAUTI cases, on average, by 51.1 days (59.9days versus 8.8 days, P＜.001). An electronic automatic HAUTI surveillance system simplifies the workflow of hospital infection control, provides convenience and shortens the time to HAUTI detection. It allows specialists to have more time to deal with ad hoc occurrences. As a process for efficiency improvement, the surveillance system would also strengthen the quality of medical care as well as patient safety.