Leiden University Medical Center, Department of Clinical Pharmacy & Toxicology, Albinusdreef 2, 2333 ZA Leiden, The Netherlands.
Artif Intell Med. 2013 Sep;59(1):15-21. doi: 10.1016/j.artmed.2013.04.001. Epub 2013 May 7.
Our advanced clinical decision support (CDS) system, entitled 'adverse drug event alerting system' (ADEAS), is in daily use in our hospital pharmacy. It is used by hospital pharmacists to select patients at risk of possible adverse drug events (ADEs). The system retrieves data from several information systems, and uses clinical rules to select the patients at risk of ADEs. The clinical rules are all medication related and are formulated using seven risk categories.
This studies objectives are to 1) evaluate the use of the CDS system ADEAS in daily hospital pharmacy practice, and 2) assess the rule effectiveness and positive predictive value (PPV) of the clinical rules incorporated in the system.
Leiden University Medical Center, The Netherlands. All patients admitted on six different internal medicine and cardiology wards were included.
Outcome measures were total number of alerts, number of patients with alerts and the outcome of these alerts: whether the hospital pharmacist gave advice to prevent a possible ADE or not. Both overall rule effectiveness and PPV and rule effectiveness and PPV per clinical rule risk category were scored.
During a 5 month study period safety alerts were generated daily by means of ADEAS. All alerts were evaluated by a hospital pharmacist and if necessary, healthcare professionals were subsequently contacted and advice was given in order to prevent possible ADEs.
During the study period ADEAS generated 2650 safety alerts in 931 patients. In 270 alerts (10%) the hospital pharmacist contacted the physician or nurse and in 204 (76%) cases this led to an advice to prevent a possible ADE. The remaining 2380 alerts (90%) were scored as non-relevant. Most alerts were generated with clinical rules linking pharmacy and laboratory data (1685 alerts). The overall rule effectiveness was 0.10 and the overall PPV was 0.08. Combination of rule effectiveness and PPV was highest for clinical rules based upon the risk category "basic computerized physician order entry (CPOE) medication safety alerts fine-tuned to high risk patients" (rule efficiency=0.17; PPV=0.14).
ADEAS can effectively be used in daily hospital pharmacy practice to select patients at risk of potential ADEs, but to increase the benefits for routine patient care and to increase efficiency, both rule effectiveness and PPV for the clinical rules should be improved. Furthermore, clinical rules would have to be refined and restricted to those categories that are potentially most promising for clinical relevance, i.e. "clinical rules with a combination of pharmacy and laboratory data" and "clinical rules based upon the basic CPOE medication safety alerts fine-tuned to high risk patients".
我们的先进临床决策支持(CDS)系统,名为“药物不良事件警报系统”(ADEAS),在我们医院的药剂科中被广泛使用。它被医院药剂师用于筛选可能发生药物不良事件(ADE)的患者。该系统从多个信息系统中检索数据,并使用临床规则来筛选有 ADE 风险的患者。临床规则均与药物相关,并使用七个风险类别进行制定。
本研究旨在评估 CDS 系统 ADEAS 在日常医院药剂科实践中的使用情况,并评估系统中包含的临床规则的有效性和阳性预测值(PPV)。
荷兰莱顿大学医学中心。所有在六个不同的内科和心脏病学病房住院的患者均被纳入研究。
结果指标包括警报总数、有警报的患者数以及这些警报的结果:医院药剂师是否提供了预防可能的 ADE 的建议。分别对总体规则有效性和 PPV 以及每个临床规则风险类别中的规则有效性和 PPV 进行评分。
在为期 5 个月的研究期间,ADEAS 每天生成安全警报。医院药剂师对所有警报进行评估,如果需要,联系医疗保健专业人员并提供建议以预防可能的 ADE。
在研究期间,ADEAS 在 931 名患者中生成了 2650 个安全警报。在 270 个警报(10%)中,医院药剂师联系了医生或护士,其中 204 个(76%)案例导致了预防可能的 ADE 的建议。其余 2380 个警报(90%)被评为无关。大多数警报是通过链接药房和实验室数据的临床规则生成的(1685 个警报)。总体规则有效性为 0.10,总体 PPV 为 0.08。基于“基本计算机化医嘱录入(CPOE)药物安全警报微调至高危患者”风险类别制定的临床规则的规则有效性和 PPV 的组合最高(规则效率=0.17;PPV=0.14)。
ADEAS 可有效地用于日常医院药剂科实践,以筛选有潜在 ADE 风险的患者,但为了提高常规患者护理的效益并提高效率,应提高临床规则的有效性和 PPV。此外,临床规则应进行细化,并限制在对临床相关性最有潜力的类别,即“具有药房和实验室数据相结合的临床规则”和“基于基本 CPOE 药物安全警报微调至高危患者的临床规则”。