Samartín-Ucha Marisol, Castro-Domínguez José, Fernández-Vega Hadriana, Piñeiro-Corrales Guadalupe
Pharmacy Department, University Hospital of Vigo. Servizo Galego de Saude, Vigo.
Farm Hosp. 2019 May 1;43(3):110-115. doi: 10.7399/fh.11175.
To classify hospital units into three risk levels in order to define and prioritise improvement and training measures in each of them.
The risk map was developed in two phases: First phase involved the setting up of a multidisciplinary team, a bibliographic search, the identification of medications and of the criteria to design the map: (1) Location: number of high-alert medications; (2) Staff turnover: the units were classified in low turnover units = 1, medium turnover units = 2 and high turnover units = 3 according to data provided by the human resource department; (3) Frequency: quotient between the number of high alert medicactions in each unit and the total of medications used, and (4) Severity: voluntary survey of professionals. An accumulated risk of severity of each unit was calculated: Σ (severity of the drug x number of its units). The Neperian logarithm was applied to this value to reduce the variability of the values. Thus a risk probability index was established = staff turnover x frecuency x Neperian logarithm of severity. In a second phase, the units were classified into three groups and the risk map of high-alert medication was elaborated in the hospital. In it, the units that had a risk probability index higher than 2.9 were classified as high risk units, those that had between 1-2.9 as intermediate risk units and those that had less than 1 as low risk units. According to the risk probability index, improvement measures were defined and priorities were set for each of them.
A total 447 high-risk medications corresponding to 227 active ingredients were identified during the study period. The units showing a higher risk were: Intensive Care Medicine (10.51), Reanimation (4.01), and Palliative Care (3.90). Improvement actions (informative poster, visual identification, alerts, training and double checks) were defined and prioritised in accordance with the risk probability index.
Knowing the degree of risk of hospitalization units in the management of high-alert medications allows for the implementation of improvement plans in relation to the degree of vulnerability detected.
将医院科室分为三个风险等级，以便确定每个科室的改进和培训措施并确定其优先级。
风险地图分两个阶段绘制：第一阶段包括组建多学科团队、进行文献检索、确定药物以及设计地图的标准：（1）位置：高警示药物数量；（2）人员流动率：根据人力资源部门提供的数据，科室被分为低人员流动率科室=1、中等人员流动率科室=2和高人员流动率科室=3；（3）频率：每个科室高警示药物数量与所用药物总数的商，以及（4）严重程度：专业人员的自愿调查。计算每个科室严重程度的累积风险：Σ（药物严重程度×其科室数量）。对该值应用自然对数以降低值的变异性。由此建立风险概率指数=人员流动率×频率×严重程度的自然对数。在第二阶段，科室被分为三组，并绘制了医院高警示药物风险地图。其中，风险概率指数高于2.9的科室被列为高风险科室，1 - 2.9之间的为中等风险科室，低于1的为低风险科室。根据风险概率指数，确定改进措施并为每个科室设定优先级。
在研究期间共识别出447种对应227种活性成分的高风险药物。风险较高的科室有：重症医学科（10.51）、复苏科（4.01）和姑息治疗科（3.90）。根据风险概率指数确定并优先安排了改进措施（信息海报、视觉识别、警示、培训和双重核对）。
了解住院科室在高警示药物管理中的风险程度有助于根据检测到的脆弱程度实施改进计划。
