Marisol Samartín-Ucha1, José Castro-Domínguez2, Hadriana Fernández-Vega3, Guadalupe Piñeiro-Corrales4. 1. Pharmacy Department, University Hospital of Vigo. Servizo Galego de Saude, Vigo. marisol.samartin.ucha@sergas.es. 2. Pharmacy Department, University Hospital of Vigo. Servizo Galego de Saude, Vigo. jmcastro@povisa.es. 3. Pharmacy Department, University Hospital of Vigo. Servizo Galego de Saude, Vigo. hadriana.fernandez.vega@sergas.es. 4. Pharmacy Department, University Hospital of Vigo. Servizo Galego de Saude, Vigo. guadalupe.pineiro.corrales@sergas.es.
Abstract
OBJECTIVE: To classify hospital units into three risk levels in order to define and prioritise improvement and training measures in each of them. METHOD: 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. RESULTS: 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. CONCLUSIONS: 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. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.
OBJECTIVE: To classify hospital units into three risk levels in order to define and prioritise improvement and training measures in each of them. METHOD: 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. RESULTS: 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. CONCLUSIONS: 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. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.