O Guzmán-Ruiz1, P Ruiz-López2, A Gómez-Cámara3, M Ramírez-Martín4. 1. Medicina Interna, Hospital Santa Bárbara, Puertollano, Ciudad Real, España. Electronic address: oguzmanruiz@yahoo.es. 2. Coordinación de Calidad, Hospital Universitario 12 de Octubre, Madrid, España. 3. Instituto de Investigación-Unidad de Investigación Clínica, Hospital Universitario 12 de Octubre, Madrid, España. 4. Aparato Digestivo, Hospital Santa Bárbara, Puertollano, Ciudad Real, España.
Abstract
OBJECTIVES: To identify and characterize adverse events (AE) in an Internal Medicine Department of a district hospital using an extension of the Global Trigger Tool (GTT), analyzing the diagnostic validity of the tool. METHODS: An observational, analytical, descriptive and retrospective study was conducted on 2013 clinical charts from an Internal Medicine Department in order to detect EA through the identification of 'triggers' (an event often related to an AE). The 'triggers' and AE were located by systematic review of clinical documentation. The AE were characterized after they were identified. RESULTS: A total of 149 AE were detected in 291 clinical charts during 2013, of which 75.3% were detected directly by the tool, while the rest were not associated with a trigger. The percentage of charts that had at least one AE was 35.4%. The most frequent AE found was pressure ulcer (12%), followed by delirium, constipation, nosocomial respiratory infection and altered level of consciousness by drugs. Almost half (47.6%) of the AE were related to drug use, and 32.2% of all AE were considered preventable. The tool demonstrated a sensitivity of 91.3% (95%CI: 88.9-93.2) and a specificity of 32.5% (95%CI: 29.9-35.1). It had a positive predictive value of 42.5% (95%CI: 40.1-45.1) and a negative predictive value of 87.1% (95%CI: 83.8-89.9). CONCLUSIONS: The tool used in this study is valid, useful and reproducible for the detection of AE. It also serves to determine rates of injury and to observe their progression over time. A high frequency of both AE and preventable events were observed in this study.
OBJECTIVES: To identify and characterize adverse events (AE) in an Internal Medicine Department of a district hospital using an extension of the Global Trigger Tool (GTT), analyzing the diagnostic validity of the tool. METHODS: An observational, analytical, descriptive and retrospective study was conducted on 2013 clinical charts from an Internal Medicine Department in order to detect EA through the identification of 'triggers' (an event often related to an AE). The 'triggers' and AE were located by systematic review of clinical documentation. The AE were characterized after they were identified. RESULTS: A total of 149 AE were detected in 291 clinical charts during 2013, of which 75.3% were detected directly by the tool, while the rest were not associated with a trigger. The percentage of charts that had at least one AE was 35.4%. The most frequent AE found was pressure ulcer (12%), followed by delirium, constipation, nosocomial respiratory infection and altered level of consciousness by drugs. Almost half (47.6%) of the AE were related to drug use, and 32.2% of all AE were considered preventable. The tool demonstrated a sensitivity of 91.3% (95%CI: 88.9-93.2) and a specificity of 32.5% (95%CI: 29.9-35.1). It had a positive predictive value of 42.5% (95%CI: 40.1-45.1) and a negative predictive value of 87.1% (95%CI: 83.8-89.9). CONCLUSIONS: The tool used in this study is valid, useful and reproducible for the detection of AE. It also serves to determine rates of injury and to observe their progression over time. A high frequency of both AE and preventable events were observed in this study.
Authors: Maria das Dores Graciano Silva; Maria Auxiliadora Parreiras Martins; Luciana de Gouvêa Viana; Luiz Guilherme Passaglia; Renata Rezende de Menezes; João Antonio de Queiroz Oliveira; Jose Luiz Padilha da Silva; Antonio Luiz Pinho Ribeiro Journal: Br J Clin Pharmacol Date: 2018-07-08 Impact factor: 4.335
Authors: Luisa C Eggenschwiler; Anne W S Rutjes; Sarah N Musy; Dietmar Ausserhofer; Natascha M Nielen; René Schwendimann; Maria Unbeck; Michael Simon Journal: PLoS One Date: 2022-09-01 Impact factor: 3.752