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Abstract(s)
Introdução: Ainda estamos longe de conhecer a realidade portuguesa relativamente ao que é a Segurança do Doente, sendo imperativo pensar em estratégias que fomentem a identificação de Eventos Adversos (EAs). A ICU Adverse Event Trigger Tool, desenvolvida pelo Institute for Healthcare Improvement (IHI) e publicada a janeiro de 2002, providencia um manual de instruções para uma revisão retrospetiva de processos clínicos, utilizando triggers que identificam possíveis EAs na Unidade de Cuidados Intensivos (UCI). Esta ferramenta mede o nível de dano que pode ser experienciado na prestação de cuidados de saúde. Objetivos: Aplicação da ICU Adverse Event Trigger Tool do IHI na UCI do Centro Hospitalar Universitário Cova da Beira (CHUCB) para identificar, medir e categorizar EAs. Métodos: Estudo retrospetivo e descritivo realizado na UCI do CHUCB. Da listagem de todos os processos clínicos que tiveram lugar entre 1 de janeiro e 31 de dezembro de 2017, foram analisados os que tinham os seguintes critérios de inclusão: pacientes com idade superior a 18 anos, processos clínicos completos, com mais de 2 dias de internamento e com alta clínica naquele mesmo ano. A ICU Adverse Event Trigger Tool foi aplicada a cada processo clínico da amostra por dois revisores. O tratamento e análise de dados teve o auxílio do software estatístico IBM SPSS Statistics 25. Resultados: Foram analisados 118 processos clínicos. 48,3% dos pacientes que foram internados na UCI estiveram anteriormente no Serviço de Urgência. 26,3% dos pacientes analisados morreram na UCI. Um total de 81 triggers foram detetados em 41 pacientes e o número médio de triggers por paciente com triggers positivos foi de 1,98. Foram encontrados EAs em 39 processos clínicos. Os seis triggers com maior prevalência foram a Hemocultura Positiva, Intubação/Reintubação, Elevação dos níveis de azoto ureico sérico e/ou creatinina sérica duas vezes acima do valor basal, Pneumonia com início na UCI, Readmissão na UCI e Diálise de novo. Houve 10 tipos de triggers sem qualquer ocorrência. A maioria dos EAs são de categoria F. Existe uma correlação forte e significativa entre o número de dias de internamento, o número de triggers e o número de potenciais EAs. Conclusões: A ICU Adverse Event Trigger Tool é prática na deteção de triggers e na medição de EAs na UCI. No entanto, é fundamental a adaptação da ferramenta ao contexto nacional e do profissional de saúde. A avaliação dos Eventos Adversos que ocorreram no passado permite criar medidas de alerta e prevenção para a UCI do futuro.
Introduction: We are still far from a thorough knowledge of the national reality regarding what is the Patient Safety and it is imperative to think of strategies that encourage the identification of Adverse Events (AEs). The ICU Adverse Event Trigger Tool, developed by the Institute for Healthcare Improvement (IHI) and published in January 2002, provides an instruction manual for a retrospective review of clinical charts using triggers that identify possible AEs in the Intensive Care Unit (ICU). This tool measures the level of harm that can be experienced in providing health care. Objectives: Application of the ICU Adverse Event Trigger Tool (ICU) to identify, measure and categorize AEs in the ICU of Cova da Beira University Hospital Center (CHUCB). Methodology: Retrospective and descriptive study carried at the ICU of CHUCB. Clinical charts between January 1st and December 31st 2017, were abstracted with the following inclusion criteria: patients over 18 years of age, fully completed clinical records, with more than 2 days of hospitalization and with discharge in that same year. IHI’s ICU Adverse Event Trigger Tool was applied to each clinical chart from the sample by two reviewers. Data processing and analysis was aided by the statistical software IBM SPSS Statistics 25. Results: A total of 118 clinical trials were analyzed. 48.3% of the patients came from the Emergency Department. 26.3% of the patients analyzed died in the ICU. A total of 81 triggers were detected in 41 patients and the mean number of triggers per patient per patient was 1.98. EAs were found in 39 clinical charts. The six triggers with the highest prevalence were: Positive Hemoculture, Intubation / Reintubation, Elevation of blood urea nitrogen and serum creatinine two times above baseline, Pneumonia with ICU onset, ICU Readmission and New onset dialysis. There were 10 types of triggers without any occurrence. Most AEs were category F. There is a strong and significant correlation between the number of days of hospitalization, the number of triggers and the number of AEs. Conclusions: The ICU Adverse Event Trigger Tool it’s a practical tool in the detection of triggers and measurment of AEs in the ICU. However, an adaptation to the national context and to the health professional are essential. The evaluation of adverse events that have occurred in the past is a form of awareness and prevention for the ICU of the future.
Introduction: We are still far from a thorough knowledge of the national reality regarding what is the Patient Safety and it is imperative to think of strategies that encourage the identification of Adverse Events (AEs). The ICU Adverse Event Trigger Tool, developed by the Institute for Healthcare Improvement (IHI) and published in January 2002, provides an instruction manual for a retrospective review of clinical charts using triggers that identify possible AEs in the Intensive Care Unit (ICU). This tool measures the level of harm that can be experienced in providing health care. Objectives: Application of the ICU Adverse Event Trigger Tool (ICU) to identify, measure and categorize AEs in the ICU of Cova da Beira University Hospital Center (CHUCB). Methodology: Retrospective and descriptive study carried at the ICU of CHUCB. Clinical charts between January 1st and December 31st 2017, were abstracted with the following inclusion criteria: patients over 18 years of age, fully completed clinical records, with more than 2 days of hospitalization and with discharge in that same year. IHI’s ICU Adverse Event Trigger Tool was applied to each clinical chart from the sample by two reviewers. Data processing and analysis was aided by the statistical software IBM SPSS Statistics 25. Results: A total of 118 clinical trials were analyzed. 48.3% of the patients came from the Emergency Department. 26.3% of the patients analyzed died in the ICU. A total of 81 triggers were detected in 41 patients and the mean number of triggers per patient per patient was 1.98. EAs were found in 39 clinical charts. The six triggers with the highest prevalence were: Positive Hemoculture, Intubation / Reintubation, Elevation of blood urea nitrogen and serum creatinine two times above baseline, Pneumonia with ICU onset, ICU Readmission and New onset dialysis. There were 10 types of triggers without any occurrence. Most AEs were category F. There is a strong and significant correlation between the number of days of hospitalization, the number of triggers and the number of AEs. Conclusions: The ICU Adverse Event Trigger Tool it’s a practical tool in the detection of triggers and measurment of AEs in the ICU. However, an adaptation to the national context and to the health professional are essential. The evaluation of adverse events that have occurred in the past is a form of awareness and prevention for the ICU of the future.
Description
Keywords
Evento Adverso Segurança do Doente Trigger Tool Triggers Unidade de Cuidados Intensivos