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Int J Qual Health Care ; 31(2): 110-116, 2019 Mar 01.
Artigo em Inglês | MEDLINE | ID: mdl-29788153

RESUMO

OBJECTIVE: To examine if clustering of root causes of sentinel events (SEs) can contribute to organisational improvement of healthcare and patient safety by providing insight into organisational risk factors, patterns and trends. DESIGN: Retrospective, cross-sectional review of SEs from a hospital database reported to the Board of directors in 2016. SETTING: A regional teaching hospital in the Netherlands. INTERVENTION(S): Clustering of characteristics and variables of SEs to establish vulnerabilities and patterns of failure factors of the organisation. MAIN OUTCOME MEASURE(S): Characteristics and contributory causes of failure of SEs identified via root cause analysis (RCA). Outcomes reported using descriptive statistics. RESULTS: A total of 21 events were included involving 21 patients. Mean age was 56.7 years (SD 24.4), 71.4% were above 50 years of age. In 81.8%, the care was multi-disciplinary and in 76.2% the event resulted in permanent harm or injury. Of the 132 identified contributory root causes, most were related to human factors (53.8%) and organisational factors (40.2%). Technical and patient-related factors were identified in 3.0%. Organisational improvement strategies focused on the care of elderly patients, patients subjected to multi-disciplinary care and on improving knowledge, protocols and coordination of care. CONCLUSION: Clustering variables of SEs and contributory factors of failure through RCA helps to delineate a hospital-specific profile by providing a detailed insight into risk factors, patterns and trends in an organisation and to determine the best strategies for improvement by drawing lessons across events.


Assuntos
Erros Médicos/estatística & dados numéricos , Segurança do Paciente/normas , Gestão da Segurança/métodos , Adulto , Idoso , Idoso de 80 Anos ou mais , Estudos Transversais , Feminino , Administração Hospitalar/métodos , Hospitais de Ensino/organização & administração , Humanos , Lactente , Masculino , Erros Médicos/mortalidade , Pessoa de Meia-Idade , Países Baixos , Estudos Retrospectivos , Análise de Causa Fundamental/métodos
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