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2.
Home Healthc Now ; 37(6): 365-366, 2019.
Artigo em Inglês | MEDLINE | ID: mdl-31688478
3.
Jt Comm J Qual Patient Saf ; 44(11): 643-650, 2018 Nov.
Artigo em Inglês | MEDLINE | ID: mdl-30190221

RESUMO

BACKGROUND: There are no reliable estimates of hospital inpatient suicides in the United States. Understanding the rate and the methods used in suicides is important to guide prevention efforts. This study analyzed two national data sets to establish an evidence-based estimate of hospital inpatient suicides and the methods used. METHODS: The study is designed as a cross-sectional analysis of data from 27 states reporting to the National Violent Death Reporting System (NVDRS) for 2014-2015, and from hospitals reporting to The Joint Commission's Sentinel Event (SE) Database from 2010 to 2017. Categorical variables and qualitative reviews of event narratives were used to identify and code suicide events occurring during hospital inpatient treatment. RESULTS: Based on the hospital inpatient suicides reported in the NVDRS during 2014-2015, 73.9% of which occurred during psychiatric treatment, it is estimated that between 48.5 and 64.9 hospital inpatient suicides occur per year in the United States. Of these, 31.0 to 51.7 are expected to involve psychiatric inpatients. Hanging was the most common method of inpatient suicide in both the NVDRS and SE databases (71.7% and 70.3%, respectively). CONCLUSION: The estimated number of hospital inpatient suicides per year in the United States ranges from 48.5 to 64.9, which is far below the widely cited figure of 1,500 per year. Analysis of inpatient suicide methods suggests that hospital prevention efforts should be primarily focused on mitigating risks associated with hanging, and additional suicide prevention efforts may be best directed toward reducing the risk of suicide immediately following discharge.


Assuntos
Hospitais/estatística & dados numéricos , Pacientes Internados/estatística & dados numéricos , Suicídio/estatística & dados numéricos , Causas de Morte , Estudos Transversais , Humanos , Unidade Hospitalar de Psiquiatria/estatística & dados numéricos , Vigilância em Saúde Pública/métodos , Características de Residência , Suicídio/prevenção & controle , Estados Unidos/epidemiologia
4.
Jt Comm J Qual Patient Saf ; 42(2): 70-6, 2016 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-26803035

RESUMO

BACKGROUND: An understanding of how health information technology (health IT) can contribute to sentinel events is necessary to learn how to safely implement and use health IT. An analysis was conducted to explore how health IT may contribute to adverse events that result in death or severe harm to the patient. METHODS: For 3,375 de-identified sentinel events voluntarily reported to The Joint Commission between January 1, 2010, and June 30, 2013, categorical and keyword queries were used to search for potential health IT-related events. Each of the identified events was reviewed on the basis of findings from root cause analyses (RCAs) to determine if health IT contributed to or caused the event, and if so, how and why. The contributing factors were classified using a composite of existing classification schemes. RESULTS: A total of 120 health IT-related sentinel events (affecting 125 patients) were identified. More than half resulted in patient death, 30% resulted in unexpected or additional care, and 11% resulted in permanent loss of function. The three most frequently identified event types were (1) medication errors, (2) wrong-site surgery (including the wrong side, wrong procedure, and wrong patient), and (3) delays in treatment. Contributing factors were most frequently associated with the human-computer interface, workflow and communication, and clinical content-related issues. CONCLUSIONS: The classification of health IT-related contributing factors indicates that health IT-related events are primarily associated with the sociotechnical dimensions of human-computer interface, workflow and communication, and clinical content. Improved identification of health IT-related contributing factors in the context of the sociotechnical dimensions may help software developers, device manufacturers, and end users in health care organizations proactively identify vulnerabilities and hazards, ultimately reducing the risk of harm to patients.


Assuntos
Sistemas de Informação/estatística & dados numéricos , Erros Médicos/estatística & dados numéricos , Comunicação , Computadores , Humanos , Erros Médicos/classificação , Erros de Medicação/estatística & dados numéricos , Políticas , Análise de Causa Fundamental , Vigilância de Evento Sentinela , Software , Fatores de Tempo , Fluxo de Trabalho
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