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How can Never Event data be used to reflect or improve hospital safety performance?
Olivarius-McAllister, J; Pandit, M; Sykes, A; Pandit, J J.
Afiliação
  • Olivarius-McAllister J; Department of Respiratory Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Pandit M; Department of Respiratory Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Sykes A; Department of Respiratory Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
  • Pandit JJ; Department of Respiratory Medicine, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Anaesthesia ; 76(12): 1616-1624, 2021 12.
Article em En | MEDLINE | ID: mdl-33932033
ABSTRACT
The absolute number of Never Events is used by UK regulators to help assess hospital safety performance, without account of hospital workload. We applied funnel plots, as an established means of taking workload into account, to published Never Event data for 151 acute Trusts in NHS England, matched to finished consultant episodes for 3 years, 2017-2020. Trusts with excess event rates should have the most Never Events if absolute number is a valid way to judge performance. The absolute number of Never Events was correlated with workload (r2 = 0.51, p < 0.001), but the five Trusts above the upper 95% confidence limit did not have the highest number of Never Events. However, a limitation to interpretation was that the data were skewed; 12 out of 151 Trusts lay below the lower 95% limit. This skew probably arises because funnel plots pool all Never Events and workload data; whereas, ideally, different Never Events should use as denominator only the relevant workload actions that could cause them. We conclude that the manner in which Never Event data are currently used by regulators, in part to judge or rate hospitals, is mathematically invalid. The focus should shift from identifying 'outlier' hospitals to reducing the overall national mean Never Event rate through shared learning and an integrated system-wide approach.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Erros Médicos / Segurança do Paciente Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Erros Médicos / Segurança do Paciente Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article