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Real-time management of incident learning reports in a radiation oncology department.
Wright, Jean L; Parekh, Arti; Rhieu, Byung-Han; Opris, Valentina; Souranis, Annette; Choflet, Amanda; Viswanathan, Akila N; DeWeese, Theodore L; McNutt, Todd; Terezakis, Stephanie A.
Afiliação
  • Wright JL; Johns Hopkins University, Department of Radiation Oncology, Baltimore, Maryland. Electronic address: jwrigh71@jhmi.edu.
  • Parekh A; Johns Hopkins University, Department of Radiation Oncology, Baltimore, Maryland.
  • Rhieu BH; Johns Hopkins University, Department of Radiation Oncology, Baltimore, Maryland.
  • Opris V; Johns Hopkins University, Department of Radiation Oncology, Baltimore, Maryland.
  • Souranis A; Johns Hopkins University, Department of Radiation Oncology, Baltimore, Maryland.
  • Choflet A; Johns Hopkins University, Department of Radiation Oncology, Baltimore, Maryland.
  • Viswanathan AN; Johns Hopkins University, Department of Radiation Oncology, Baltimore, Maryland.
  • DeWeese TL; Johns Hopkins University, Department of Radiation Oncology, Baltimore, Maryland.
  • McNutt T; Johns Hopkins University, Department of Radiation Oncology, Baltimore, Maryland.
  • Terezakis SA; Johns Hopkins University, Department of Radiation Oncology, Baltimore, Maryland.
Pract Radiat Oncol ; 8(5): e337-e345, 2018.
Article em En | MEDLINE | ID: mdl-29907503
ABSTRACT

PURPOSE:

The optimal approach to managing incident learning system (ILS) reports remains unclear. Here, we describe our experience with prospective coding of events reported to the ILS with comparisons of risk scores on the basis of event type and process map location. METHODS AND MATERIALS Reported events were coded by type, origin, and method of discovery. Events were given a risk priority number (RPN) and near-miss risk index (NMRI) score. We compared workflow versus near-miss events with respect to origin and detection in the process map and by risk scores. A χ2 test was used to compare the differences between workflow and near-miss events. A comparison of RPN scores was done by independent t test.

RESULTS:

During 2016, 1351 events were reported. Of these events, 1300 (96.2%) were workflow and 51 (3.8%) near-miss events. Workflow events were more likely to both originate (1041 of 1300 events; 81.2%) compared with near-miss events (31 of 51 events; 62.7%; P = .005) and be detected in pre-treatment (997 of 1300 events; 76.7%) compared with near-miss events (24 of 51 events; 47%; P < .001). Average occurrence (scale 1-10) was 6.14 for workflow versus 3.33 for near-miss events (P < .001), average severity was 2.94 versus 7.35 (P < .001), and average detectability was 1.33 versus 4.67 (P < .001). Mean overall RPN was 22.4 for workflow versus 108.4 for near-miss events (P = .07) and mean NMRI was 1.16 versus 3.19, respectively. Events that originated and were detected in treatment delivery had the greatest mean overall RPN (38.2 and 32.1, respectively) and NMRI scores (1.62 and 1.6, respectively).

CONCLUSIONS:

Our experience demonstrates that workflow event reports are far more common than near-misses and that near-miss events are more likely to both originate and be discovered in later treatment phases. The frequency of workflow reports highlights the imperative need for safety and operational teams to work collaboratively to maximize the benefit of ILS. We suggest a potential utility of the RPN system to guide mitigation strategies for future near-miss events.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Lesões por Radiação / Gestão de Riscos / Radioterapia (Especialidade) / Erros Médicos / Neoplasias Tipo de estudo: Etiology_studies / Evaluation_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Lesões por Radiação / Gestão de Riscos / Radioterapia (Especialidade) / Erros Médicos / Neoplasias Tipo de estudo: Etiology_studies / Evaluation_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article