Applying Healthcare Failure Mode and Effect Analysis and the Development of a Real-Time Mobile Application for Modified Early Warning Score Notification to Improve Patient Safety During Hemodialysis.
J Patient Saf
; 18(5): 475-485, 2022 08 01.
Article
em En
| MEDLINE
| ID: mdl-35121722
OBJECTIVE: Patients undergoing hemodialysis are a high-risk population. This study identified possible errors by using a healthcare failure mode and effect analysis system to improve patient safety during hemodialysis. METHODS: A multidisciplinary collaborative team, including physicians, nurses, information technicians, and medical staff members, was assembled. A flow diagram was used to indicate each process of the hemodialysis procedure from evaluating patient condition to transporting the patient back to the ward from the hemodialysis center. We scored all possible failure modes using the hazard scoring method as a combination of the occurrence frequency and severity. These potential failure modes were used to identify and evaluate possible risks by using a risk scoring matrix. RESULTS: Thirty failure modes were identified across 6 processes, and their potential causes were explored. Four major strategies for addressing most of the failure modes were implemented: establishment of a mobile application that sends real-time automated alerts to the medical team based on the Modified Early Warning Score, design of a modified dialysis Identify-Situation-Background-Assessment-Recommendation checklist for dialysis, technician education and training, and internal auditing and monitoring of the implementation of the entire process. After the implementation of the strategies, the hazard scores of patients during dialysis dropped by 71.2% from 170 points to 49 points. CONCLUSIONS: The healthcare failure mode and effect analysis system was useful for evaluating potential risk during dialysis. Using the mobile application reduced the occurrence of emergency resuscitation during hemodialysis and significantly improved the communication between medical personnel.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Aplicativos Móveis
/
Análise do Modo e do Efeito de Falhas na Assistência à Saúde
/
Escore de Alerta Precoce
Tipo de estudo:
Prognostic_studies
/
Screening_studies
Limite:
Humans
Idioma:
En
Revista:
J Patient Saf
Assunto da revista:
SERVICOS DE SAUDE
Ano de publicação:
2022
Tipo de documento:
Article
País de publicação:
Estados Unidos