High reliability organizations (HROs), such as the aviation industry, successfully engage in high-risk endeavors and have low incidence of adverse events. HROs have a preoccupation with failure and errors. They analyze each event to effect system wide change in an attempt to mitigate the occurrence of similar errors. The healthcare industry can adapt HRO practices, specifically with regard to teamwork and communication. Crew resource management concepts can be adapted to healthcare with the use of certain tools such as checklists and the sterile cockpit to reduce medication errors. HROs also use The Swiss Cheese Model to evaluate risk and look for vulnerabilities in multiple protective barriers, instead of focusing on one failure. This model can be used in medication safety to evaluate medication management in addition to using the teamwork and communication tools of HROs.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4469723 | PMC |
http://dx.doi.org/10.1007/s13181-015-0471-2 | DOI Listing |
J Health Organ Manag
January 2025
Amrita School of Business - Amritapuri Kollam Campus, Kollam, India.
Purpose: This paper aims to delve into the critical aspect of supplier selection in the healthcare sector, emphasizing the significance of strategic sourcing in enhancing operational efficiency and quality of services. The primary aim is to develop a comprehensive framework for supplier evaluation that aligns with the unique requirements of hospitals, ultimately improving procurement processes and patient care outcomes.
Design/methodology/approach: The study leverages the renowned Carter's 7 C model as a foundational framework for supplier assessment, supplemented by insights gathered from interviews with experts in the New Product Introduction, Purchasing and Procurement departments of a leading hospital in India.
J Cancer Educ
January 2025
Department of Pharmacy, Al Rafidain University College, 10001, Baghdad, Iraq.
Chemotherapy-drug interactions (CDIs) pose significant challenges in oncology, affecting treatment efficacy and patient safety. Despite their importance, there is a lack of validated tools to assess oncologists' knowledge of CDIs. This study aimed to develop and validate a comprehensive questionnaire to address this gap and ensure the reliability and validity of the instrument.
View Article and Find Full Text PDFJ Cancer Res Clin Oncol
January 2025
Department of Gynecology, University Medical Center Hamburg-Eppendorf, Martinistrasse 52, 20246, Hamburg, Germany.
Objective: In advanced ovarian cancer, the majority of patients receive anti-angiogenic treatment with bevacizumab. However, its use is often associated with severe side effects, and not all patients benefit from the therapy. Currently, there are no reliable biomarkers to predict response to treatment.
View Article and Find Full Text PDFGenes Genomics
January 2025
Department of Pediatric Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, 450000, Henan, China.
Background: The clinical course of high-risk neuroblastoma patients remains suboptimal, and the dynamic and reversible nature of cellular senescence provides an opportunity to develop new therapies.
Objective: This study aims to identify unique markers of cellular senescence in neuroblastoma and to explore their clinical significance.
Methods: The impact of multiple genetic regulatory mechanisms on cellular senescence-associated genes (CSAGs) was first assessed.
BMJ Glob Health
January 2025
Unit of HIV and Tuberculosis, Institute of Tropical Medicine Department of Clinical Sciences, Antwerpen, Belgium.
Introduction: The WHO endorsed the Xpert MTB/RIF (Xpert) technique since 2011 as initial test to diagnose rifampicin-resistant tuberculosis (RR-TB). No systematic review has quantified the proportion of pretreatment attrition in RR-TB patients diagnosed with Xpert in high TB burden countries.Pretreatment attrition for RR-TB represents the gap between patients diagnosed and those who effectively started anti-TB treatment regardless of the reasons (which include pretreatment mortality (death of a diagnosed RR-TB patient before starting adequate treatment) and/or pretreatment loss to follow-up (PTLFU) (drop-out of a diagnosed RR-TB patient before initiation of anti-TB treatment).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!