Patient safety risk assessment and risk management: A review on Indian hospitals

2011 ◽  
Vol 2 (4) ◽  
pp. 186 ◽  
Author(s):  
Gaurav Sharma ◽  
Anuj Dixit ◽  
Swapnil Awasthi ◽  
Garima Sharma
2019 ◽  
Vol 26 (3) ◽  
pp. 770-785
Author(s):  
Hossam Elamir

Purpose The growing importance of risk management programmes and practices in different industries has given rise to a new risk management approach, i.e. enterprise risk management. The purpose of this paper is to better understand the necessity, benefit, approaches and methodologies of managing risks in healthcare. It compares and contrasts between the traditional and enterprise risk management approaches within the healthcare context. In addition, it introduces bow tie methodology, a prospective risk assessment tool proposed by the American Society for Healthcare Risk Management as a visual risk management tool used in enterprise risk management. Design/methodology/approach This is a critical review of published literature on the topics of governance, patient safety, risk management, enterprise risk management and bow tie, which aims to draw a link between them and find the benefits behind their adoption. Findings Enterprise risk management is a generic holistic approach that extends the benefits of risk management programme beyond the traditional insurable hazards and/or losses. In addition, the bow tie methodology is a barrier-based risk analysis and management tool used in enterprise risk management for critical events related to the relevant day-to-day operations. It is a visual risk assessment tool which is used in many higher reliability industries. Nevertheless, enterprise risk management and bow ties are reported with limited use in healthcare. Originality/value The paper suggests the applicability and usefulness of enterprise risk management to healthcare, and proposes the bow tie methodology as a proactive barrier-based risk management tool valid for enterprise risk management implementation in healthcare.


2004 ◽  
Vol 39 (5) ◽  
pp. 20-21
Author(s):  
Donna Vanderpool

2021 ◽  
Vol 14 (01) ◽  
pp. 77-86
Author(s):  
Bhima Shakti Arrafat

Every practical activity carried out by student at Aircraft Engineering Departement, then these activities have risks that need mitigation measures. In safety risk management requires departement to conduct an assessment of the risks that can occur from an activity using hazard identification, risk assessment and mitigation. By identifying types of hazards, assessing risks, getting results in the form of risk matrix and risk level and identifying mitigation actions that can be taken and accepted. Furthermore, it produces hazard identification and risk assessment & mitigation (HIRAM) documents, and controls risks to acceptable and tolerable levels with mitigation measures. Safety risk management which is one of the standards in implementing safety management system in Aircraft Engineering Departement can be fulfilled.


2020 ◽  
Vol 37 (7) ◽  
pp. 1251-1268
Author(s):  
Christopher A. Roseman ◽  
Brian M. Argrow

AbstractAs the number of applications for small unmanned (i.e., remotely operated) aircraft systems (sUAS) continues to grow, comprehensive safety risk assessment studies are required to ensure their safe integration into the National Airspace System. One source of hazards for sUAS that has not been extensively addressed is adverse weather. A framework is presented for analyzing weather forecast data to provide sUAS operators with risk assessment information that they can use for making risk-aware decisions. The sUAS Weather Risk Model (sWRM) framework quantifies weather hazard risk for sUAS operations in rural to urban environments using weather forecast, population density, structure density, and sUAS data. sWRM is developed by following the safety risk management guidelines from the U.S. Federal Aviation Administration. Development of sWRM highlights a number of aerospace and meteorological research areas that must be addressed prior to weather risk models for sUAS becoming operational. Primary among these research areas is developing widely available finescale (<1 km) weather forecasts and conducting extensive sUAS flight-report studies to accurately estimate parameters of Bayesian belief network conditional probability tables used in the proposed framework. As a proof of concept, sWRM was applied over Boulder, Colorado, using the High-Resolution Rapid Refresh weather product. This initial demonstration of sWRM highlights the potential effectiveness of a detailed risk assessment model that takes into account high-resolution weather and environmental data.


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