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Zhang Y, Liu T. Risk assessment based on a STPA-FMEA method: A case study of a sweeping robot. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2023; 43:590-604. [PMID: 35383984 DOI: 10.1111/risa.13927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Despite rapid developments in the quality and safety of consumer products, the rise of intelligent household appliances, such as sweeping robots, has introduced new safety concerns. Considering "person-product-environment" elements and the complex systems of emerging consumer products, this study presents a new method of risk assessment for consumer products: systems theoretic process analysis (STPA)-failure mode and effects analysis (FMEA). As a case study, this method is applied to the safety control of a sweeping robot. The results suggest that this method can identify all the possible failure modes and injury scenarios among the product components, and the safety constraints in the hierarchical control structure of the interactive system. Moreover, the STPA-FMEA method combines user and environmental factors with the value of product risk events, based on the risk priority number (RPN). This provides an accurate and orderly system to reduce or eliminate the root causes of accidents and injuries. Finally, analysis of unsafe control behavior and its causes can be used to suggest improved safety constraints, which can effectively reduce the risk of some injury scenarios. This paper presents a new method of risk assessment for consumer products and a general five-level complex index system.
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Affiliation(s)
- Yanxi Zhang
- School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, China
| | - Tiezhong Liu
- School of Management and Economics, Beijing Institute of Technology, Beijing, China
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2
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Kaya GK. A system safety approach to assessing risks in the sepsis treatment process. APPLIED ERGONOMICS 2021; 94:103408. [PMID: 33711556 DOI: 10.1016/j.apergo.2021.103408] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 02/23/2021] [Accepted: 02/26/2021] [Indexed: 06/12/2023]
Abstract
In healthcare, most accidents occur as a result of inadequate interactions between system components rather than component failures. In such cases traditional risk analysis methods are of limited use for analysing system safety, so methods such as Systems Theoretic Process Analysis (STPA) and the Functional Resonance Analysis Method (FRAM) have been developed. This study uses STPA to assess risks in the sepsis treatment process, discusses the potential value STPA adds and compares the results of STPA with the results of another study that used FRAM. The findings indicate that STPA and FRAM have different strengths which reflect the different scientific approaches behind these two methods. FRAM facilitates an in-depth understanding of a system, while STPA allows for more comprehensive risk analysis by identifying more risks, scenarios and safety recommendations. Nevertheless, it is reasonable to say that not only does STPA provide more comprehensive risk analysis; its terminology and philosophy are also closer to the current safety management applications employed in complex systems.
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Affiliation(s)
- Gulsum Kubra Kaya
- Industrial Engineering, Faculty of Engineering and Natural Sciences, Istanbul Medeniyet University, Uskudar, Istanbul, Turkey.
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McLeod R, Russell W, Stewart M, Prentice M, Bowie P. Preliminary case report study of training and support needed to conduct bowtie analysis in healthcare. BMJ Open Qual 2021; 10:bmjoq-2020-001240. [PMID: 34162661 PMCID: PMC8230928 DOI: 10.1136/bmjoq-2020-001240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 05/22/2021] [Indexed: 11/05/2022] Open
Abstract
Background There is limited engagement in healthcare with the kinds of proactive approaches to risk assessment used in other industries. Bowtie analysis (BTA) has previously been shown to have potential as a straightforward approach to proactively assessing risk in healthcare. The visual nature of BTA diagrams can aid communication of the essential elements of a complex risk management system. The aim of this small case report study was to investigate the training and support likely to be needed for existing healthcare professionals to conduct BTA in compliance with recognised industry best-practice. Method Of 17 volunteers who attended training, 3 completed an analysis of significant healthcare risks in the study period: misadministration of gentamicin; unknown development of acute kidney injury and disposal of medical devices containing patient identifiable information (PII). Subjective assessments of the quality of the analyses were made against indicators of BTA best-practice. Results Use of the BTA method led to a deeper understanding of the issues and a more thorough understanding of the risks and what was needed to control them than would have been the case if ‘normal practice’ had been followed. Classroom-based training supported by written guidance; however, do not appear adequate to support development of competence to carry out a quality BTA in a healthcare setting. Conclusions BTA seems to have potential though further evaluation of its application and utility is necessary. The most cost-effective and productive approach is likely to be to train a small number of people to develop deeper skills and experience in BTA. In addition to training and user guidance, the opportunity to facilitate at least one analysis, with some specialist/trainer support, appears to be essential in developing BTA competence.
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Affiliation(s)
| | - Wendy Russell
- Acute Medicine, University Hospital Crosshouse, Kilmarnock, UK
| | | | - Mark Prentice
- Medical Physics, Queen Elizabeth University Hospital Campus, Glasgow, UK
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Bas E. STPA methodology in a socio-technical system of monitoring and tracking diabetes mellitus. APPLIED ERGONOMICS 2020; 89:103190. [PMID: 32854823 DOI: 10.1016/j.apergo.2020.103190] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2019] [Revised: 05/30/2020] [Accepted: 06/09/2020] [Indexed: 05/25/2023]
Abstract
In this paper, an adaptation of the system-theoretic process analysis (STPA) approach to a sociotechnical system of monitoring and tracking diabetes mellitus (DM) is proposed. Several human controllers such as the patient, physicians, other healthcare providers, and people in the social environment were considered in the hierarchical safety control structure. During the identification of the causal factors (causal scenarios) for the unsafe control actions of the human controllers, the three-phase approach proposed by France (2017) as well as the interaction problems between the subsystems in the hierarchical safety control structure were considered, and the implementation of the basic safety design procedure was included in the methodology for the improvement of system. A dynamic STPA methodology is also proposed as an extension to the basic methodology.
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Affiliation(s)
- Esra Bas
- Istanbul Technical University, Department of Industrial Engineering, Macka, 34367, Istanbul, Turkey.
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5
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Abstract
The purpose is to show the advantages of a Bowtie diagram as a versatile tool for displaying and understanding the evolvement and management of critical incidents.
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Xie Y, Gunasekeran DV, Balaskas K, Keane PA, Sim DA, Bachmann LM, Macrae C, Ting DSW. Health Economic and Safety Considerations for Artificial Intelligence Applications in Diabetic Retinopathy Screening. Transl Vis Sci Technol 2020; 9:22. [PMID: 32818083 PMCID: PMC7396187 DOI: 10.1167/tvst.9.2.22] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Accepted: 01/23/2020] [Indexed: 02/06/2023] Open
Abstract
Systematic screening for diabetic retinopathy (DR) has been widely recommended for early detection in patients with diabetes to address preventable vision loss. However, substantial manpower and financial resources are required to deploy opportunistic screening and transition to systematic DR screening programs. The advent of artificial intelligence (AI) technologies may improve access and reduce the financial burden for DR screening while maintaining comparable or enhanced clinical effectiveness. To deploy an AI-based DR screening program in a real-world setting, it is imperative that health economic assessment (HEA) and patient safety analyses are conducted to guide appropriate allocation of resources and design safe, reliable systems. Few studies published to date include these considerations when integrating AI-based solutions into DR screening programs. In this article, we provide an overview of the current state-of-the-art of AI technology (focusing on deep learning systems), followed by an appraisal of existing literature on the applications of AI in ophthalmology. We also discuss practical considerations that drive the development of a successful DR screening program, such as the implications of false-positive or false-negative results and image gradeability. Finally, we examine different plausible methods for HEA and safety analyses that can be used to assess concerns regarding AI-based screening.
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Affiliation(s)
- Yuchen Xie
- Singapore National Eye Center, Singapore Eye Research Institute, Singapore
| | - Dinesh V Gunasekeran
- Singapore National Eye Center, Singapore Eye Research Institute, Singapore
- School of Medicine, National University of Singapore, Singapore
| | | | - Pearse A Keane
- Moorfields Eye Hospital, National Health Service, London, UK
| | - Dawn A Sim
- Moorfields Eye Hospital, National Health Service, London, UK
| | - Lucas M Bachmann
- Clinical Epidemiology, University of Zurich, Zurich, Switzerland
| | - Carl Macrae
- Business School, Nottingham University, Nottingham, UK
| | - Daniel S W Ting
- Singapore National Eye Center, Singapore Eye Research Institute, Singapore
- School of Medicine, Duke-National University of Singapore, Singapore
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, Guangdong, China
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Lamé G, Liberati E, Burt J, Draycott T, Winter C, Ward J, Dixon-Woods M. IMproving the practice of intrapartum electronic fetal heart rate MOnitoring with cardiotocography for safer childbirth (the IMMO programme): protocol for a qualitative study. BMJ Open 2019; 9:e030271. [PMID: 31256041 PMCID: PMC6609047 DOI: 10.1136/bmjopen-2019-030271] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Revised: 05/22/2019] [Accepted: 06/10/2019] [Indexed: 11/30/2022] Open
Abstract
INTRODUCTION Suboptimal electronic fetal heart rate monitoring (EFM) in labour using cardiotocography (CTG) has been identified as one of the most common causes of avoidable harm in maternity care. Training staff is a frequently proposed solution to reduce harm. However, current approaches to training are heterogeneous in content and format, making it difficult to assess effectiveness. Technological solutions, such as digital decision support, have not yet demonstrated improved outcomes. Effective improvement strategies require in-depth understanding of the technical and social mechanisms underpinning the EFM process. The aim of this study is to advance current knowledge of the types of errors, hazards and failure modes in the process of classifying, interpreting and responding to CTG traces. This study is part of a broader research programme aimed at developing and testing an intervention to improve intrapartum EFM. METHODS AND ANALYSIS The study is organised into two workstreams. First, we will conduct observations and interviews in three UK maternity units to gain an in-depth understanding of how intrapartum EFM is performed in routine clinical practice. Data analysis will combine the insights of an ethnographic approach (focused on the social norms and interactions, values and meanings that appear to be linked with the process of EFM) with a systems thinking approach (focused on modelling processes, actors and their interactions). Second, we will use risk analysis techniques to develop a framework of the errors, hazards and failure modes that affect intrapartum EFM. ETHICS AND DISSEMINATION This study has been approved by the West Midlands-South Birmingham Research Ethics Committee, reference number: 18/WM/0292. Dissemination will take the form of academic articles in peer-reviewed journals and conferences, along with tailored communication with various stakeholders in maternity care.
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Affiliation(s)
- Guillaume Lamé
- The Healthcare Improvement Studies Institute (THIS Institute), University of Cambridge, Cambridge, UK
| | - Elisa Liberati
- The Healthcare Improvement Studies Institute (THIS Institute), University of Cambridge, Cambridge, UK
| | - Jenni Burt
- The Healthcare Improvement Studies Institute (THIS Institute), University of Cambridge, Cambridge, UK
| | - Tim Draycott
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- Women and Children's Health, North Bristol NHS Trust, Westbury on Trym, UK
| | - Cathy Winter
- School of Social and Community Medicine, University of Bristol, Bristol, UK
- Women and Children's Health, North Bristol NHS Trust, Westbury on Trym, UK
| | - James Ward
- Engineering Design Centre, University of Cambridge, Cambridge, UK
| | - Mary Dixon-Woods
- The Healthcare Improvement Studies Institute (THIS Institute), University of Cambridge, Cambridge, UK
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Kaya GK, Ward J, Clarkson J. A Review of Risk Matrices Used in Acute Hospitals in England. RISK ANALYSIS : AN OFFICIAL PUBLICATION OF THE SOCIETY FOR RISK ANALYSIS 2019; 39:1060-1070. [PMID: 30395689 DOI: 10.1111/risa.13221] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/04/2017] [Revised: 09/27/2018] [Accepted: 10/03/2018] [Indexed: 06/08/2023]
Abstract
In healthcare, patient safety has received substantial attention and, in turn, a number of approaches to managing safety have been adopted from other high-risk industries. One of these has been risk assessment, predominantly through the use of risk matrices. However, while other industries have criticized the design and use of these risk matrices, the applicability of such criticism has not been investigated formally in healthcare. This study examines risk matrices as used in acute hospitals in England and the guidance provided for their use. It investigates the applicability of criticisms of risk matrices from outside healthcare through a document analysis of the risk assessment policies, procedures, and strategies used in English hospitals. The findings reveal that there is a large variety of risk matrices used, where the design of some might increase the chance of risk misprioritization. Additionally, findings show that hospitals may provide insufficient guidance on how to use risk matrices as well as what to do in response to the existing criticisms of risk matrices. Consequently, this is likely to lead to variation in the quality of risk assessment and in the subsequent deployment of resources to manage the assessed risk. Finally, the article outlines ways in which hospitals could use risk matrices more effectively.
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Affiliation(s)
- Gulsum Kubra Kaya
- Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, UK
| | - James Ward
- Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, UK
| | - John Clarkson
- Engineering Design Centre, Department of Engineering, University of Cambridge, Cambridge, UK
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