Risk Assessment In Health Care Research Articles

COVID-19: Risk assessment and mitigation measures in healthcare and non-healthcare workplaces

The coronavirus disease-2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), is the third emerging human coronavirus, leading to fatal respiratory distress and pneumonia. The disease originated in December 2019 in Wuhan City, Hubei province, China. As of 23 November 2021, over 258 million cases and 5.1 million deaths have been reported in more than 222 countries and territories worldwide. The COVID-19 is under biological hazards group 4 of high risk of spreading to the community with the potential to overwhelm the health system, especially in resource limited countries. Transmission of COVID-19 within healthcare and non-healthcare facilities has been recorded. Therefore, several authorities such as the World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC), and other global partners issued guidance to mitigate the COVID-19 pandemic in these facilities. A global emergency due to the COVID-19 pandemic requires various studies of mitigation measures and risk assessment. The Failure Mode and Effects Analysis (FMEA) was used as a tool for risk assessment in healthcare and clinical fields that assigns a numerical value to each risk associated with failure. Therefore, in this review, the FMEA procedure was used to evaluate the COVID-19 risks and risk groups in health care and non-healthcare workplaces. Proposed mitigation measures and risk ranking tools were also summarized. The COVID-19 transmission risk should be theoretically and practically reduced by applying the best hygienic practices. However, providing safe work practices must be improved for infection control measures in healthcare and non-healthcare workplaces. Additionally, it is recommended to reassess the risk of COVID-19 infection from time to time, especially after vaccines availability.

Risk Evaluation Using Nominal Group Technique for Cloud Computing Risk Assessment in Healthcare

Emerging of cloud computing with flexibility, improve accessing data, and cost-saving makes this technology accessible and growing fast. As a result of the emergence of cloud computing bring interest to industries to used cloud computing. Although cloud computing brings so many benefits to customers, the previous study reveals that cloud computing penetration in the Healthcare area is still low. With effective cloud risk assessment methodology will gain the confidence to cloud users in this technology. Study in cloud risk assessment methodology still infant and the complexity in identifying security risk still debating. This paper explores the risk assessment process by highlighting the method in the risk evaluation process. Risk evaluation is an essential phase in the risk assessment process. It compares the result from the risk analysis process and determines whether to accept or tolerate the risk criteria to decide on the risk analysis. In this study, the Nominal Group Technique (NGT) is introduced to compare risk analysis results in the earlier phase. Since risk evaluation based on organizational objectives, external and internal context and stakeholders' views, NGT is promising for effective results. This study not only contributing to the prioritizing list of risks and threats in a systematical manner but indirectly NGT process makes stakeholders aware of the current cloud security risk situation in the organization. Equal opportunity expressing views in this focus group discussion is hope can generate a brilliant solution in risk assessment results.

Dynamic risk assessment in healthcare based on Bayesian approach

Risks related with healthcare are always dynamic, and they are affected by situations of patients, human errors in treatment and even the states of medical devices. This paper proposes a dynamic medical risk assessment model, for capturing the impacts of factors on the occurrence of adverse events. In this model, a static fault tree is established to show risk scenarios. Dynamic Bayesian network and Bayesian inference are introduced to analyze the operations of medical devices, in consideration of their failures, repairs, and human errors over time. Hemodialysis infection is taken as the case to verify that the proposed method is helpful to demonstrate the changes of medical risks with time, and to identify the critical events contributing to the occurrence of the adverse event at different moments. These findings can act as the basis to assign and adjust safety measures.

Designing for Risk Assessment Systems for Patient Triage in Primary Health Care: A Literature Review.

BackgroundThis literature review covers original journal papers published between 2011 and 2015. These papers review the current status of research on the application of human factors and ergonomics in risk assessment systems’ design to cope with the complexity, singularity, and danger in patient triage in primary health care.ObjectiveThis paper presents a systematic literature review that aims to identify, analyze, and interpret the application of available evidence from human factors and ergonomics to the design of tools, devices, and work processes to support risk assessment in the context of health care.MethodsElectronic search was performed on 7 bibliographic databases of health sciences, engineering, and computer sciences disciplines. The quality and suitability of primary studies were evaluated, and selected papers were classified according to 4 classes of outcomes.ResultsA total of 1845 papers were retrieved by the initial search, culminating in 16 selected for data extraction after the application of inclusion and exclusion criteria and quality and suitability evaluation.ConclusionsResults point out that the study of the implications of the lack of understanding about real work performance in designing for risk assessment in health care is very specific, little explored, and mostly focused on the development of tools.

Designing for patient risk assessment in primary health care: a case study for ergonomic work analysis

In this paper, we study the importance of a consistent description of real work in patient risk assessment in the primary healthcare domain. Through a case study in the context of primary health care, we address the research problem of finding ways to build consistent real work descriptions of the patient risk assessment system in the primary healthcare domain, in order to foster the design of improved work situations and support devices. This is a qualitative field study based on ethnographic observation and semi-structured interviews carried out among professionals involved in the risk assessment process in a primary healthcare facility. The objects of ergonomic work analysis were work places and work situations with focus on human activity, as well as surrounding aspects. The analysis identified elements in the work domain with high cognitive demand and operations that could increase mental workload, providing elements for the earlier stages of the design of work situations and support devices to improve the risk assessment in primary health care. This paper shows the usefulness of real work descriptions in the design for complex situations like the risk assessment in health care, as well the impact of poor descriptions in generating harmful situations for both the patient and healthcare practitioners in the explored domain.

A Model for Risk Assessment in Health Care Using a Health Care Failure Method and Effect Analysis

AbstractObjective: The purpose of this research is to track and reduce risks so as to prevent errors within the process of health care. The aim is to design an organizational information model using error prevention methods for risk assessment.Method: In order to assess the risk of errors, the Health Care Failure Mode and Effect Analysis is used. To determine the causes of the errors, the Root Cause Analysis is used.Results: Results of the process analysis following corrective measures shows that the risk assessment of individual error causes reduced by73.6 percent. Re-evaluation of the risks to the whole process shows that the overall risk score was decreased by 45.5 percent. The proposed model has a significant impact on professional attention, communication and information, critical thinking, experience and knowledge. The average impact of information communication technology on the reduction of medication administration errors is 56 percent. These findings represent an increase in the quality of care.Conclusions: The results of our research are theoretically and practically useful and verifiable in other environments, if the level of the organizational culture and the culture of recording errors in combination with the precise recording of data to assess the risk of errors in the process. The model provides a standardized data format that can be used for the purpose of defining factors for the occurrence of errors, for developing a base of knowledge for learning from mistakes and for continuous verification and adaptation to changes in the environment in order to prevent errors.

Managing Risk: Clinical Decision-Making in Mental Health Services

Risk assessment and management is a major component of contemporary mental health practice. Risk assessment in health care exists within contemporary perspectives of management and risk aversive practices in health care. This has led to much discussion about the best approach to assessing possible risks posed by people with mental health problems. In addition, researchers and commentators have expressed concern that clinical practice is being dominated by managerial models of risk management at the expense of meeting the patient's health and social care needs. The purpose of the present study is to investigate the risk assessment practices of a multidisciplinary mental health service. Findings indicate that mental health professionals draw on both managerial and therapeutic approaches to risk management, integrating these approaches into their clinical practice. Rather than being dominated by managerial concerns regarding risk, the participants demonstrate professional autonomy and concern for the needs of their clients.