When non-significance maybe significant: lessons learned from a study into the development, implementation and evaluation of a risk assessment tool for fleet settings

Introduction This study reports on the development of a self report assessment tool to increase the efficacy of crash prediction within Australian Fleet settings Over last 20 years an array of measures have been produced (Driver anger scale, Driving Skill Inventory, Manchester Driver Behaviour Questionnaire, Driver Attitude Questionnaire, Driver Stress Inventory, Safety Climate Questionnaire) While these tools are useful, research has demonstrated limited ability to accurately identify individuals most likely to be involved in a crash. Reasons cited include; - Crashes are relatively rare - Other competing factors may influence crash event - Ongoing questions regarding the validity of self report measures (common method variance etc) - Lack of contemporary issues relating to fleet driving performance

When non-significance may be significant : lessons learned from a study of the development, implementation and evaluation of a fleet risk assessment tool

This paper reports on the development and implementation of a self-report risk assessment tool that was developed in an attempt to increase the efficacy of crash prediction within Australian fleet settings. This study forms a part of a broader program of research into work related road safety and identification of driving risk. The first phase of the study involved a series of focus groups being conducted with 217 professional drivers which revealed that the following factors were proposed to influence driving performance: Fatigue, Knowledge of risk, Mood, Impatience and frustration, Speed limits, Experience, Other road users, Passengers, Health, and Culture. The second phase of the study involved piloting the newly developed 38 item Driving Risk Assessment Scale - Work Version (DRAS-WV) with 546 professional drivers. Factor analytic techniques identified a 9 factor solution that was comprised of speeding, aggression, time pressure, distraction, casualness, awareness, maintenance, fatigue and minor damage. Speeding and aggressive driving manoeuvres were identified to be the most frequent aberrant driving behaviours engaged in by the sample. However, a series of logistic regression analyses undertaken to determine the DRAS-WV scale’s ability to predict self-reported crashes revealed limited predictive efficacy e.g., 10% of crashes. This paper outlines proposed reasons for this limited predictive ability of the DRAS-WV as well as provides suggestions regarding the future of research that aims to develop methods to identify “at risk” drivers.

Predicting the likelihood of non-healing : a venous leg ulcer risk assessment tool

This project developed, validated and tested reliability of a risk assessment tool to predict the risk of failure to heal of patients with venous leg ulcers within 24 weeks. The risk assessment tool will allow clinicians to be able to determine realistic outcomes for their patients, promote early healing and potentially avoid weeks of inappropriate therapy. The tool will also assist in addressing specific risk factors and guide decisions on early, alternative, tailored interventions.

The challenge of developing a fleet driving risk assessment tool: What can be learned from the process?

One of the riskiest activities in the course of a person's work is driving. By developing and testing a new work driving risk assessment measurement tool for use by organisations this research will contribute to the safety of those who drive for work purposes. The research results highlighted limitations associated with current self-report measures and provided evidence that the work driving environment is extremely complex and involves constant interactions between humans, vehicles, the road environment, and the organisational context.

Randomized trial of a computerized coronary heart disease risk assessment tool in HIV-infected patients receiving combination antiretroviral therapy

Exposure to combination antiretroviral therapy (cART) can lead to important metabolic changes and increased risk of coronary heart disease (CHD). Computerized clinical decision support systems have been advocated to improve the management of patients at risk for CHD but it is unclear whether such systems reduce patients' risk for CHD.

Proposal on How To Conduct a Biopharmaceutical Process Failure Mode and Effect Analysis (FMEA) as a Risk Assessment Tool

With the publication of the quality guideline ICH Q9 "Quality Risk Management" by the International Conference on Harmonization, risk management has already become a standard requirement during the life cycle of a pharmaceutical product. Failure mode and effect analysis (FMEA) is a powerful risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to biopharmaceutical processes brings about some difficulties. The proposal presented here is intended to serve as a brief but nevertheless comprehensive and detailed guideline on how to conduct a biopharmaceutical process FMEA. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. The application for such a biopharmaceutical process FMEA is widespread. It can be useful whenever a biopharmaceutical manufacturing process is developed or scaled-up, or when it is transferred to a different manufacturing site. It may also be conducted during substantial optimization of an existing process or the development of a second-generation process. According to their resulting risk ratings, process parameters can be ranked for importance and important variables for process development, characterization, or validation can be identified. LAY ABSTRACT: Health authorities around the world ask pharmaceutical companies to manage risk during development and manufacturing of pharmaceuticals. The so-called failure mode and effect analysis (FMEA) is an established risk analysis tool that has been used for decades in mechanical and electrical industries. However, the adaptation of the FMEA methodology to pharmaceutical processes that use modern biotechnology (biopharmaceutical processes) brings about some difficulties, because those biopharmaceutical processes differ from processes in mechanical and electrical industries. The proposal presented here explains how a biopharmaceutical process FMEA can be conducted. It includes a detailed 1-to-10-scale FMEA rating table for occurrence, severity, and detectability of failures that has been especially designed for typical biopharmaceutical processes. With the help of this guideline, different details of the manufacturing process can be ranked according to their potential risks, and this can help pharmaceutical companies to identify aspects with high potential risks and to react accordingly to improve the safety of medicines.

A high-resolution map of direct and indirect connectivity of erosion risk areas to surface waters in Switzerland: A risk assessment tool for planning and policy-making

Off-site effects of soil erosion are becoming increasingly important, particularly the pollution of surface waters. In order to develop environmentally efficient and cost effective mitigation options it is essential to identify areas that bear both a high erosion risk and high connectivity to surface waters. This paper introduces a simple risk assessment tool that allows the delineation of potential critical source areas (CSA) of sediment input into surface waters concerning the agricultural areas of Switzerland. The basis are the erosion risk map with a 2 m resolution (ERM2) and the drainage network, which is extended by drained roads, farm tracks, and slope depressions. The probability of hydrological and sedimentological connectivity is assessed by combining soil erosion risk and extended drainage network with flow distance calculation. A GIS-environment with multiple-flow accumulation algorithms is used for routing runoff generation and flow pathways. The result is a high resolution connectivity map of the agricultural area of Switzerland (888,050 ha). Fifty-five percent of the computed agricultural area is potentially connected with surface waters, 45% is not connected. Surprisingly, the larger part of 34% (62% of the connected area) is indirectly connected with surface waters through drained roads, and only 21% are directly connected. The reason is the topographic complexity and patchiness of the landscape due to a dense road and drainage network. A total of 24% of the connected area and 13% of the computed agricultural area, respectively, are rated with a high connectivity probability. On these CSA an adapted land use is recommended, supported by vegetated buffer strips preventing sediment load. Even areas that are far away from open water bodies can be indirectly connected and need to be included in planning of mitigation measures. Thus, the connectivity map presented is an important decision-making tool for policy-makers and extension services. The map is published on the web and thus available for application.

The development of poultry farms risk assessment tool for avian influenza in Imo State, Nigeria

Background: Nigeria was one of the 13 countries where avian influenza outbreak in poultry farms was reported during the 2006 avian influenza pandemic threat and was also the first country in Africa to report the presence of H5N1influenza among its poultry population. There are multiple hypotheses on how the avian influenza outbreak of 2006 was introduced to Nigeria, but the consensus is that once introduced, poultry farms and their workers were responsible for 70% of the spread of avian influenza virus to other poultry farms and the population. ^ The spread of avian influenza has been attributed to lack of compliance by poultry farms and their workers with poultry farm biosecurity measures. When poultry farms fail to adhere to biosecurity measures and there is an outbreak of infectious diseases like in 2006, epidemiological investigations usually assess poultry farm biosecurity—often with the aid of a questionnaire. Despite the importance of questionnaires in determining farm compliance with biosecurity measures, there have been few efforts to determine the validity of questionnaires designed to assess poultry farms risk factors. Hence, this study developed and validated a tool (questionnaire) that can be used for poultry farm risk stratification in Imo State, Nigeria. ^ Methods: Risk domains were generated using literature and recommendations from agricultural organizations and the Nigeria government for poultry farms. The risk domains were then used to develop a questionnaire. Both the risk domain and questionnaire were verified and modified by a group of five experts with a research interest in Nigeria's poultry industry and/or avian influenza prevention. Once a consensus was reached by the experts, the questionnaire was distributed to 30 selected poultry farms in Imo State, Nigeria that participated in this study. Survey responses were received for all the 30 poultry farms that were selected. The same poultry farms were visited one week after they completed the questionnaires for on-site observation. Agreement among survey and observation results were analyzed using a kappa test and rated as poor, fair, moderate, substantial, or nearly perfect; and internal consistency of the survey was also computed. ^ Result: Out of the 43 items on the questionnaire, 32 items were validated by this study. The agreement between the survey result and onsite observation was analyzed using kappa test and ranged from poor to nearly perfect. Most poultry farms had their best agreements in the contact section of the survey. The least agreement was noted in the farm management section of the survey. Thirty-two questions on the survey had a coefficient alpha > 0.70, which is a robust internal consistency for the survey. ^ Conclusion: This study developed 14 risk domains for poultry farms in Nigeria and validated 32 items from the original questionnaire that contained 43 items. The validated items can be used to determine the risk of introduction and spread of avian influenza virus in poultry farms in Imo State, Nigeria. After further validations in other states, regions and poultry farm sectors in Nigeria; this risk assessment tool can then be used to determine the risk profile of poultry farms across Nigeria.^