Data collection/analysis safety

CCPS G-56. 1998. Guidelines for Improving Plant Reliability through Data Collection and Analysis. American Institute of Chemical Engineers, Center for Chemical Process Safety, New York. 

The focus of this chapter has been on proactive application of these analytical methods such as safety audits, development of procedures, training needs analysis, and equipment design. However, many of these methods can also be used in a retrospective mode, and this issue deserves further attention in its own right. Chapter 6 describes analytical methods for accident investigations and data collection. 

Another publication produced by the Center for Chemical Process Safety, Guidelines for Investigating Chemical Process Incidents (CCPS, 1992d), is directed at achieving similar objectives but from a differing perspective and with differing emphasis. Both sources of information can be used in a complementary manner to improve the quality of data collection and incident analysis in the CPI. 

It is therefore easy to see why this current drug safety paradigm, with its lack of standards in data collection and analysis, hinders the analysis of adverse events. Without data standards in place, it is difficult to build practical, reusable tools for systematic safety analysis. With no standard tools, truly standardized analyses cannot occur. Reviewers may forget their initial analytical processes if they are not using standardized data and tools. Comprehensive reproducibility and auditability, therefore, become nearly impossible. In practice, the same data sets and analytical processes cannot be easily reused, even by the same reviewers who produced the original data sets and analyses. Not using standardized tools slows the real-time systematic analysis... 

One approach is to mesh all investigation and root cause analysis activities under one management system for investigation. Such a system must address all four business drivers (1) process and personnel safety, (2) environmental responsibility, (3) quality, and (4) profitability. This approach works well since techniques used for data collection, causal factor analysis, and root cause analysis can be the same regardless of the type of incident. Many companies realize that root causes of a quality or reliability incident may become the root cause of a safety or process safety incident in the future and vice versa. 

The comments here focus on the statistical review of the NDA. The major difference between an IND and an NDA submission is that, when the NDA is submitted, the studies proposed in the IND have been conducted, and analysis and interpretation of the data collected are included. The FDA s review of the NDA focuses on determining if it finds the evidence concerning safety, efficacy, and manufacturing ability to be compelling and if it is therefore prepared to approve the drug for marketing. The FDA s statistical reviewers play a major role in making this determination. Statistical reviewers typically review both the Statistics and Clinical Data sections, and they are also available to review other sections. 

The previous chapter discussed the (currently) relatively loosely defined statistical approaches to safety data collected in clinical trials. In contrast, there are widely accepted statistical methods for demonstrating efficacy in clinical trials. As has been noted several times in this book, if the study design and methodology have been appropriate and have led to the collection of optimum quality data, the statistical analysis and interpretation of efficacy data are relatively straightforward. The clinical (biological) interpretation of efficacy data is typically not quite as clear-cut, but there are widely accepted methodologies that are very useful in this realm too. Of particular importance here is the expert judgment of the clinicians who will review the statistical results with the statisticians and the rest of the study team. 

Besides regulatory development and enforcement, other OPS functions include pipeline safety data analysis based on data collected by OPS through annual and incident reports from the industry and from OPS inspections of pipeline systems, sponsoring of research, and training. 

Following the collection, analysis, and interpretation of the in vivo and in vitro information and data pertaining to the current state of the art with respect to the safety and performance of prosthetic heart valves (mechanical and tissue), we conclude that ... 

Perform safety audits, performance assessments, and inspections using the hazard analysis results as the preconditions for operations and maintenance. Collect data to ensure safety policies and procedures are being followed and that education and training about safety is effective. Establish feedback channels for leading indicators of increasing risk. 

The PSAP is part of a well-defined, coordinated, program-wide approach that may help facilitate the planning, collection, and assessment of safety data during drug development. It provides a useful means to facilitate standardization of data collection and data analysis among the studies of the product. This proactive approach can make data integration easier and may avoid problems with inconsistency in data collection and analysis. This can enable better detection of potential safety issues and better understanding of them. 

Shorf of prospectively collecting fhe safety outcome, the outcome can be retrospectively obtained and adjudicated with a well-defined procedure. This approach was faken in fhe antidepressant meta-analysis example in this chapter. This approach requires detailed extensive patient-level data. It is also helpful to have fhe individual sfudy protocol to understand the information collected in fhe frials. Wifh fhis version of a retrospective outcome ascertainment, attention should be given to potential differential outcome ascertainment between the treatment arms. If the outcome was not actively solicited, there may be differences in reporting between the arms because of unrelated side effecfs of fhe freafmenf. For example, if a drug has more side effecfs, fhe patienf may be more likely to have encounters with the study investigators and report the safety outcome. 

Reliability and Safety Data Collection and Analysis Fault Identification and Diagnostics Maintenance Modelling and Optimisation Structural Reliability and Design Codes Software Reliability Consequence Modelling Uncertainty and Sensitivity Analysis Safety Culture Organizational Learning Human Factors... 

ABSTRACT Demonstrating compliance with reliability targets in the operational phase is a key requirement in the follow-up of safety instrumented systems. This paper describes a new approach for demonstrating such comphance, taking into accoimt the information from reported failures. This includes to update the failure rate and to make decisions regarding the functional test interval. A brief discussion of some practical experience with data collection and analysis in the operational phase is also included. The main focus is on safety instrumented systems in the oil and gas industry, but the approach may be applicable for other industry sectors as well. 

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