Data collection information provided

With such a system for an isolated source, adequate data can be obtained in 1 year to determine the impact of the sources on the air quality of the area. There are very few instances where less than 1 year of data collection will provide adequate information because of variability in climatic conditions on an annual basis. 

The following techniques can be used to collect data about human performance in CPI tasks and provide input to task analysis methods described in Section 4.3. These data can include process information critical for the task, control strategies used by the workers, diagnostic plans etc. A distinction can be made among data collection methods that provide qualitative data (such as interviews, observations, and sources of documentation) and methods that can be used to measure aspects of performance (such as activity analysis, simulations, and information withholding). The latter methods can provide more precise data which can be quantified. 

The types of data required for incident reporting and root cause analysis systems are specified. Data Collection practices in the CPI are described, and a detailed specification of the types of information needed for causal analyses is provided. 

This section provides information on the personnel who should be involved in data collection and the design of reporting forms. The specific data needs for major incident analyses are discussed, together with the storage and retrieval of data for the purpose of analysis. 

The function of this section is to provide an overall framework within which to describe the important aspects of data collection systems in the CPI. As mentioned in the introduction, the emphasis in this chapter will be on methods for identifying the causes of errors that have led to accidents or significant near misses. This information is used to prevent reoccurrence of similar accidents, and to identify the underlying causes that may give rise to new types of accidents in the future. Data collection thus has a proactive accident prevention function, even though it is retrospective in the sense that it is usually carried out after an accident or near miss has already occurred. 

The first area focuses on the cultural and organizational factors that will have a major influence on the effectiveness of a human error data collection system and how well the information derived from such a system is translated into successful error reduction strategies. Regardless of how effectively the technical issues are dealt with, the system will not be successful imless there is a culture in the organization which provides support for the data gathering process. No data collection system aimed at identifying human error causes of accidents will be workable without the active cooperation of the workforce. 

As discussed earlier, most data collection systems in the CPI place considerable emphasis on the "what," but provide little support for the "how" or "why." Causal analysis methods can be broadly divided into techniques which emphasize the structure of an accident and those which focus on causes. Structural techniques provide information on the "what" and "how," and the causal techniques enable the "why" to be investigated. 

Individuals involved in accidents where error was a possible factor can have access to a computer which will allow them to provide information on a confidential basis. Although portable computers have not yet made a significant impact on incident data collection, there is clearly considerable potential in this area. 

Since the resources for data collection systems will be provided by senior management it is essential that information from the system is fed back to policy makers at this level. It is also important that the system indicates the problem areas as well as the successes. Many organizations have drifted to a state where safety standards have fallen to below acceptable levels over time as a result of suppression of information feedback to senior managers. This may be carried out with good intentions, but its long-term effect can be disastrous. 

When selecting in-process measures, try to use measures for which data are already available. For example, avoid using in-service failure data unless the maintenance systems can make this information readily available. These measures will be used to identify potential problems and correct them as early as possible. During the development of the integrated systems, data that will be available for in-process measurement should be identified and measures developed. These measures are most likely to be calculated annually as the volume of data required to provide useful data will be collected only over relatively long periods of time. 

Plant-specific data are frequently unavailable or are low in their level of confidence. Further, this source of data cannot provide information on equipment not in use at the plant, nor can it do more than suggest how plant equipment might behave under different circumstances. Since data collection is very difficult, using shared or generic data is one way of resolving these problems without the expense of extensive data collection systems. 

To help the reader select the appropriate data resource, an index precedes Sections 4.3 through 4.8. The index provides the source number within the section and the following set of data elements for each source title, industry, number and type of records, and data boundary. Appendix C contains additional information about the data elements presented in each data resource. It can also be used to help identify the resources which may provide data for a CPQRA. A discussion of the Appendix C Matrix and an explanation of data elements indexed is presented. After examining Appendix C and the pattern of data elements contained in the data resources, it is evident that equipment reliability data have been published in a variety of formats, often without any apparent effort to conform to a recognized standard for data specification. The CCPS Taxonomy and the raw data collection requirements in Chapter 6 present the basis for reliability data specification in future literature. 

Three reports have been issued containing IPRDS failure data. Information on pumps, valves, and major components in NPP electrical distribution systems has been encoded and analyzed. All three reports provide introductions to the IPRDS, explain failure data collections, discuss the type of failure data in the data base, and summarize the findings. They all contain comprehensive breakdowns of failure rates by failure modes with the results compared with WASH-1400 and the corresponding LER summaries. Statistical tables and plant-specific data are found in the appendixes. Because the data base was developed from only four nuclear power stations, caution should be used for other than generic application. 

WASH-1400 is a fundamental document for PRA methodology. The data appendixes contain a great deal of useful information on methods of data assessment. A large number of sources for data are considered, and very general failure rate estimates will produce only gross approximations. Since the advent of data collection schemes across and within plants, the WASH-1400 data are solely useful as a constituent to a data aggregation process or as widely bounded figures that provide a basis for comparison. 

Data collection procedures must be established to capture the required information. Various methods have been proposed for collecting such data, including a draft international standard that provides criteria for collecting data in nuclear power plants.i These criteria are also useful in developing methodologies for collection of data within the CPI. Smith and Babb provide additional information beyond that presented in this book. 

A more serious problem is that we lose all kinetic information about the system until the data collection begins, and ultimately this limits the rates that can be studied. For first-order reactions we may be able to sacrifice the data contained in the first one, two, or three half-lives, provided the system amplitude is adequate that is, the remaining extent of reaction must be quantitatively detectable. However, this practice of basing kinetic analyses on the last few percentage of reaction is subject to error from unknown side reactions or analytical difficulties. 

Although each of the commercially available computer-based vibration monitoring systems has unique features and formats, the information contained in this chapter is applicable to all of the systems. However, the manual provided by the vendor should be used in conjunction with this chapter to ensure proper use of the microprocessor-based data collection analyzer and the computer-based software. 

Assessments are both initial and ongoing. An initial assessment is made based on objective and subjective data collected when the patient is first seen in a hospital, outpatient clinic, health care provider s office, or other type of health care facility. The initial assessment usually is more thorough and provides a database (sometimes called baseline) from which later data can be compared and decisions made The initial assessment provides information that is analyzed to identify... 

Web-based data collection and management systems provide a mechanism for remote data entry, where entered data are added to a centralized database once the submit button is pressed. They can be designed to automate the various aspects of clinical trials such as eligibility evaluation, data collection, and tracking specimens. They also serve as a resource site for participating sites to access trial-specific information, facilitate communication, track data queries and their resolutions, and allow administrative management of trials [28, 29]. For these reasons, they play an important role in facilitating the conduct of international clinical trials. 

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