Types of Data Collection Systems

Many data collection systems place the primary emphasis on the technical causes of accidents. There is usually a very detailed description of the chemical process in which the accident occurred, together with an in-depth analysis of the technical failures that are seen as the major causes. The human or system failures that may have contributed to the accident are usually treated in a cursory manner. Technically oriented reporting systems are very common in the CPI, where engineers who may be unfamiliar with human factors princi- 

The systems which are the major focus of this chapter are described below. They emphasize the identification of underlying causes and the use of this information to specify error and accident reduction strategies. 

The main function of an incident reporting system (IRS) is to identify recurring trends from large numbers of incidents with relatively minor outcomes, or from near misses. One of the important characteristics of an IRS is that the time and resources required to evaluate an incident and incorporate it into the database must be minimized. This means that the designers of an IRS have to carefully evaluate the benefits and costs of requiring more comprehensive information from each incident that is to be reported. A requirement for too much information will bring the system into disrepute, and too little information will mean that the results are too general to be of any real value. 

Other important considerations in the design of an IRS are the data storage and analysis requirements. These need to be considered early in the design of the system if it is to be used to research and display trends effectively. For example, in addition to the answers to specific questions, the accident data analyst may wish to make use of free text descriptions of the circumstances of the accident. This implies that a text-based retrieval system will be required. 

The value of near miss reporting has been emphasized at a number of points in this book. Near misses represent an inexpensive way to learn lessons from 

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The discussion of alternative types of data collection systems serves to emphasize the fact that the design of such systems needs to have very clear objectives. Although a range of data collection systems have been described as if they... 

Although it is possible to identify and test every scenario of consistency checks, a business decision has to be made as to the depth of the checks. However, it is essential that all serious scenarios that could affect data analysis be tested. This is true for any type of data collection system. However, for a system to be one hundred percent reliable, every scenario must be tested and dealt with appropriately. A scenario that cannot be predicted at the time of development may be incorporated into the system or handled as an exception and dealt with accordingly when it occurs. 

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 model of human error held by management and the plant culture constitutes the environment in which the data collection system operates. Within this environment, all data collection systems need to address the topics listed in Figure 6.1. These topics, from the types of data collected, to the feedback systems that need to be in place, will be addressed in subsequent sections of this chapter. 

Specify Data Collection Methods and Responsibilities Several types of data collection have been specified in earlier sections. It is important that the responsibilities for operating the various aspects of the system are imambiguously defined. 

In a similar type of data collection, during 2000 to 2001 Wozniak (2002) examined the incidence of anabolic hormone residues in 5393 animals, consisting of cattle, pigs, horses, rabbits, chickens, geese, turkeys, ducks, and fish. Wozniak assayed for residues of diethylstibestrol, hexesterol, dienestrol, zeranol, trenbolone, and 19-noresterone. In addition, 632 cattle and swine were assayed for medroxyprogesterone and 1176 were assayed for natural 17-p-estradiol and testosterone. In only three heifers and two cows did serum testosterone exceed the MRL (EC 0.5 pg per liter) two bulls and four cows had an increased content of 17-(3-estradiol in their blood. A total of 11 animals of the 5393 examined (0.2%) had excessive quantities of hormone materials in their system. None of the other animals showed evidence of the presence of... 

Complete data indicates that all of the units under the test failed and the time-to-failure for each unit is known. Therefore, complete information is known regarding the entire sample. However, data collection is generally performed passively by the system owner and such type of data collection is often uncontrolled and important details are not always recorded or they can be lost. The actual times-to-failure are often not recorded even though the failure itself has been carefully noted. E.g. for a variety of reasons over 90% of the data in the Reliability Analysis Center (RAC)... 

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. 

The following types of information are collected in most CPI safety-related data collection systems ... 

The fact that the model connecting error types with their causes may change as a result of gaining further experience with the data collection system means that the informahon gathered on the PIFs in a situation may also change. For example, if incident data indicates the neglect of safety procedures because of production pressures, then the questions relating to this area wUl need to be extended. 

Pure paper-based data collection systems are most suitable for small and short-term studies. Their advantages are that no computer hardware or software is needed at the participating sites because data are recorded manually on paper forms that are transferred to the centralized location in batches. A major drawback is that participating sites do not have real-time access to their data because no database is created locally. However, both hardware and software are needed at the centralized location for the data management system. The type of hardware and software used is determined by the configuration of the centralized computer. The most commonly used platforms include Open VMS, Unix, or PC, and one of the most widely used software packages is SAS [16]. 

The use of electronic-based data collection and management systems allows the easy tracking of patient progress in the trial. Patient, visit, and form status are tracked. Patient status can be in screening, excluded, randomized, withdrew, or completed study. Similarly, status codes can be assigned to protocol scheduled visits to indicate whether the visit occurs or not. Form status depends on the type of the data collection system. For example a form in a distributed data collection system can be incomplete, filled, completed, altered, or transmitted. ... 

On a ternary equilibrium diagram like that of Figure 14.1, the limits of mutual solubilities are marked by the binodal curve and the compositions of phases in equilibrium by tielines. The region within the dome is two-phase and that outside is one-phase. The most common systems are those with one pair (Type I, Fig. 14.1) and two pairs (Type II. Fig. 14.4) of partially miscible substances. For instance, of the approximately 1000 sets of data collected and analyzed by Sorensen and Arlt (1979), 75% are Type I and 20% are Type II. The remaining small percentage of systems exhibit a considerable variety of behaviors, a few of which appear in Figure 14.4. As some of these examples show, the effect of temperature on phase behavior of liquids often is very pronounced. 

TABLE I Summary of Data Collected from the Literature, Including Type of System, Source of the DOC Used in the Bioassay, Range of Ambient DOC, Number of Individual Time Courses Extracted from That report, and the Reference... 

All of the types of data that can be collected, as listed above, can be stored in databases for summary and analysis. One such database, the Mouse Disease Information System (MoDIS), is freely available online (http //research.jax.org/... 

All major mass spectral data collections consist of El mass spectra, mostly recorded under accepted standardized conditions such as an ionization voltage of 70 eV, an emission current of 100-200 xA, and an ion source temperature of 150-200°C. Several types of GC/MS systems may be applied, for instance, magnetic sector, quadrupole, or ion trap analyzers. Ion trap systems are considered less applicable, when data comparison is required with spectra from a reference library. In particular, basic compounds related to VX or the three nitrogen mustards tend to produce protonated molecular ions by self-protonation. Magnetic sector and quadrupole mass spectrometers suffer less from interference of self-protonation, and spectra produced with these types of instruments are generally reproducible. 

Several types of data are routinely collected related to infectious disease surveillance, including morbidity, mortality, and health indicator data (CDC, 1992). Each state has requirements for mandatory reporting by health care providers and facilities, including laboratories, of cases of notifiable infectious diseases. There is a national notifiable disease list as well, for which reporting is voluntary, with data compiled through the National Notifiable Disease Surveillance System (CDC, 2004d, 2006). 

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