Data collection forms design

The explosion of graphical software and the ability of database management systems to store graphical data provide a mechanism for designing and implementing clip art to convey certain meaning to the user. For example traffic lights have been used to convey the status of data collection forms. 

Valid analysis cannot be conducted unless one can distinguish animals which were examined and did not have the relevant response and animals which were not examined. It can also be important clearly to identify why data are missing. Table 22.4 identifies some basic rules for effective design of data collection forms. 

For computer workstations, the workstation configuration must be verified using the technical design specification. The result of the verification must be documented using the data collection forms located in the approved protocol. 

Design your CRFs accordingly. Do not start by simply deciding to use the data collection forms that were used in previous studies. If there are some questions on previous forms that address the collection of data you need, can those questions be improved ... 

The CRF design process can begin either following or concurrent with the protocol development. Well-designed data collection forms are critical to achieve the objectives of the clinical trial. Consideration should be given to the content, format, and layout of the forms since all these factors contribute to the overall quality and accuracy of the data that will be collected, processed, and reported. 

The administrative cost of voucher schemes is one of their main drawbacks. However, they can be administered more easily than other demand-side subsidies. Requiring the provider to present a voucher in order to receive the subsidy can prevent irregularities and false claims. If designed well, the voucher can serve as a receipt and a data collection form, as well as a token of exchange. 

Any document used to collect research data on clinical study subjects may be genetically classed as a data collection form. These completed forms provide evidence of the research conducted. The most common type of data collection form is the CRF. Other types of data collection forms include diary cards, dispensing records, quality of life forms, etc. The CRF must allow for proper analysis of the data and proper reporting of the data in the final clinical study report and it must reflect the protocol exactly no more and no less data must be collected. Thus, a CRF must be created for each clinical study and must be prepared in parallel with the protocol. CRFs are usually also prepared by spon-sors/CROs in pharmaceutical industry research because of the demanding requirements for their design and contents. 

Data collection forms were designed and covered the data subject areas 1-5 above, trial completion of the forms was undertaken and revisions made on the basis of the trial results. 

The raw data collected during the experiment are then analyzed. Frequently the data must be reduced or transformed to a more readily analyzable form. A statistical treatment of the data is used to evaluate the accuracy and precision of the analysis and to validate the procedure. These results are compared with the criteria established during the design of the experiment, and then the design is reconsidered, additional experimental trials are run, or a solution to the problem is proposed. When a solution is proposed, the results are subject to an external evaluation that may result in a new problem and the beginning of a new analytical cycle. 

Another reactor that was approved for development was a land-based prototype submarine propulsion reactor. Westinghouse Electric Corp. designed this pressurized water reactor, using data collected by Argonne. Built at NRTS, the reactor used enriched uranium, the metal fuel in the form of plates. A similar reactor was installed in the submarine l autilus. 

Quality assurance programs are designed to serve two functions (1) assessment of collected air quality data and (2) improvement of the data collection process. These two functions form a loop as air quality data are collected, procedures are implemented to determine whether the data are of acceptable precision and accuracy. If they are not, increased quality control procedures are implemented to improve the data collection process. 

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 information gathered from the interviews conducted as part of the human error data collection process is entered on paper forms. In order to facilitate the ease and accuracy of data collection, the forms should be designed using human factors guidelines for written materials (e.g., Wright, 1987 Wright and Barnard, 1975). 

Additional examples of variability in data collection (which, in turn, affects data interpretation) include questionnaires and physical exam forms. Questionnaires often utilize open-ended questions that allow great variability in the type and extent of adverse event information gathered. Physical exam forms—even when designed in a checklist format—may elicit variable collection of adverse event data what is a serious event to one clinician may not be serious to another. 

In order to design the best form for their needs, users must first define what data they wish to collect and which factors are of the greatest importance. In addition, all the usual factors in form design need to be considered (e.g., size, layout, color, print type, spacing, flow of questions, boxes, language, and instructions). A pilot to test the form should be carried out before formal introduction and use. 

The following discussion will focus on how to apply the previously discussed concepts to the validation of marketed products. To provide a fuller understanding of this procedure, the manufacture of several dosage forms designed for different routes of administration will be examined. For each dosage form, critical process steps and quality control tests will be identified. Useful statistical techniques for examining the assembled data will be illustrated. It is also important to note that not all of the collected information for a product lends itself to this type of analysis. This will become more apparent as we proceed with the evaluation of the five drugs under consideration. 

Case report forms (CRFs) are used throughout clinical trials to record data collected during a trial. They record all of the information specified in the protocol for each subject (all data recorded on the CRF must be verifiable from original source documentation). While the traditional paper CRF format is still used, electronic data collection is becoming more common. Voorhees and Scheipeter (2005) discussed CRF development in detail, highlighting some of the fundamental aspects of their purpose, design, and nature ... 

There are two forms of the f-test, and each is applicable for sets of measurements that have been obtained in different ways. The method of data collection precisely and uniquely determines which of these two forms of statistical analysis is appropriate. Section 7.6 introduced the independent groups Mest, which is appropriate for the analysis of data collected during a study employing a parallel group study design. Another form of the Mest is called the dependent measures t-test. This test is sometimes called the related measures Mest, the repeated measures Mest, or the Mest for matched pairs. The name dependent measures Mest has been chosen here since the contrast with the word independent in the name independent groups Mest is clear. 

There are two competing and equivalent nomenclature systems encountered in the chemical literature. The description of data in terms of ways is derived from the statistical literature. Here a way is constituted by each independent, nontrivial factor that is manipulated with the data collection system. To continue with the example of excitation-emission matrix fluorescence spectra, the three-way data is constructed by manipulating the excitation-way, emission-way, and the sample-way for multiple samples. Implicit in this definition is a fully blocked experimental design where the collected data forms a cube with no missing values. Equivalently, hyphenated data is often referred to in terms of orders as derived from the mathematical literature. In tensor notation, a scalar is a zeroth-order tensor, a vector is first order, a matrix is second order, a cube is third order, etc. Hence, the collection of excitation-emission data discussed previously would form a third-order tensor. However, it should be mentioned that the way-based and order-based nomenclature are not directly interchangeable. By convention, order notation is based on the structure of the data collected from each sample. Analysis of collected excitation-emission fluorescence, forming a second-order tensor of data per sample, is referred to as second-order analysis, as compared with the three-way analysis just described. In this chapter, the way-based notation will be arbitrarily adopted to be consistent with previous work. 

We should point out that the ability to fit equations of the form (5-18) or like (5-19), or of an even more complicated form, is predicated on having data from enough different mixtures to allow unambiguous identification of the parameters b. This requires proper data collection strategy. Much of the existing statistical research on the topic of mixture experiment design has to do with the question of wise allocation of experimental resources under the assumption that a particular type of equation is to be fit. 

Every effort should be made to have the protocol produce quantifiable data concerning each of the hypotheses to be tested. The statistician should design or review the nature of this quantification to make sure that the raw data collected in the clinical sites to be submitted will be in a useable form. 

In the field of public health, the term surveillance refers to the ongoing, systematic collection, analysis, interpretation, and dissemination of health data (CDC, 2001b, p. 2). The data collected and analyzed through surveillance systems provide information about patterns of disease occurrence in a population. In turn, this information forms the basis of action by public health officials in designing, implementing, and evaluating interventions to control or prevent disease (CDC, 1992). The activities carried out in a surveillance system are described briefly in the following. 

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