Quality systems data integrity

Data used by a safety-related system should be classified based upon the uses made of the data and the way in which the data influences the behaviour of the system. The nature and influences of data faults will also vaiy with the form and use of the data within a system. Data integrity requirements are essential if the suitability of data models is to be assessed. This paper has presented a process by which these data integrity requirements may be established. Additional design analysis may identify that the structure and composition of the data set or that data from the real world cannot be obtained in either the quantity, nor of the requisite quality. These data integrity requirements may also be used to identify verification and validation requirements for the system. 

The decommissioning procedure must address both operational and safety aspects of the computer system application and establish integrity and accuracy of system data until use of the system and/or process is terminated. For quality-related critical instrumentation, proof of calibration prior to disconnection is needed. 

So, what level of data integrity is acceptable The total percentage of errors we found in our study was 5%. Is this satisfactory Is this the best we can hope for Hopefully not, especially as more people become dependent on databases and the rate of production of data becomes ever faster. Clearly, there is a need for a system that will better validate data being entered in the most used CAS databases. It is desirable that the quality of the databases increases at the same time as they are mushrooming in size. 

In order for emerging methods to be acceptable for use in a regulatory context work is needed to validate them, and to develop QA/QC procedures for their use. There is also a need for dissemination of information on their performance and potential uses within the WFD. This is especially important since the type of information obtained with some tools is different from that provided by current practice. In some cases it may be appropriate to use a battery of tools in water quality management. In this case there is a need for a system to integrate the available information to provide a comprehendible set of data that can provide support for those responsible for risk analysis, and decision making in this area. 

As a result, electronic document and records management systems (ERMS) are becoming more and more essential in this environment in order to handle the volume of data and related documents as well as to verify the quality and the integrity of the data for FDA auditors. ERMS have become critical for research and development in the biotech and pharmaceutical industry to the extent that the FDA created... 

These requirements may not seem to be helpful suggestions, but they provide the basic understanding that data quality, reliability and integrity have to be ensured in ways that are not intrinsically different, whether they are acquired and handled by computerised systems or not. 

Another extremely important aspect of an effective quality system is documentation. Accurate and full documentation of all activities is required to ensure the integrity of data generated in the laboratory. Standard operating procedures and working instructions should be prepared and used for the laboratory processes, and all such documents should be controlled. Any notes made, calculations, or changes to procedures should be recorded and, if necessary, explained. It is useful to adopt the phrase If you did not write it... 

One could of course argue that assurance of the integrity of data is also a requirement under any other quality system such as GMP. This assurance requires that analysts are trained, that procedures are written and approved, that analytical equipment is calibrated and maintained, that reagents and test materials are controlled and that accurate records and original raw data are kept. 

Higher product and documentation quality is achievable with the use of integrated systems. Through integration, all functions of a product model are made aveiilable to the user. Any errors that may occur during data transmission between separate systems are avoided. 

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