¶ … Standards Technology Impact on Clinical Research and the Interrelationship of Uniform Data Format Standards

With increasing robustness of technology, clinical programmers began realizing inefficiencies in metadata and recreation from scratch each time, in addition to overlapping data elements over research works. Further, they saw the numerous inconsistent techniques for collection of specific, seemingly-simple data elements. The most straightforward example conveying the above challenge is: defining subject gender (Female or Male) in a clinical research work. At a swift glance, this appears to be a rather clearly defined data point. But, as is proven, even seemingly simple elements can prove challenging (McBride, 2014). An evolution is occurring in data management. By embracing emergent technologies once again, data managers are likely to be a lot more efficient than before. Under this article, only some aspects of innovation impact clinical managers of data are covered; however, it is evident that, over time, several more technologies will emerge and prove their impact (Etheredge, 2007).

Regulatory Controls and Legal and Ethical Frameworks

Clinical Data Management (CDM) has standards and guidelines, which have to be observed. As the pharmaceutical sector depends on electronic data for drug evaluation, they are required to observe good CDM practices and maintain electronic information capture standards. These electronic registers require 21 CFR- Part 11- compliance (CFR denotes Code of Federal Regulations). This regulation applies to electronic records, which are created, maintained, altered, transmitted, archived, or retrieved (Raptis, Mettler, Fischer, Patak, Lesurtel, Eshmuminov, De Rougemont, ... & Breitenstein, 2014), and calls for validated system application, for ensuring data accuracy, consistency and reliability, with use of time-stamped, secure, and computer-generated audit...

SCDM (i.e., Society for CDM) publishes guidelines for good CDM practices (GCDMP), a record offering good practice standards for CDM. The guidelines were published initially in September of 2000, and have thereafter gone through numerous revisions. The latest version, followed at present, is that issued in July of 2009. GCDMP offers guidance on acceptable CDM practices in keeping with regulatory procedures. CDISC (Clinical Data Interchange Standards Consortium), a not-for-profit, multidisciplinary firm, has devised standards for supporting clinical metadata and research data acquisition, submission, exchange, and archival (Krishnankutty, Bellary, Kumar & Moodahadu, 2012).
System Parties Involved

Different responsibilities and roles are assigned to members of CDM teams. The minimum required educational qualification for CDM team members is a graduate degree in life sciences and computer applications knowledge. Preferably, medical coders must be graduates in the field of medicine. But graduates in the paramedical field are hired for the role of medical coders, as well. There are a few key roles vital to every CDM team; these are: A Data Manager, Medical Coder, Data Entry Associate, Quality Control Associate, Database Designer/Programmer, and Clinical Data Coordinator (Krishnankutty et al., 2012).

How Has the Growth of Technology and Data Standards Affected the Management of Clinical Data?

Forgoing repetitive error-prone tasks: The execution of identical tasks, repetitively, makes the process prone to mistakes, as well as being time-consuming and costly. Unfortunately, numerous everyday data managerial tasks necessitate manual creation and repeated checking of the same charts and reports. For instance, this may involve manual MS-Excel-based reviewing or filtering…