Conducting a clinical trial involves managing a great amount of data, from the very beginning to the very end. For this reason, finding a way of smoothening this process is an excellent way of ensuring the success of everyone’s efforts.
Moreover, in this globalized era, it is extremely common that different countries from all over the world work together, and that is why the implementation of standards regarding all aspects of a clinical trial is even more relevant.
This article will focus on how to enhance source data collection with the CDASH standard in order to simplify and streamline its conversion to SDTM format.
Bearing in mind how crucial it is to ensure data coherence and quality, it is fundamental to pay close attention to the beginning of the data collection process to avoid having future issues or difficulties in the following steps toward cleaned data that can be accepted by regulatory authorities.
As you well know, before starting a clinical trial, the sponsor needs to plan, organize, and set up all necessary elements which will guarantee the trial success.
Among those elements, we can find, among others, a research team that has enough expertise in the medical area under study, a professional CRA who will make sure that every instruction in the protocol is followed, and qualified personnel that will create, maintain, and assist in each of the data processing steps.
Regarding the latter, it is widely known how essential it is to have a well-structured and goal-oriented Case Report Form (CRF).
When working on the CRF design, it is imperative to have a deep understanding of the protocol to record essential contents required in it.
However, even though following standards developed internally or by the sponsor is allowed, it is highly advisable to maintain consistency among all clinical trials either at national or international level.
Therefore, thanks to the Clinical Data Interchange Standards Consortium (CDISC) initiative, a standard regarding best practices for CRF development has been established. This standard is known as Clinical Data Acquisition Standards Harmonization (CDASH). 
What is CDISC?
The Clinical Data Interchange Standards Consortium is a global nonprofit organization whose primary objective is developing data standards.
This consortium is composed of volunteers who have great expertise in the different fields linked to clinical trials as they belong to pharmaceutical or biotechnology companies, and CROs .
Having diverse perspectives on the clinical trial needs ensures the coverage of all potential issues, hence the resulting standards embrace best practices regarding the whole process.
Moreover, CDISC works closely with international agencies to develop codes and requirements which have a great impact on its standards. Among them we can find the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA).
As stated on the CDISC official web page, these standards have a clarifying nature of clinical research features. Therefore, they provide helpful guidance about data related aspects: collection methodology, communication, exchange, submission, and archive. This initiative aims at achieving the highest quality outcomes of clinical trials. 
Furthermore, implementing CDISC standards will entail a great deal of benefits. To begin with, it will not be necessary to worry about reformatting your data in order to make them compatible with diverse systems, which means a relief considering how globalized the clinical research sector is, and the number of different systems that exist.
Moreover, following these standards will make your data more accessible and reusable, because they will be processed according to the most common practices used in the clinical research industry.
In addition, the clinical trial will be easier to record, and it will provide a better understanding of the description of the disease to be treated with a medicine, and the population for which the medicine is intended.
Lastly and most importantly, adhering to these standards will simplify data collection, hence saving time and money, which is an excellent strategy to make your clinical trial more profitable and less time-consuming. 
What are the most commonly used CDISC standards?
As previously mentioned, CDISC has a deep understanding of clinical trials at every step, and for that reason, its standards are adapted to each one of the stages that data go through, namely the data collection, data organization and data analysis stages. CDASH, SDTM and ADaM standards respectively apply to each one of them.
Clinical Data Acquisition Standards Harmonization (CDASH) describes a standard way of collecting data to ensure their optimal submission into the Study Data Tabulation Model (SDTM), which is the next step of the process. Furthermore, regulatory bodies and people in charge of reviewing this data will take advantage of the transparency that applying these standards entails. 
As stated in the previous paragraph, SDTM is the second stage data move to. In this stage, data need to be organized and formatted to optimize its management, analysis, and reporting. Apart from that, SDTM helps compiling as well as storing the information, and smooths data sharing and regulatory review. 
The final stage of the whole data process in a clinical trial consists of analyzing the data. To do so, CDISC developed ADaM which stands for Analysis Data Model, in other words, a set of standards that describe how to build datasets and associated metadata. The implementation of ADaM, as stated on CDISC web page, “supports efficient generation, replication, and review of clinical trial statistical analyses, and traceability among analysis results, analysis data, and data represented in the Study Data Tabulation Model (SDTM)”. 
CDASH benefits to your clinical trial
As mentioned above, CDASH is the initiative of CDISC to achieve a common way of collecting data to ensure quality, consistency, and improvement of analyzed data.
In order to meet that goal, in 2006 this organization joined together clinical data managers, statisticians, medical monitors, and programmers to develop these standards that comprised all their perspectives and points of view. 
The result was a set of standards that cover all possible data collection needs and future data analysis issues as it ensures an excellent CRF design; the data collection tool that can be in electronic or paper format.
The CDASH approach could be summarized in a single word: optimization.
Let’s explain how that word applies to most CDASH recommendations:
- To begin with, these standards recommend collecting only key data, which reduces the CRF fields. An example of it is the Inclusion/Exclusion Criteria Domain which, according to the last version of CDASH Implementation Guide for Human Clinical Trials (2.2 Final), is recommended to record in the CRF only the unmet criterion and for that “the collection method has been simplified to require the site to record a single “Y/N” value in the IEYN variable” .
- Secondly, another best practice described in the CDASH Implementation Guide 2.2 is with regards to clarity. It is recommended that questions in a CRF are self-explanatory in order to avoid having to include a great deal of long instructions. Also, when the need of including an instruction is unavoidable, it is considered that short instructions and prompts on a CRF will increase the possibility of them being read and followed. This approach will reduce costs and the number of queries as well as help CRF users to identify missing responses due to pages reduction .
- The third one concerns the free-text responses. In the CDASH Implementation Guide 2.2, it is stated that this kind of responses should be minimized to prevent data from being recorded into wrong fields. To accomplish this, using a predefined list of responses reviewed closely by the protocol development team is strongly recommended .
- Finally, these recommendations also establish the format for collecting times. Considering SDTM-based datasets use ISO 8601 date/time formats, using a 24-hour clock format when entering data in the database is advisable .
These recommendations are just a small number of examples of what CDASH can offer. Furthermore, since these standards are a subset of SDTM —the format which facilitates creating the necessary documents for the regulatory submissions— the whole data process smoothens because their collection is designed in a way to simplify its conversion to the format that many regulatory authorities require (including the FDA of the United States).
Implementing CDASH in your CRF will reduce time, money, queries, and efforts involved in the creation, maintenance, and use of this data capture tool. 
To sum up, having your CRF created by following the CDASH standard allows you to develop a perfectly structured data collection tool, directly linked to SDTM features. Furthermore, bearing in mind how complex and time consuming it is to manage and ensure high quality data in a clinical trial, optimizing the entire process is the best way to increase efficiency and reduce stress.
 Clinical Data Acquisition Standards Harmonization Implementation Guide for Human Clinical Trials Version 2.2 (Final)