The clinical trials industry has changed significantly in the past decades with more and more complex studies taking place at present. Today multicentre, multinational clinical trials with complex treatment protocols are common and it requires a large team of clinical staffs and huge data sets which complicate the clinical process. The clinical trials industry relies a great deal on data entry services for data collecting, tracking, scanning, data entry, data curation and so on.
With millions of dollars invested in the research and development of new treatments and drugs, there is immense pressure on clinical investigators to produce quality clinical trial data once the study is complete. The US Food and Drug Administration (FDA) requires researchers to produce more convincing and strong clinical trial data, and this has made data accuracy a very important element. Error-free data is essential for gaining accurate conclusions regarding the treatment’s safety and efficacy. Organizations and clinical research sponsors typically ensure accuracy of data with data cleansing services provided by data entry companies.
Many clinical studies involve multicentre clinical trials and with years the number of studies increases, the number of data entry professionals working on them increases, and consequently risk of human error in data entry also increases. These errors are risky in that companies sponsoring the research could end up losing a lot of money. Let us consider some of the most common sources of human error in the clinical trial scenario and how these can be addressed.
Inaccurate and Inconsistent Data Entry
Some clinical trials choose centralized data entry into the clinical trial management software in order to reduce cost and improve productivity. However, with this method it is difficult to resolve data related issues. Outsourcing data processing mitigates the risk of error since the data entry would be done by professionals in the field and you can choose to have on-site or offsite data entry.
On-site process would shorten the time between data collection and data entry. Moreover, errors such as omissions and confusing entries can be immediately corrected. A double entry process can help reduce data errors-where two data entry professionals enter the same data and a verification program is used to identify the difference between the files. If any changes are found, they are corrected so that the files match completely.
Omission of Authorization and Signature
Missing signature in the master file of the clinical trial can cause huge complications even in a well-organized clinical trial. The omission of authorization may be due to lack of training of new staffs, a missing signature, or a simple oversight on the part of the clinical trials professionals and these mistakes can damage data integrity. In a clinical trial, all data must be organized and made complete in anticipation of FDA inspection. Electronic data capture is helpful in this regard in that it will ensure that all important data is entered correctly and electronically signed. Many clinical data management programs can identify erratic data entry, and prompt data entry staff to review and correct them.
Tips for Optimal Clinical Trial Data Collection
Collecting huge volume of data can be tedious, and this can increase the risk of human errors when data entry staff has to deal with a larger volume of data. So, those sponsoring clinical trials can consider the following tips to reduce the chances of errors.
- Capture only the data that are relevant for the study protocol and do not deviate from the study protocol unless it is necessary.
- The data collection method should be standardized and all study coordinators should collect data using the same technique, forms and format.
- Organized data capture makes data entry and analysis easy. It is also easy to ensure error-free data, data entry, data analysis and data manipulation.
- Provide sufficient time for data entry and review.
- Avoid unnecessary data collection. These additional data can complicate clinical trials and prolong the study period.
The most important consideration in clinical trial research is to eliminate human error in the data whether you use a traditional paper data collection or electronic data capture. Staffs should be given a good training program to ensure that they are aware of the importance of accuracy and careful data entry. So spending time in training the staffs and skill assessment before a clinical trial can reduce the rate of human error. Quality of data is a very important element in clinical trials and organizations that don’t want to invest in data entry staff and their training can always consider outsourcing data entry to a reliable data entry company.