The Clinical Perspective - Biomedical Informatics in Translational Research - page 21

resolving discrepancies in clinical data collected. The tool is called the Quality
Assurance Issue Tracking System (QAIT) [13]. There are thousands of enrollees in
the CBCP so far, and the project collects many hundreds of data elements from each
enrollee. Without precise methods for correcting errors, the project would lose vital
data strength and compromise its ability to conduct excellent research. The QAIT
provides secure online communication between the data entry technicians and the
quality specialists who review all the questionnaires for completeness and accuracy
before data are entered. The process is straightforward. When an issue requires clar-
ification or correction based on standard operating procedures, it is entered into the
QAIT by a data entry technician. A quality reviewer then opens that issue in the
QAIT, via secure online access, and assesses what needs to be done to resolve the
issue. This may require verifying information in a medical record or verifying infor-
mation through the research nurse who initially collected it. When the quality
reviewer successfully resolves the issue, the resolution is entered into the QAIT.
That issue is then closed by a data entry technician. The steps, dates, and times
along the way are recorded electronically by the QAIT. At any given moment, the
current stage of the issue's progress is easily identified by the users. When the issue is
resolved, the data entry technician enters the correct value into the clinical data
tracking system CLWS, which is described in more detail in Chapter 7.
These processes are the standard operating procedures for quality checks and
balances using the QAIT, before ultimate data entry into the CLWS. Once data are
entered, further quality checks are applied in the form of a computer program called
QA Metrics, which implements hundreds of established quality assurance (QA)
rules to flag discordant data, given their relationship to each other. In addition to
data problem resolution, the QAIT provides reports that enable management to
better supervise, train, and track proficiency of staff involved in the data collection
and quality assurance processes. Figure 2.1 depicts a list of issues that require clari-
fication and/or correction by users of the QAIT.
2.6.4 Data Transfer from the Health Care Clinic to the Research Setting
The biomedical information collected within the clinical setting must become avail-
able to the research specialists and scientists who will use and analyze the informa-
tion. This may involve manual and/or electronic transfer of information. It may be a
matter of entry into the data tracking systems and repositories that are on site or a
matter of shipping to sites where the data and specimen management systems are
located. Regardless, quality control practices that ensure the integrity of clinical
data and biological specimens during transfer are of paramount importance.
Quality control methods for transferring biological specimens to the repository
are covered in Chapter 3. As previously discussed, all clinical data should undergo
quality review before being cleared for data entry. The data entry processes them-
selves should also have a quality oversight component. If the data tracking system is
one whereby data entry occurs directly, such as a survey administered electronically
on the Internet, with no opportunity for quality review before data entry, it is neces-
sary for quality control procedures to begin at the point after which the data is
entered, but before it is analyzed by the researchers.