Collection of multi-institutional data pertaining to the treatment of bowel cancer has been hindered by poor clinician compliance with data entry and the lack of incentive to participate.
Dr McMurrick and colleagues established if a novel browser-based model of data collection results in complete data capture.
A Web-based data collection interface was custom written, offering automated reporting modules for clinical outcome to participants and an automated reporting system for outstanding data fields, and summary reporting of surgical quality outcomes.
The software was combined with a clinical feedback system incorporating fortnightly data review meetings, at the time of clinical multidisciplinary meetings.
|100% completion of perioperative data registered was obtained|
|Diseases of the Colon & Rectum|
The research team selected 932 consecutive patients with opt-out consent from 3 hospital sites, including public and private medicine.
The team's main outcomes were the analysis of data completeness and accuracy and ensuring that the highest-quality data were used for clinical audit of the surgical practices of Australian colorectal surgeons for the purpose of quality assurance.
A total of 932 men and women, 22 to 94 years of age, treated for colorectal neoplasia were evaluated.
The researchers obtained 100% completion of perioperative data registered by 8 specialist colorectal surgeons, and a full-time database manager.
Dr McMurrick's team concludes, "Data completeness and validity are essential for clinical databases to serve the purpose of quality assurance, benchmarking, and research."
"The results confirm the safety and efficacy of colorectal cancer surgery in both the public and private sector in Australia."
"The combination of a simple multiuser interface, defined data points, automated result-reporting modules, and data-deficiency reminder module resulted in 100% data compliance in nearly 1000 clinical episodes."
"The unprecedented success of this model has lead to the Colorectal Surgical Society of Australia and New Zealand adopting this model for data collection for Australia and New Zealand as the binational database."