Abstract
From mitigating complications during hospital stay to reducing the incidence of chronic pain, improving pain management positively impacts short- and long-term outcomes of treatment. Quality assurance has become the focus of many health care programs in an effort to confront the challenges presented by pain and its management. The analysis of treatment strategies and patient responses form the basis of a reflective, evidence-based practice, which can raise awareness of about the importance of adequate pain management. The capabilities of an electronic database can be exploited to organize large amounts of data, which can then be used to characterize symptoms and analyze treatment responses. However, the types of data to collect, the burden of data collection on workers, and costs must be considered before implementing an electronic database for research and/or everyday practice. This study tested the relevance and usability of an electronic database in an acute pain service by assessing several variables important to database development and evaluation.BACKGROUND: Quality assurance is increasingly important in the current health care climate. An electronic database can be used for tracking patient information and as a research tool to provide quality assurance for patient care.OBJECTIVE: An electronic database was developed for the Acute Pain Service, University of Alberta Hospital (Edmonton, Alberta) to record patient characteristics, identify at-risk populations, compare treatment efficacies and guide practice decisions.METHOD: Steps in the database development involved identifying the goals for use, relevant variables to include, and a plan for data collection, entry and analysis. Protocols were also created for data cleaning quality control. The database was evaluated with a pilot test using existing data to assess data collection burden, accuracy and functionality of the database.RESULTS: A literature review resulted in an evidence-based list of demographic, clinical and pain management outcome variables to include. Time to assess patients and collect the data was 20 min to 30 min per patient. Limitations were primarily software related, although initial data collection completion was only 65% and accuracy of data entry was 96%.CONCLUSIONS: The electronic database was found to be relevant and functional for the identified goals of data storage and research.