Strategies for Medical Data Extraction and Presentation Part 3: Automated Context- and User-Specific Data Extraction

Abstract

In current medical practice, data extraction is limited by a number of factors including lack of information system integration, manual workflow, excessive workloads, and lack of standardized databases. The combined limitations result in clinically important data often being overlooked, which can adversely affect clinical outcomes through the introduction of medical error, diminished diagnostic confidence, excessive utilization of medical services, and delays in diagnosis and treatment planning. Current technology development is largely inflexible and static in nature, which adversely affects functionality and usage among the diverse and heterogeneous population of end users. In order to address existing limitations in medical data extraction, alternative technology development strategies need to be considered which incorporate the creation of end user profile groups (to account for occupational differences among end users), customization options (accounting for individual end user needs and preferences), and context specificity of data (taking into account both the task being performed and data subject matter). Creation of the proposed context- and user-specific data extraction and presentation templates offers a number of theoretical benefits including automation and improved workflow, completeness in data search, ability to track and verify data sources, creation of computerized decision support and learning tools, and establishment of data-driven best practice guidelines.