A CDISC+HL7-based oncology clinical research EHR system

DESCRIPTION (provided by applicant): The integrated coordination of clinical care and research processes for patients who volunteer to participate in clinical trial protocols is increasingly important, but a major obstacle has been the absence of a standard model for an Electronic Health Record (EHR) that satisfies functional needs as well as federal regulatory requirements. The complexity of clinical care alone has hindered the creation and widespread adoption of standard Electronic Patient Record (EPR) or Electronic Medical Record (EMR) systems. Coupled with complex biomedical research needs and evolving scientific knowledge, the problem is a difficult one, at both conceptualization and implementation levels. However, recent progress in health informatics models and in software engineering methods makes tackling this problem more feasible. For clinical services, Health Level 7 (HL7) has developed high-level specifications, in particular the Reference Information Model (RIM). For clinical research, the Clinical Data Interchange Standards Consortium (CDISC) has developed specifications such as the Operational Data Model (ODM) and Study Data Tabulation Model (SDTM). For implementation, Medical Decision Logic, Inc. (MDLogix(tm)) has developed a Model Driven Architecture-based development platform ("MDLogixMDA"), enabling the use of these health informatics models to more efficiently create and continuously evolve software products. This proposal plans use of the MDLogixMDA platform to create an EHR system ("HealthDataWorks") that will support clinical and research processes for oncology centers. A core innovation is the combined implementation of the HL7 RIM and the CDISC ODM and SDTM within the MDLogixMDA platform. Building on this platform, the Phase I product focus will be on creating a set of software application modules that supports the process of matching patients to multiple oncology clinical trial protocols and optimal assignment. Improving the efficiency of oncology clinical trials will speed up the development of new knowledge and application of that knowledge to the treatment of cancer. The product focus of this project is to create a set of software application modules that supports the process of matching patients to multiple oncology clinical trial protocols and optimal assignment. The model driven software engineering approach will enable rapid deployment and wider market opportunities by making it easier to create modular extensions for applications such as practice-based clinical trials, integrated diagnostic rules, dissemination and use of clinical guidelines, and scheduling and billing functions. The option for virtual centralization can support public health applications for population monitoring, policy development, and intervention programs. Use of public standards and focus on supporting interoperability with existing system will facilitate adoption of the software.