An eClinical trial system for cancer that integrates with clinical pathways and electronic medical records.

Abstract

[Background] Various information technologies currently are used to improve the efficiency of clinical trials. However, electronic medical records (EMRs) are not yet linked to the electronic data capture (EDC) system. Therefore, the data must be extracted from medical records and transcribed to the EDC system. Clinical pathways are planned process patterns that are used in routine clinical practice and are easily applicable to the medical care and evaluation defined in a trial protocol. However, few clinical pathways are intended to increase the efficiency of clinical trials. [Purpose] Our purpose is to describe the design and development of a new clinical trial process model that enables the primary use of EMRs in clinical trials by integrating clinical pathways and EMRs. [Methods] We designed a new clinical trial model that uses EMR data directly in clinical trials and developed a system to follow this model. We applied the system to an investigator-initiated clinical trial and examined whether all data were extracted correctly. At the protocol development stage, our model measures endpoints based on clinical pathways with the same diagnosis. Next, medical record descriptions and the format of the statistical data are defined. According to these observations, screens for entry of data, which are used both in clinical practice and for study, are prepared into EMRs with an EMR template, and screens are prepared for data checks on our EMR retrieval system (ERS). In an actual trial, patients are registered and randomly assigned to a protocol treatment. The protocol treatment is executed according to clinical pathways, and the data are recorded to EMRs using EMR templates. The data are checked by a local data manager using reports created by the ERS. After edit checks and corrections, the data are extracted by the ERS, archived in portable document format (PDF) with an electronic signature, and transferred in comma-separated values (CSV) format to a coordinating centre. At the coordinating centre, the data are checked, integrated, and made available for a statistical analysis. [Results] We verified that the data could be extracted correctly and found no unexpected problems. [Limitation] To execute clinical trials in our system, the EMR template and efficient ERSs are required. Additionally, to execute multi-institutional clinical trials, it is necessary to create templates appropriate for EMRs at all participating sites and for the coordinating centre to validate local templates and procedures. [Conclusion] We proposed and pilot tested a new eClinical trial model. Because our model is integrated with routine documentation of clinical practice and clinical trials, redundant data entries were avoided and the burden on the investigator was minimised. The reengineering of the clinical trial process would facilitate the establishment of evidence in the future.