Extension of the primary care research object model (PCROM) as clinical research information model (CRIM) for the "learning healthcare system".

Wolfgang Kuchinke,Adel Taweel,Töresin Karakoyun,Stuart M Speedie,Theodoros N Arvanitis,Brendan C Delaney,Christian Ohmann

doi:10.1186/s12911-014-0118-2

Abstract

BackgroundPatient data from general practices is already used for many types of epidemiological research and increasingly, primary care systems to facilitate randomized clinical trials. The EU funded project TRANSFoRm aims to create a “Learning Healthcare System” at a European level that is able to support all types of research using primary care data, to recruit patients and follow patients in clinical studies and to improve diagnosis and therapy. The implementation of such a Learning Healthcare System needs an information model for clinical research (CRIM), as an informational backbone to integrate aspects of primary care with clinical trials and database searches.MethodsWorkflow descriptions and corresponding data objects of two clinical use cases (Gastro-Oesophageal Reflux Disease and Type 2 Diabetes) were described in UML activity diagrams. The components of activity diagrams were mapped to information objects of PCROM (Primary Care Research Object Model) and BRIDG (Biomedical Research Integrated Domain Group) and evaluated. The class diagram of PCROM was adapted to comply with workflow descriptions.ResultsThe suitability of PCROM, a primary care information model already used for clinical trials, to act as an information model for TRANSFoRm was evaluated and resulted in its extension with 14 new information object types, two extensions of existing objects and the introduction of two new high-ranking concepts (CARE area and ENTRY area). No PCROM component was redundant. Our result illustrates that in primary care based research an important but underestimated portion of research activity takes place in the area of care (e.g. patient consultation, screening, recruitment and response to adverse events). The newly introduced CARE area for care-related research activities accounts for this shift and includes Episode of Care and Encounter as two new basic elements. In the ENTRY area different aspects of data collection were combined, including data semantics for observations, assessment activities, intervention activities and patient reporting to enable case report form (CRF) based data collection combined with decision support.ConclusionsResearch with primary care data needs an extended information model that covers research activities at the care site which are characteristic for primary care based research and the requirements of the complicated data collection processes.

Highlights

Patient data from general practices is already used for many types of epidemiological research and increasingly, primary care systems to facilitate randomized clinical trials
The comparison between PCROM and Biomedical research integrated domain group (BRIDG) showed that PCROM is an easier representation of RCT than BRIDG and can easier support the interoperability needs arising from the development of electronic clinical trials systems
Coverage of randomized clinical trials, patient recruitment and cohort studies The general approach for the comparison of the different information models is to use activity diagrams to display the workflow of two very different clinical research use cases (GORD and T2D) that cover a large area of possible clinical research activities

Summary

Introduction

Patient data from general practices is already used for many types of epidemiological research and increasingly, primary care systems to facilitate randomized clinical trials. At a European level that is able to support all types of research using primary care data, to recruit patients and follow patients in clinical studies and to improve diagnosis and therapy The implementation of such a Learning Healthcare System needs an information model for clinical research (CRIM), as an informational backbone to integrate aspects of primary care with clinical trials and database searches. The EHR can play a central role in a system that learns from data collected at the point of care and applies the lessons learned to the improvement of patient care, ensuring the integrity and the quality of the research outcomes, and resulting in better diagnosis and treatment innovations With such rich data, research becomes an important participant in the iterative innovation process known as the ? Important for the implementation of the clinical use cases are several tools, the functional eCRF (an interface for integrating clinical and research data capture into the EHR), mobile eHealth (a web questionnaire for patient reported outcome, ePRO), a Data Quality Tool (to assess the quality of primary care data for research purposes, in terms of completeness, comprehensiveness and validity), and the Query and Data Extraction Workbench (consisting of query authoring for the identification of research subjects based on existing EHR data and a workbench for managing data extraction and linkage for epidemiological studies)

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Discussion

Conclusion