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Clinical Trials Powered By Electronic Health Records
Clinical Trials Powered By Electronic Health Records
Clinical Trials Powered By Electronic Health Records
Clinical Trials Powered By Electronic Health Records
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Clinical Trials Powered By Electronic Health Records

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The development of Electronic Health Record (EHR) systems containing valuable clinical information is an opportunity not only for health care but also for clinical research. Clinical Trial (CT) …

The development of Electronic Health Record (EHR) systems containing valuable clinical information is an opportunity not only for health care but also for clinical research. Clinical Trial (CT) management systems would improve their processes by accessing this EHR data in a straightforward way.
Nevertheless, there are still many problems to be solved in order to facilitate the reuse of information, including the lack of common formats for the representation of data, or a limited definition of the meaning of that data. The use of standards and clinical terminologies, together with a clear definition of clinical information models becomes essential in order to enable the semantic interoperability of EHR and clinical trials by means of a standardized definition of the data to be exchanged.

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  • 1. CDISC EU Interchange 2012Clinical Trials powered by Electronic Health RecordsDavid Moner, Juan Bru, José Alberto Maldonado, Montserrat RoblesInstituto ITACA, Universitat Politècnica de València, Spain (Contact: damoca@upv.es)IntroductionThe development of Electronic Health Record (EHR) systems containing valuable clinicalinformation is an opportunity not only for health care but also for clinical research. Clinical Trial(CT) management systems would improve their processes by accessing this EHR data in astraightforward way.Nevertheless, there are still many problems to be solved in order to facilitate the reuse ofinformation, including the lack of common formats for the representation of data, or a limiteddefinition of the meaning of that data. The use of standards and clinical terminologies, togetherwith a clear definition of clinical information models becomes essential in order to enable thesemantic interoperability of EHR and clinical trials by means of a standardized definition of thedata to be exchanged.Material / MethodsThe CEN/ISO 13606 standard for the communication of electronic health records [1] proposesan innovative approach for the representation of clinical information. It is based in the use of aReference Model for representing data instances and an Archetype Model for representingclinical concepts. Archetypes are formal definitions of clinical models which provide a powerful,reusable and interoperable mechanism for managing the creation, description, validation andquery of EHRs. Examples of archetypes include prescriptions, health problems, differentialdiagnosis, pregnancy reports or blood pressure observations. Archetypes are also the linkbetween information structures and terminologies or ontologies that semantically describe thatinformation. Page | 1
  • 2. CDISC EU Interchange 2012In the field of clinical trials, CDISC Operational Data Model (ODM) is a generic referencemodel for the representation of any information included in a clinical research study. ODM,together with CDISC CDASH, provides the basic components and structures of informationneeded and used in clinical trials.From data to knowledgeInformation structures contained in EHR systems are mainly focused to health care and could berepresented by archetypes. But it is not common to find archetype-based systems, but to haveonly data which is not standardized.A first use of archetypes is the normalization of legacy data. LinkEHR [2] is a tool that helps inthis duty by providing two basic functionalities. On the one hand, we can define archetypesbased on any reference model, for example CEN/ISO 13606, HL7 CDA or CDISC ODM. On theother hand, LinkEHR allows defining mappings between archetypes and existing data sourcesand it generates transformation programs to convert legacy data into standardized data,conformant to the selected standard and archetype.From knowledge to clinical researchClinical research requires very specific information structures reused from the EHR. Archetypescan be also used for this purpose. LinkEHR can help in linking existing archetypes to moreabstract archetypes, enriching the existing information at the same time by combining clinicaldata with new data from terminology systems and other knowledge resources such as CDSS.ResultsThe proposed solution has been used to transform diabetes information from EHR standardinformation (HL7 CDA and CEN/ISO 13606) to clinical research standards (CDISC ODM).Diabetes Mellitus is becoming the pandemic of the 21st century, with a 7.5% of peoplediagnosed and another 7.5% who does not know about their illness. Thus, Diabetes Mellitus willrequire more innovative pharmaceutical products in the years coming. In clinical trial phase 4,monitoring of new deployed products is an important step in the clinical trial process. Takinginto account the number of people who can be treated by a new product, it will becomeappropriate to find an easy and fast way to report new information and issues from EHR systemsto the CT systems.For example, our EHR system provides information about prescriptions of one patient inCEN/ISO 13606 format. These prescriptions include the patient demographics, prescriptiondates, medication brand name, dose, pharmaceutical form, and a national medicine code. It canalso generate discharge reports of the patient in HL7 CDA format. These reports include the Page | 2
  • 3. CDISC EU Interchange 2012patient demographics, dates, history, procedures, diagnosis and recommended treatments.Finally, the laboratory information system generates HL7 v2 messages with the results of severallaboratory tests, including blood glucose level, glycated hemoglobin level (HbA1c), and others.In order to reuse these data for clinical research it is necessary to extract the useful informationfor the study and enrich it with additional data. To do this, we proceed in the following threesteps, also summarized in Figure 1. - Abstraction + Prescription Medication Archetype Archetype (CEN/ISO 13606 ) (CEN/ISO 13606 ) EHR Discharge Diabetes Study Archetype Archetype STUDY (HL7 CDA) (CDISC ODM) DB Laboratory LIS Archetype (HL7 v2) + Reuse - Figure 1. Archetype-based process for reusing EHR data in clinical research. 1. Describe clinical information with a formal, computable and reusable format. By defining archetypes for each information structure of the EHR we provide a formal and semantic description of the concepts used at that level of clinical care. In our example, this is represented by the prescription, discharge and laboratory archetypes. 2. Abstract and enrich the data to make it useful for a clinical study. We can create more abstract archetypes, suitable for clinical research uses, and in parallel, a data enrichment process can be executed. In our example, this means the creation of a new medication archetype. Data from the prescription can be reused and enriched by adding new Page | 3
  • 4. CDISC EU Interchange 2012 information, such as the active ingredient, the ATC code or the side effects of the medication. 3. Combine and transform data into the format for the CT system. A final transformation can put together all needed information into a CDISC ODM data instance representing a diabetes study in order to feed the CT database.Discussion / ConclusionThe use of archetypes provides a uniform approach for linking EHR systems and CT systems.The advantages of this model are: (1) It is independent of existing standards, software andarchitecture of EHR systems. (2) Allows making EHR and CT systems fully interoperable. (3)Allows fast solution development adaptable to fit different scenarios. (4) Assures the quality ofdata for clinical research.A model like this can be keystone in the way to reach a full collaboration between health andclinical research domains.References[1] European Committee for Standardization. Health informatics - Electronic health recordcommunication. EN13606, 2008[2] Maldonado JA, et al. LinkEHR-Ed: A multi-reference model archetype editor based onformal semantics, Int. J. Med. Inform. (2009), doi:10.1016/j.ijmedinf.2009.03.006 Page | 4

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