201705 Clinical Research

Track Name

Clinical Research Track

Submitting WG/Project/Implementer Group

Biopharma FHIR project group TransCelerate Biopharma eSource Work Stream

Justification

This track is intended to continue to further explore the benefits of FHIR for clinical research of new biopharmaceutical experimental treatments, and to increase visibility of FHIR within the biopharmaceutical community. advance the use of FHIR resources as eSource data used to pre-populate clinical research case report forms for both regulated and non-regulated clinical research. This builds on previous explorations in Connectathon 13 and 14.

Clinical Research studies currently require the redundant entry of clinical data that already typically resides in Meaningful Use conformant EHR systems. EHR data represents original records in electronic format that can be used as eSource and directly imported into clinical research EDC databases so as to improve the quality and consistency of data between EHR and EDC systems and eliminate the need for redundant data entry. Establishing interoperability between EHR and EDC systems to streamline and modernize clinical investigations should improve data accuracy, patient safety, and clinical research efficiency. Given the extreme cost and extended time required for randomized clinical trials, it would be substantially better to utilize EHR source data to directly populate clinical trial databases wherever feasible. The May 2016 FDA draft guidance titled “Use of Electronic Health Record Data in Clinical Investigations” encourages the sponsors of clinical research to use EHR data as noted in the statement below. FDA encourages sponsors and clinical investigators to work with the entities that control the EHRs, such as health care organizations, to use EHRs and EDC systems that are interoperable. EHRs may be interoperable with EDC systems in a variety of ways depending on supportive technologies and standards. Interoperable technology may involve automated electronic transmission of relevant EHR data to the EDC system. For example, data elements originating in an EHR (e.g., demographics, vital signs, past medical history, past surgical history, social history, medications, adverse reactions) may automatically populate the eCRFs within an EDC system.

TransCelerate Biopharma, a consortium of 18 of the largest global pharmaceuticals, has engaged an eSource project team that will be sending representatives to the Madrid Connectathon seeking to further assess the readiness of FHIR toward the goal of creating a FHIR IG for Clinical Research. This project will build on prior work and also explore in more detail the processing of local lab data collected for patients experiencing Serious Adverse Events, which is currently a challenging prospect for clinical trials.

Proposed Track Lead

See Connectathon_Track_Lead_Responsibilities Wayne Kubick (wkubick@hl7.org), Sam Hume (swhume@gmail.com); Geoff Low (glow@mdsol.com)

Expected participants

Medidata Solutions, TransCelerate member companies (contact: kenneth.milstead@kinapse.com), Oracle, Other EDC and EHR Vendors (TBD)

Roles

Please include information here regarding how much advance preparation will be required if creating a client and/or server. This track will need to have a server supporting STU3 that includes some sample EHR data for at least 3 patients including Patient, Observation (lab) and MedicationStatement resources. The server must also support use of the ResearchStudy and ResearchSubject resources, and include sample data ( prepared with ResearchStudy identifier='201705CR001' and ResearchSubject identifiers='0001'. '0002', '0003'

Clinical Trial Designer

Sets up patient matching criteria by ResearchStudy and ResearchSubject for a synthetic test study. Creates EDC case report forms with variable mappings to FHIR that will receive EHR patient data for 1-3 clinical trial subjects.

Data Collector

Queries API to identify patients by Study and Subject identifiers to pull EHR data for demographics, medications and lab data that maps directly to variables on eCRF.

Scenarios

Scenario Step 1: Get ResearchSubject Data

Action: Identify subjects in an EHR who are participating in a given clinical trial.

Precondition: A patient has been enrolled in a named clinical study and assigned a subject identifier, both identified in the EHR. The patient has been assigned to a primary caregiver that functions as the clinical investigator. Patient clinical data has been captured in the clinical investigator’s EHR. Note Initial EHR data has been mapped and loaded into an EDC system by the Clinical Research Track during Connectathons 13 and 14, including Demographics data elements DOB and gender. MedicationStatement resource data was mapped into the Concomitant Medications CRF including data elements: effectivePeriod/start, effectivePeriod/end, dosage/text, and route. Connectathon 14 added other Demographics patient elements and Vital Signs. Connectathon 15 will test patient matching using new STU3 resources and collecting lab data.

Success Criteria: At least 3 clinical subjects enrolled in the clinical trial have been identified with identifiers and other relevant information sent as FHIR resources.

Bonus point : Document the mapping of CCDS content to CDISC standard data elements.

Identify patients who are in the study using FHIR API and pull relevant data into EDC.

Scenario Step 2: Collect ResearchSubject Lab Data and convert to CDISC

Action: Create mappings for a sample set of the most commonly used lab parameters in clinical trials.

Precondition: Lab data stream has lab data available. One patient has at least 2 sets of lab observations for at least 3 lab tests. LOINC codes for the set of lab tests to be used and mappings to CDISC for these will be specified in advance.

Success Criteria: The lab data is successfully imported into an EDC system and the EDC system shows both the original test name and unit and the mapped test name and unit.

Bonus point : Document the mapping of CCDS content to CDISC standard data elements.

TestScript(s)

TBD