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Difference between revisions of "201709 Clinical Research"

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1) Apply clinical study eligibility criteria (using both structured and unstructured data) to identify potential study investigators and subjects using FHIR API
2) Pre-populate EDC eCRFs for clinical study subjects using EHR data (patient demographics, encounters, observations, diagnosis, medications, healthcare resource utilization) retrieved through FHIR API
3) Explore updating patient data in EHR after data corrections have been identified and verified in EDC study database
4) Explore integration of patient-generated data (possibly collected using SMART-on-FHIR apps) with EHR patient data, and explore import of the patient-generated data back into the EHR.
5) Explore conduct of a long-term randomized clinical study, with protocol/plan definition, e-consent.
6) Explore use of CDS Hooks during patient encounters to notify study project manager and to identify protocol deviations.
===Scenario 1 Examining EHR patient data for protocol feasibility and clinical trial recruitment ===
===Scenario 1 Examining EHR patient data for protocol feasibility and clinical trial recruitment ===

Revision as of 21:17, 23 June 2017

Track Name

Clinical Research Track

Submitting WG/Project/Implementer Group

Biopharma FHIR project group; TransCelerate Biopharma eSource Work Stream


This track will 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. This track advances 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. It will also explore use of PlanDefinition in the context of research protocols. This builds on previous explorations in Connectathon 13-15.

Plans for this connection include participating from at least 5 Pharmaceutical companies, Members of TransCelerate Biopharma, Inc. consortium, who will be bringing programmers from the EDC vendors they work with to manage clinical study databases. A set of 4-8 detailed use case scenarios will be proposed. A challenge grant award will be issued by TransCelerate to the pharma/vendor team that creates the best FHIR solution to meet one or more of the scenarios. This work will inform development of profiles and IGs to support clinical research using FHIR.

Clinical Research studies currently require the redundant entry of clinical data that already typically reside 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.

Proposed Track Lead

See Connectathon_Track_Lead_Responsibilities Wayne Kubick (, Sam Hume (; Geoff Low (; Trisha Simpson (

Expected participants

TransCelerate Biopharma, Inc., UCB, Pfizer, Novo-Nordisk, GSK, Merck, Lilly, Medidata, Oracle Health Sciences


Please include information here regarding how much advance preparation will be required if creating a client and/or server.

Role 1 Name

FHIR Client

Support the sending and receiving of clinical research study data: create, read, search and update from a clinical study database system or a patient device.

FHIR Server

Support the sending and receiving of Clinical Research subject and study data from an EHR.

Clinical Trial Designer

Sets up patient matching criteria and identifiers for ResearchStudy and ResearchSubject for a synthetic test study. Creates study database, mappings/interfaces, EDC case report forms with variable mappings to FHIR that will receive EHR patient data for clinical trial subjects. Generate updates from EDC to apply to the EHR.

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. Provides data generated by patients to add to study databases or EHRs.


Scenario 1 Examining EHR patient data for protocol feasibility and clinical trial recruitment

Action: Queries are run against EHR data to identify patients who may meet certain sample protocol eligibility criteria
Precondition: At least 1 patient meeting eligibility criteria exists in the EHR database; may be preassigned a study and subject identifier
Success Criteria: Returns counts, practitioner identifiers, patient identifiers
Bonus point: Assign a ResearchStudy Identifier and ResearchSubject Identifier in EHR for enrolled subjects

Scenario 2 Extract relevant EHR data for ResearchSubject and import into Study Database

Action: Identify
Precondition: Patient records include demographics, MedicationStatement, Lab observation data, possibly problems, diagnosis, healthcare utilization data. At least 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 EHR data is successfully imported into an EDC system for the selected subject.
Bonus point : Document the mapping of CCDS content to CDISC standard data elements.

Scenario 3 Receive and apply updates to the study database as new or changed data is recorded in the EHR

Action: Enter new data in EHR for a current ResearchSubject after new patient encounter is recorded in EHR
Precondition: Patient is enrolled as a ResearchSubject for a ResearchStudy.
Success Criteria: The updated EHR data is successfully imported into an EDC system for the selected subject.
Bonus point : Use CDS Hooks to trigger update after patient encounter is recorded.

Scenario 4 Import Patient-generated data into EHR for ResearchStudy

Action: Import relevant new data in EHR for a current ResearchSubject generated from SMART on FHIR App on mobile device.
Precondition: Patient is enrolled as a ResearchSubject for a ResearchStudy. SMART on FHIR App relevant to research is identified and able to import data into EHR.
Success Criteria: The subject data is successfully imported into an EDC system for the selected subject and available for export to Study Database.
Bonus point :The subject-generated data is successfully imported into Study Database.