Biopharma Breakout Track Notes
Tuesday pm
Interest areas:
· APIs
· Argonaut/joining Argonaut
· Oncology
· Collecting data out of EMRs
· Connecting patients with the data
· RCRIM and BRIDG/ODM – CDISC standard for moving clinical data between two systems (XML format)
· Clinical Device trials
Mid-November – next milestone to propose plans for Jan FHIR connect-a-thon.
Topics for today:
· Use cases
· Data flows
· Report from connect-a-thon - Sam
· Lessons from Argonaut - Micky
· Experience with FHIR apps – Bev Buckta from Pfizer
· Lessons from clinicians on FHIR- workshop activities. Developers work with clinicians to help them understand. Viet will lead this discussion. Similar opportunity with FDA?
· Validation and testing – AEGIS will provide this presentation
· Next steps and plans
Processes that pharma can do better is one thing. Might also explore enabling areas that allow us to do new things that are not currently possible. Let’s discuss both and distinguish between them.
Wayne reviewed takeaways from previous meeting in April:
· High interest in FHIR among attendees
· What opportunities and use cases did we identify for improving interoperability
o Align with clinical research process
o Study design/planning; recruitment; Protocol feasibility
o Data collection; aggregation
· What are the top 3 priorities
· What systems and processes need to be introduced or changed internally to use hl7’s FHIR to improve interoperability
Wayne reviewed Use Case Priorities from April meeting and the additional feedback from from that meeting
Need to Increase awareness of FHIR among pharma by reaching key decision makers. Maybe get patient advocacy groups to demand the use. These groups are increasingly important.
Some discussion around privacy and security rules in different countries. Some at EMA are interested in using FHIR as an alternative way to represent information for Identification of Medical Products.
Argonaut presentation – Micky Tripathi – how could it apply to pharma?
· Driver for Argonaut was a common, external, specific need (MU). They narrowed the focus to a particular use case. Is there a similar common external need for biopharma?
· Could look a couple of different ways. It could be an Argonaut like project that this group does separately or it could be a separate Special Interest Group under the existing Argonaut
· Do you expand scope or go deeper in current use case? Original Argonauts wanted to go narrower and deeper
· In pharma, it is a challenge to develop relationships with EHRs
· *Novartis wants scope to increase in a way that is value-add for EMR vendors and industry as whole. They want research data collected using CDISC standards. Micky suggests developing a problem statement to present to Argonaut and describe how it would benefit from EHR/provider collaboration. Transcelerate might be the place to develop this problem statement.
· Concern that EHRs typically don’t have the structured data that biopharma wants.
· How aligned is Sync for Science with what we are doing? Some feel this is not very aligned
· John Burch feels most real world claims data is used for marketing. Could we find ways to improve drug discoveries and development (which includes clinical trials)? Are there ways that data that FHIR can now get can help on the drug discovery side?
· Potential use case: ePrescribing – how to look at who is taking what and mapping to genomics. What subpopulations have issues? This is de-identified data. There might be identified data that is de-identified (you don’t know the patient, but you do know the data is from same patient for 5 years). Some discussion about experiences to date.
· Argonaut is predominantly EHR focused now. If this group could find common ground to engage on, does the existing need to get high quality APIs impact what biopharma might want to do? There is no compelling need that will drive the EHRs toward what biopharma wants unless it falls under population health. Oauth enables patient to authorize their data to be used.
· January connect-a-thon – you need to tell FMG what tests/activities you want to try. The resources that will mature most quickly are those that have the volunteers willing to do the work, so Biopharma needs to get more engaged.
Connectathon Experience – Sam Hume
· Use cases
o Use FHIR to retrieve data from an EHR to pre-populate Case Report Forms
o The test scenario – create a web page that allows a clinician performing the role of site coordinator to match research subjects to patients and allow import of data into Rave via FHIR API. Once patients are matched to Subjects, you can import content.
o Used Rave API to load data from the FHIR Patient resource into the demographics CRF
o Used Rave API to load data from the MedicationStatement Resource – take meds listed for patient an loaded to Rave conmeds CRF page
o Alternative approach using HAPI-FHIR- same use cases and data, but uses different technical approach. Didn’t have access to Rave, so loaded the content into CDISC ODM-XML CDASH CRFs.
o Lessons learned
§ Much simpler to retrieve EHR content using FHIR vs parsing a CCD document to load the same info
§ Certain FHR resources have obvious applications within clinical research
§ Resource extensions will be required in certain cases in order to complete a larger percentage of the content expected for clinical research. Ethnicity and Race are examples of resources already there.
§ Profiles will be necessary to constrain the resource content to better match the data expected in research CRFs.
o Additional connectathon observations:
§ Well organized and easy to access documentation
§ Numerous test servers with test data are available
§ Lots of open source software is available
§ Active, global community supports FHIR
§ Technology friendly – reduces technology as an implementation barrier
§ Able to quickly get started without prior training
o Next steps
§ Expanded review of resources related to ONC Common Clinical Data Set (CCDS) and mapping to CDISC standards content
§ Experiment with extensions to add data that naturally extends an existing resource and represent required data for clinical research
§ Experiment with profiles to better understand how they could be applied to make healthcare data better match clinical research requirement – data required by the CDISC standard; manage different code systems.
What can we do next and pitch to Argonaut:
o Data collection for clinical trials – lots of edges we could focus on
o Specific data elements you wish to focus on with terminology translations
o Eligibility and recruitment
o Safety/regulatory
EDC vendors would probably be interested in activities that fit with their business models.
o EHR eSource data is important and FDA wants the data to be standardized. Using existing EDC systems people are using and pull in data from EHR. This is trivial to do and could significantly simplify things.
o Getting subject and study ID aligned with EHR identifiers
o Extensions done for efficacy data. Defining the elements and terminologies. If you want to look at a disease area, select one not overly complex
o Adverse events – if these could be pulled down directly through FHIR, this would be ideal. Under the earlier Aster project, when a person was removed from a drug, they generated a form but FDA wasn’t able to process the form data directly. FDA may be working on this with Kaiser and Duke.
Comparing data flow with and without FHIR – Wayne presented
o FHIR will eventually allow for virtual repositories that can be dynamically queried as needed rather then creating multiple copies of data that are transformed over and over for different purposes. FDA reviewers can view source in EHR of individual subjects – such as those experience serious adverse events. Structured Data Capture can create forms necessary only for data this is not in EHR making a simpler, more traceable process. Since FHIR can produce data in standard format, fewer transformations should be required. Requires transition from SAS Xport.
Possible use case for next connectathon (need to write a proposal by mid-November);
o Data collection - Further assess the use of the FHIR API to pull relevant data than can be used to pre-populate EDC CRFs for clinical trials
§ Determine how much data is available that is relevant to research
§ Assess data quality and consistency across different systes
§ Evaluate speed of access
§ Improve efficiency of trial conduct
o Protocol Feasibility – Identify a representative set of eligibility criteria relevant to pivotal/critical clinical trials and assess the readiness of using the FHIR API to get a rapid count of potential subjects who may be eligible for a clinical trial. This would fit well with Argonaut. Need to provide representative search data as a baseline and determine how to represent these in an expression language that can be run through FHIR API.
o Patient Centricity and population health
o What data does pharma need to do this
o How can it be used to improve development programs and trial design
o Hit on the Argonaut use case to enable the patient to collect all of their relevant medical data and make it available to the research project (EHR, omics, etc)
Wed AM
Bev Buckta presented on Pfizer’s app, which reaches out to patients directly to collect immunization records. This application has been developed in FHIR and fully tested, and they’re actively looking to pilot it in a production healthcare environment.
Viet Nguyen presented a recorded video on Clinicians on FHIR. Wayne noted that biopharam may wish to work with investigators/reviewers in a similar manner to understand what we are doing. They would be able to tap into the EHR. Viet demonstrated David Hay’s ClinFHIR tool.
Mario Hyland presented on continuous testing. There is a national ROI many orgs are realizing thru the use of Shared Services in a cloud based ecosystem. Mario will help this group write a proposal to get into the FHIR connectathon. He mentioned they have renamed conformance statement to Capability statement. Testing is available 24/7/365. He is an advocate of Test Driven Development (TDD). This type of testing approach may have other applications to reduce the effort of software validation in general within Biopharma.
Wed. PM – Other Use Cases and Next Steps:
Continued discussion on use cases. There is some interest in exploring how FHIR could be used to connect EDC with EHR – to send back queries about recorded data and keep the two databases in sync to simplify traceability from eSource to Clinical Database. Might be easier to begin in the Post-Marketing world first.
The Argonaut Provider Directory IG might have some benefit to help identify potential investigators for clinical studies.
Some discussion on how to interpret the ONC requirements for an API required under Meaningful Use 3 in 2017. They are waiting for FHIR to have a normative release but are actively encouraging that approach.
With regard to regulatory use cases, it will be necessary to provide a lot of education to FDA to make progress. Probably premature to explore these use cases (such as drilling down to the EHR from a submission dataset to further explore the patient record or supporting REMS) at this time until FDA becomes more familiar with the potential of FHIR. Would be good to emphasize positive benefits of supporting the FDA’s mission of advancing public health – not just study submissions. Likely to be greater interest in CDER Division of Hematology and Oncology and Oncology.
Some discussion about future discussion on ways that will promote patient engagement and population health.
Closing statements:
In addition to reviewing key points, there was interest in exploring some cross-track topics in the next Partners meeting:
§ Combining Pharma with payers to discuss ways to work together on care plans and protocols related to Diabetes
§ Combiing Pharma with Clinicians to discuss how both could leverage work being done to define data elements related to Clinical Registries on FHIR to support biopharma research studies as well.
§ It was noted that the Atlanta location will provide the opportunity for more interaction with CDC, which might merit exploring the impact of FHIR on VAERS and public health surveillance
§ Interest in engaging greater involvement from the TransCelerate Biopharma eSource project team.