Learning Health System
12/13/17 | Discover Insights
MU’s strides in precision medicine can be conceptualized as “big data” that uses rapidly accumulating information systems related to the genome, metabolome, microbiome, environment, biosensor technologies, and individual behaviors, among others. Although precision medicine is more than just genomics, these data sets are particularly relevant for many areas of physician practice.
Genomic data presents many challenges for the current generation of EHRs, including:
- Data storage
- Data life cycle
- Data standards,Complexity of order entry
- Complexity of data interpretation
However, the EHR is rapidly becoming a platform that uses new standards, such as HL7 FHIR (Fast Health Interoperability Resources) and SMART (Substitutable Medical Applications and Reusable Technology). These platforms enable third-party developers to rapidly integrate next-generation applications into EHRs.
This “SMART on FHIR” framework enables Clinical Decision Support (CDS) strategies that leverage “hooks” to provide:
- Context-sensitive information
- Alternative choices for providers
- Access to more in-depth applications, if needed
The EHR can already capture the phenotypic and clinical information to enhance personalized medicine. We believe this capability presents a unique opportunity for precision medicine at MU.
Planning for the future
In January, we held a retreat to identify areas where MU faculty can make unique scientific contributions that do not largely duplicate research at peer institutions.
We chartered four interdisciplinary teams to identify pilot projects in the domains of oncology, cardiovascular disease, autism spectrum disorders, and “Beyond Next Generation Sequencing”.
Through these pilot projects, we will grow biospecimen collection standards, storage protocols, information analytics and workflows needed to support each of these initiatives.
We charged a fifth team with developing a proposal for a technology-enabled, clinical decision support precision medicine project.
Through these pilot projects, we will expand the technical manpower needed to enhance the biomedical informatics infrastructure at MU.
Expanding our industry partnerships
Industry partnerships represent a source of potential research funding. As such, we are building on our successful engagement with our first partner, and are investigating other industry partnerships.
With one partner we aim to develop an application for the efficient collection, organization, and presentation of tumor board data and references.
Efforts are underway to build Phase II of the project, which impacts development using SMART on FHIR technology. We are having conversations about where we want to take the relationship over the next five years — beyond the end of the project.
We are also talking with two premier device companies. One proposal is a Joint Research Data Center that will merge implanted rhythm management device data with MU’s clinical data to explore and develop new predictive models for cardiac interventions.
An early demonstration project focuses on our ability to integrate a cloud-connected enteral feeding device into the Cerner EHR. This demonstration project will help develop a research platform for putting translational device-related decision support into practice.
Exceptional access to data
Over the next year, MU looks to extend our leadership in the Greater Plains Collaborative (GPC). Initially funded by the Patient Centered Outcomes Research Institute, this Community Data Research Network (CDRN) represents a critical opportunity for continuing to expand research funding.
Many GPC members use competing EHRs, so participation is an opportunity to demonstrate MU, Tiger Institute, and Cerner capabilities in the data sharing arena. As a full participant in the Patient-Centered Outcomes Research Network, we continue to enhance our Common Data Model (CDM). This work enables participation in nationwide trials, such as Aspirin Dosing: A Patient-Centric Trial Assessing Benefits and Long-Term Effectiveness, “ADAPTABLE” clinical trial.
Our next milestone is to enhance the CDM with American Community Survey data to enable participation in a nationwide diabetes study called Natural Experiments for Translation in Diabetes.
I2B2 continues to be a centerpiece of our data-related cyberinfrastructure plan. Our focus has been on both ensuring quality of I2B2 and continuing to enhance with new datasets.
Over the next six months, we will move a copy of this tool to our local environment. This will increase the scale of this critical asset to support researchers and make us more agile in the marketplace.
In the past, we would often support research with a time-intensive, one-time build of a research dataset. In the future, we will direct those same resources at enhancing the existing I2B2 clinical ontology with geospatial and publicly available data (such as the American Community Survey Data).
More large-scale research projects
In early 2017, the MU Research Computing Support Services group successfully completed the security review process for a High Performance Computing (HPC) environment capable of storing/processing ePersonal Health Information.
This Secure4 environment lets us do large-scale health and bio-informatics projects, such as data mining and predictive algorithm development.
Our first demonstration projects center around the availability of HealthFacts data in the HPC environment.
With more tools and infrastructure in place, along with well-defined common goals, we look to a future in which our partnership can further enhance research at MU.
Collaboration the key to becoming a regional and national player
In 2018 we will focus on how to bring Cerner and Tiger Institute capabilities together to further our clinical research priorities and mission. In this environment, we look to maximize the benefit from industry partnerships.
Through the GPC CDRN and our participation with the Kansas City Area Life Sciences Institute, we are solidifying our relationship with University of Kansas Medical Center on the Kansas City side.
A recent Clinical and Translational Science Award partnership with Washington University is a move toward strengthening our relationships in the St. Louis area. The objective is to streamline the environment to enable researchers to take discoveries and turn them into clinical practice with Bio-Medical Informatics as a key enabler.
Through these partnerships, we will grow MU’s iconic standing in the research community.
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