Digital healthcare is generating enormous volumes of data related to the health status of patients, but the electronic data currently is not used well for clinical research.
The current clinical research operating model was developed decades ago, prior to digital healthcare. It grew out of individual study workflows and capturing patient data on forms, making it largely disconnected from routine clinical practice and modern, real-world care delivery systems.
Current clinical research inefficiencies
There are many known issues and inefficiencies with the current clinical research model, said Tom Langan, CEO of Veradigm, a vendor of EHR, practice management and e-prescribing technologies, including:
- High costs and relatively long timeframes are common due to the level of rigor and regulatory oversight associated with data capture in traditional trials.
- View of the patient’s overall healthcare journey is limited to the data collected for individual studies.
- Little interoperability, connectivity between studies, or reuse of the data outside of the study, creating “research data silos.”
- Challenges with patient recruitment and retention because patients often are required to participate in a parallel environment to their normal clinical setting.
- Strict inclusion requirements needed to accurately test a hypothesis often are not generalizable to product use “in the wild,” where treatment in the trial may not reflect routine practice patterns, and the patients participating in the trial may not reflect the actual population that will be treated.
- Data generated through healthcare digitization is largely untapped for research despite the wealth of medical insights and data available as routine clinical service becomes digitized.
Electronic health record vendors develop platforms to enable digital healthcare delivery at the point of care. Veradigm recognized the opportunity to leverage its platforms and scale in a new market – life sciences – bringing research into point-of-care workflows and producing research data as a natural output of the care process, Langan explained.
Compiling a massive amount of clinical data
Today, Veradigm Life Sciences is focused on implementing a new clinical research operating model it calls “integrated research.” Toward this goal, the vendor has entered into several partnerships that focus on different aspects of the integrated research model, Langan said.
Its partnership with NextGen allows it to capture non-hospital clinical data on nearly 20% of the active patient population in the U.S. across the two companies’ combined EHR platforms. They so far have amassed 150 million de-identified EHR patient records supporting large-scale medical research.
“The current healthcare ecosystem is fragmented and no one company can provide a complete solution.”
Tom Langan, Veradigm
And as part of Veradigm’s strategic relationship with the American College of Cardiology, the vendor acquired the Pinnacle and Diabetes collaborative registries – which represent the largest and deepest collection of cardiometabolic patient data in the U.S. comprising 18 million patients.
“Part of our strategy is to go deep into targeted therapeutic areas, with an initial focus on chronic diseases that have a significant population impact,” Langan said. “Our recent partnership with Komodo Health has produced a linked EHR/claims data asset of nearly 50 million patients. Linked EHR and claims data provides a complete picture of the patient journey – including both clinical and economic outcomes.”
And Veradigm’s partnership with Microsoft is focused on developing a “research workbench platform” that integrates directly with EHR systems, enabling new research data capture at the point of care, he added.
“The new research model relies on technology platforms that collect study data completely outside of point-of-care workflows,” he said. “This model makes new data capture more efficient, enables integration with digital health data already captured and is potentially much less expensive.”
EHR-agnostic ‘integrated research’ model
Veradigm proposed “integrated research” model is an EHR-agnostic research workbench that attaches to EHR systems using public standards and interfaces. The vendor is working with Microsoft to develop an integrated research workbench and expects it to be available early next year.
There is a variety of key issues that an integrated model should be able to solve. First is virtual visits. Current telemedicine capabilities provided in many EHR systems can be extended to support virtual study visits, allowing data to be captured without requiring the patient to travel to a study site.
Next is the digital healthcare journey: “The use of the EHR as the foundation of research enables the creation of an integrated ‘digital healthcare journey’ for each patient,” Langan said. “And then comes patient engagement. Technology already part of many EHR systems can reach out to patients and notify patients of studies they qualify for and facilitate an electronic informed consent process.”
Another key issue that an integrated model should be able to solve is protocol, patient and physician matchmaking.
“It should automatically identify patients who qualify for study protocols and alert physicians of patients within their practice who qualify for research protocols,” Langan said. “Another key issue is study feasibility. A model should collect data about patient characteristics and availability, site performance, and investigator availability in one place at scale, enabling effective feasibility studies.”
AI and machine learning curates data
Yet another key issue is eSource data, Langan said. A model should use technology such as AI and machine learning to curate structured and unstructured patient data into high-quality data for use in clinical research, he said.
EHR-based electronic data capture should be part of extended EHR systems that support research data capture and enable researchers to link the research data collected back to the patient data record, Langan said.
“And finally, digitized protocols should standardize key elements into a quarriable format,” Langan said. “The structured digital representations of a clinical trial streamline the review process and allow for analysis of the relationship between study design and conduct.”
Veradigm currently is early in development of the research platform and is executing pilot studies concurrently as it builds the platform. Examples of pilots that are currently underway include:
- Using EHR patient data to identify patients who may qualify for a study, and notifying their provider.
- Alerting physicians with patients who present with flu-like symptoms, and analyzing whether these patients had a flu shot, and if so which one.
- Identifying patient populations where treatment provided is not aligned with treatment guidelines, and providing education at the point of care for those targeted populations and treating physicians.
Clinical database yields dozens of studies
To date, Veradigm has executed and presented dozens of studies using its large patient database. Three recent studies that were accepted for presentation at national conferences include:
- “Characteristics of Migraine Patients with Migraine Disability Assessment (MIDAS) Scores in Real-world Clinical Practice” (with Amgen), presented at the International Society for Pharmacoeconomic and Health Outcomes Research (ISPOR) 2019 Conference this spring.
- “Extracting and Standardizing Social Determinants of Health Diagnosis from Problems List from a Large Ambulatory Electronic Health Record Database.” To be presented at the American Medical Informatics Association in November.
- “Building a Left Ventricular Ejection Fraction (LVEF_ extraction pipeline for SOAP notes).” To be presented at the American Medical Informatics Association in November.
“The current healthcare ecosystem is fragmented and no one company can provide a complete solution,” Langan said. “The market is moving at lightning speed: Partnerships that combine complementary capabilities and create scale can quickly provide unique value. Digital healthcare delivery creates enormous opportunities to leverage patient data; solutions that are able to use that data to connect and engage stakeholders around the healthcare transaction provide more value than data and analytics alone.”
An ecosystem of connected partners that create a “platform of health” has the potential to provide much more value to the healthcare market, as opposed to the current status quo where individual vendors are creating point-to-point solutions and solve one problem, he said.
Email the writer: [email protected]
Healthcare IT News is a HIMSS Media publication.
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