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Precision medicine isn’t just about genomics anymore. With the field moving forward as the next step in population health management, environmental, social and lifestyle factors that live outside the medical system are increasingly important to target treatments and engage patients. That means health plans also need innovative technology solutions to capture, store and integrate this crucial information.
Mention precision medicine, and genomics quickly comes to the top of mind. While genomics and clinically oriented analysis are extremely valuable in implementing precision medicine as the next step in population health management, they are really only a small part of the big picture.
Increasingly, the value of environmental, social and lifestyle factors that live outside the medical system is also getting recognized in the effective implementation of personalized medicine in this country. The federal government’s Precision Medicine Initiative (PMI) that calls for $215 million in fiscal year 2016 to support research in this area focuses not just on genetics and biology, but also behavior and environment - “with the goal of developing more effective ways to prolong health and treat disease.”
The funding includes a $130-million allocation for the National Institutes of Health (NIH) to build a data-driven national PMI Cohort Program of 1 million or more participants from diverse social, racial/ethnic and ancestral populations living in a variety of geographies, social environments and economic circumstances, and from all age groups and health statuses. This initiative will collect extremely valuable data on social and environmental determinants of health to help guide effective, individualized treatment plans.
Meanwhile, many health plans focused on achieving the Institute for Healthcare Improvement’s Triple Aim of improving population health, enhancing patient experience and reducing costs are already digging deeper into the aspects of precision medicine that extend beyond genomics.
When it comes to targeted treatment, success is often very much related to lifestyle and social circumstances such as patients’ motivations and life goals. Precision medicine is not just about which drugs can best treat which patients, but also specific ways that patients can get and stay healthy via individualized treatment plans that fit their lifestyles and social circumstances.
In order to deliver the most effective healthcare, including early interventions and effective preventive care, it’s critical to capture and analyze patient data such as social and environmental determinants of health. For example, factors that can have a major impact on outcomes include: family history, social media use, whether patients have transportation to doctors’ appointments, and whether they live alone.
Having access to this type of information can drive interventions that affect quality of care. For example, research has shown that patients who live alone have a much higher chance of preventable hospital readmissions than those who have family members at home. If these patients are flagged prior to discharge, unnecessary readmissions can be prevented by taking steps such as follow-up calls and/or visits from social workers or case managers.
A recent example in the news related to social factors that may be tied to health is the University of Pittsburgh School of Medicine study that found the more that young people used social media, the more likely they were to be depressed. Collecting data such as social media use and flagging at-risk patients for interventions is another example of how these types of analytics can be harnessed to improve healthcare.
While caregivers and clinicians traditionally do go through some questions about social, environmental and lifestyle factors when taking a patient’s history, they may struggle with some of the nuances - and there are always time factors at play. When health plans work with a precision medicine-focused data analytics company with an open platform that can combine all data types collected from many sources, this type of information can be effectively managed and related to the clinical record. This open platform integration removes the limitations of a closed-system electronic medical record (EMR).
Access to this crucial data prompts an individualized care plan that will be most effective for each patient, and the clinician saves time by not having to go through as many questions. This also removes the variability of a clinician being unaware of specific social questions that should be asked.
A new report from the Journal of the American Medical Informatics Association found that nearly half of patient face-to-face contact with healthcare providers - checkups, emergency department visits, and even hospital admissions - were missing from their electronic medical records. Imagine what that means as related to social and environmental determinants of health that aren’t being captured - but can and should be.
Ultimately, this data-driven care management approach results in greater engagement, which leads to healthier patients. When health plans focus on making patients’ social and environmental data available to clinicians and it’s combined with evidence-based guidance to target treatment, clinicians can set effective, achievable treatment goals. As a result, patients begin to see progress, they engage better, and more effective disease management and prevention follow.
Wayne Oxenham was recently appointed president-North America at Orion Health, after serving in various leadership roles within the company since 2003. Orion Health’s open-data platform - which has offered storage and integration solutions to clients for genomic and social data for more than 12 years - delivers technology solutions to drive interoperability, population health management and precision medicine.