In 2003, the National Human Genome Research Institute used the tagline From Double Helix to Health to celebrate the sequencing of the human genome. Many people hoped that a genomic revolution would soon enable personalized medicine to predict, prevent, and mitigate disease. But the path from a scientific breakthrough to transforming health care is not straight.
Even beyond next-generation gene sequencing and developing diagnostic tools and targeted therapies, the basic approach to clinical care has to be re-envisioned to fulfill the promise of personalized medicine. Specifically, care must move from sporadic treatment of episodic disease (a reactive mode) to predicting disease and then acting to prevent and mitigate it (a proactive mode).
Lofty goals for personalized and precision medicine (PPM), reflected in the 2015 Precision Medicine Initiative, are out of reach until the health care delivery system is designed for health promotion, comprehensive disease prevention, and efficient adoption of PPM capabilities. Toward that end, we believe in a personalized health care approach that abandons the reactive find-it-and-fix-it model of care and more effectively addresses the complex chronic diseases that now account for about 80% of health care expenses.
Prospective Care with a Clear Clinical Workflow
Disease develops dynamically as a consequence of inherited genetic susceptibilities and resistances, influenced by environmental factors. At the Duke Center for Research on Personalized Health Care, we reason that, with available and emerging tools, risk for disease can be quantified and prevention measures initiated before pathology develops — and that when it does, its mechanisms can be identified so that disease is treated with precision.
Our inflection curve, shown in the figure above, illustrates how disease evolves and where potential interventions can minimize disease burden. In line with that concept, our personalized health care model is fundamentally prospective: It aims to reorient front-line care so that health risks are identified and stratified early, healthful behaviors are promoted, and disease is either prevented or precisely treated.
The model uses optimal clinical judgment, best available risk-assessment tools, disease-tracking biomarkers, precision diagnostics, and targeted therapies — and it customizes care for the individual patient in the form of personalized health planning (PHP). That kind of customization can be rendered in a five-step workflow process, adaptable to available resources:
- Before meeting with the clinician, a member of the care team assesses the patient’s level of engagement and capacity for self-management, so that the patient can participate in his or her care in a meaningful way. As part of that process, the patient completes a self-assessment of health needs, preferences, and goals by telephone, electronically, or in person. Through the medical record, this information is conveyed to the clinician before or at the time of the appointment.
- The clinician assesses the patient’s health status and health risks using the best available conventional, genomic, and other precision diagnostic tools. Optimal risk-mitigation and therapeutic goals for the patient are identified.
- The clinician and patient set and clearly articulate shared goals, using the clinician’s health assessment and the patient’s self-assessment.
- The shared goals are then incorporated into a personalized health plan that the patient is directly involved in crafting. The clinician chooses appropriate metrics for monitoring progress, identified explicitly for the patient; an electronic medical record is used for data collection and tracking.
- The clinician coordinates care with the rest of the patient’s care team and arranges for appropriate follow-up.
With this five-step process, the personalized health plan becomes a living, adaptable document — available to all team members — that is continually revisited in person, by phone, and/or via patient portals and mobile applications.
Personalized Health Planning in Practice
The Veterans Health Administration (VHA) has identified personalized, proactive, patient-driven care as one of its major strategic goals. To this end, it has conducted primary care pilots at diverse clinical sites to determine whether primary care clinicians can adopt PHP into their practices. VHA Patient Aligned Care Teams have provided a team-based structure for PHP, and results indicate that the model can indeed be integrated into primary care workflows. Ongoing work to refine and disseminate the PHP approach is part of a larger effort to improve veterans’ health.
At Duke University Medical Center, we have incorporated PHP within shared medical appointments (SMAs) for patients with type 2 diabetes. Each patient in the group is provided with health self-management tools, sets shared health goals with his or her clinician, and creates a personalized health plan to track progress.
We expect that by increasing patients’ commitment to achieving meaningful health goals, this approach could amplify the benefits of SMAs for chronic disease care. In routine primary care, PHP is designed to leverage the capabilities of the patient-centered medical home, which focuses on disease prevention and patient engagement.
PHP elements can also be integrated into clinical decision trees for defined episodes of care (e.g., for treatment of cancer or congestive heart failure), so that best practices can be followed more easily. Supported by the electronic medical record, decision trees can guide clinicians in selecting the most appropriate validated diagnostic tools and therapies while they involve patients in setting and adhering to shared goals. This model also facilitates continuous learning, as data collected across decision points can be analyzed to assess efficacy and create predictive algorithms.
In diagnosing and treating cancer, for example, standard-of-care guidelines can be used to create a workflow similar to the one shown in the figure below. The evaluations of the patient’s health status and health risks identify the presence of cancer (left panel); the cancer mechanism is defined and appropriate chemotherapy and targeted therapy options are chosen (middle panel); and clinical progress is measured and therapy revised as necessary (right panel). At each stage, relevant precision tools are employed.
The 1910 Flexner Report shocked the medical establishment into incorporating scientific advances to transform how disease is defined, diagnosed, and treated. More than a century later and a decade since the genomic revolution, it’s again time to redesign clinical care to also enhance health and prevent disease.
Fundamental change is not easy, however. As President and CEO of the Duke University Health System from 1998 to 2004, I (Ralph Snyderman) witnessed firsthand the financial obstacles created by perverse reimbursement incentives that inhibit implementation of innovative clinical delivery models. To realize the promise of personalized health care, health policy leaders, providers, payers, and implementation scientists must coordinate their efforts to arrive at a rational, proactive approach to health care delivery. If we want to stem the epidemic of preventable chronic diseases and improve our nation’s health, we have no other choice.
This article originally appeared in NEJM Catalyst on December 28, 2016.