Precision Medicine Goes Mainstream at Leading Health Systems


By Alissa Winzeler-Cotton


Precision medicine (or personalized medicine) has been a buzzword in the healthcare industry for many years. Depending on the audience, its use can evoke either a panacea in which each patient is given a therapy tailored exactly for them, or a pipe dream in which patients try designer drugs that fail to deliver the promise of a miracle cure.  The reality, as always, lies somewhere in the middle.  Precision medicine is a practical approach to improving care by identifying which therapies, out of a growing array of options, are most likely to benefit a specific patient, taking as many relevant factors into account as possible.  

This is important because, for so many diseases, a large percentage of patients simply don’t respond to any given treatment.  Diabetes drugs, for example, are effective in only 57% percent of patients.  Arthritis drugs: 50%.  Alzheimer’s drugs: 30%.  Finally, cancer drugs are typically only effective in 25% of patients*.  This means that the value of precision medicine is really in developing an increasingly nuanced understanding of the specific factors that are likely to impact a patient’s response to therapy, and using that understanding to improve the choices that are made regarding a patient’s care.

Precision Medicine is a Top Strategic Priority for Leading Health Systems

A recent study by the Health Management Academy (“the Academy”) has shown that a precision medicine approach to improving patient care has gone mainstream at health systems across the country.  In a survey of C-suite executives and service line leaders at leading health systems (LHS), the Academy found that 67%  were “very likely” to place precision medicine as a “top strategic priority over the next 3-5 years.”  In qualitative interviews, one respondent even questioned this timeframe, saying that, “There are things health systems can do today. The knowledge is available and actionable. The idea of a five-year timeline for precision medicine is too long.”  The top value of establishing such a priority, cited by 100% of respondents, was in “improving patient outcomes, long-term.”  Thus, while the debate may continue in other quarters, health systems are committed to investing in an approach that they believe will improve the quality of care they deliver to their patients.

Most Systems Are Starting In Oncology, but With Any Eye Toward Expansion

As one participant put it, “Oncology is at the forefront of precision medicine.”  In addition to the detailed sub-segmentation of cancer types into histologies with distinct prognoses and best practices in care, several well-characterized biomarkers have been shown to either influence a patient’s prognosis or predict their response to specific classes of therapies, either positively or negatively.  Many of our health system partners have begun their precision medicine programs in oncology for exactly this reason.  

Thus, it is perhaps not surprising that 92% of leading health systems describe that today they “deliver precision medicine” within either oncology only (58% of total) or oncology and other service lines (34% of total).  More surprising, in fact, is the converse.  Although almost all systems have started in oncology, none are planning to stop there.  Among leading health systems that delivered in only oncology, all had plans to expand beyond oncology.  This mirrors trends we are seeing in the market, in which leading health systems are viewing precision medicine as more than an individual service line strategy, and instead are starting to develop comprehensive precision medicine programs.  Within these more comprehensive strategies, program development must still be tailored to individual disease areas, but creating a broader umbrella enables these health systems to build organizations and infrastructure designed to serve the needs of more than one service line over time.

Data-Driven Insights are Central to Enabling Precision Medicine Programs

In order to establish sustaining precision medicine programs, leaders must have detailed insight into current practice patterns, provide support for clinicians making care decisions, and monitor the impact of their programs.  The structured data that is typically available within a health system’s electronic medical record (EMR), however, is rarely sufficient to support these needs.  A complete view of the patient’s characteristics and history are required to fully contextualize the patient and provide meaningful answers to the questions that matter to program leaders. 

Thus, it is perhaps not surprising that “data management or infrastructure” was cited as a top-three pain point for LHS, as well as a top-two investment area.  Consistent with these quantitative findings, the Academy cites that, “Most health system leaders emphasize broad data collection and data management efforts as the most important factors to consider when launching an enterprise-wide precision medicine program,” and recommends that LHS, “Build robust data infrastructure with data analytics, gene profiling, and decision-support tools” as one of its Informed Practices.

Of course, this is easier said than done.  Most biomarker data in provider EMRs remains locked in PDF reports, and the information required to contextualize those results (e.g. detailed disease information, treatment information, and outcomes) is dispersed across a number of clinical sources of varying reliability, including in free-text physician’s notes.  

Additionally, in order to answer many of the questions that really matter in precision medicine, patients must be sub-segmented into extremely specific cohorts in order to provide meaningful insights.  As one Chief Clinical Transformation Officer who responded put it,  “Precision medicine starts first with acquiring data… Then create analytics around that data to be able to separate into precision cohorts. Finally, deliver insights on those analytics to develop specific care paths around that precision cohort.” Development of these precision insights requires not only high quality data, but also a sufficient level of breadth, depth, longitudinality, recency, and extensibility to provide meaningful answers to specific questions..

At Syapse, we specialize in pulling the right information together, regardless of the source, to provide answers to questions that enable the practice of precision medicine.  Which patients are getting specific types of molecular testing, and at what time in their treatment journeys? Do we have enough relevant patients to open a rare biomarker-driven trial? If so, which specific patients should we evaluate in detail for their eligibility?  Is this variant of unknown significance (VUS) likely to affect my patients’ response to this drug? How has my precision medicine program influenced care decisions and outcomes?  We answer these types of questions by not only integrating data within a health system, but also normalizing those data across health systems to create a true Learning Health Network that can leverage its combined scale to develop more meaningful patient insights.

Building a precision medicine program is a complex endeavor that requires alignment across the health system enterprise and an investment in planning that addresses both the short-term opportunities and the organization’s long-term vision. Please contact us if you are interested in learning how Syapse can help you scale your precision medicine programs using clinical, operational, and research insights from one of the largest networks of health systems. 

To learn more about the research results and the Academy’s seven Informed Practice recommendations for health systems launching an enterprise-wide precision medicine program, please download the overview here

*Brian B. Spear Margo Heath-Chiozzi Jeffrey Huff, Clinical application of pharmacogenetics. TRENDS in Molecular Medicine Vol.7 No.5 May 2001.