Skip to main content
Skip to footer

How Data Can Bridge the Gap Between Personalized Medicine and Care

Published on 3/16/2017

We're celebrating Women's History Month with a month-long "Women in HIT" blog series. Every week, we'll be highlighting some leading female voices in the HIT industry — both at Cerner and beyond. These experts will be taking on hot-button issues and industry trends to advance the conversation around health care. Earlier this month, Cerner's Meg Marshall tackled the economics behind America's complicated path to health care reform while Cerner's Brenna Quinn discussed how to manage change in a health care organization.

Cancer treatment strategies have always been complex and, in the coming years, that trend will continue. This is partly because the challenge of identifying the optimal treatment for a patient with cancer involves the clinical care team, as well as the patient and their family. It's also partly because new treatments are constantly being developed.

With increasing innovation in genomics, oncologists no longer treat patients based solely on tumor location. They also look at tumor biology, basing treatment on whether a tumor has certain mutations or defects. This treatment is considered within the context of the patient's individual genome. Strategies that take this data into account fall under the category of personalized medicine and will be the key to successful cancer outcomes in the future.

The link between personalized medicine and personalized care

When we think about genomics in treating cancer, we consider two aspects. First is the patient's own genome, which is in every cell in their body. In their genome, they may have mutations that make them more susceptible to a particular type of cancer than someone who doesn't have that particular type of mutation. For example, we know that individuals with specific inherited mutations in BRCA1 and BRCA2 genes are at a greater risk for breast and ovarian cancers.

The second side of genomics is the specific genetics of the tumor. Doctors look at the genetic profile of a tumor to determine if it has one or more mutations that would affect its behavior, including mutations that make it more likely to respond to a specific treatment. The appearance of a specific mutation does not mean the cancer will definitely respond to that targeted therapy, but it does mean it is more likely to.

In addition to a patient's biology and the biology of their tumor, doctors also consider the patient's personal value system to ensure the treatment strategy fits their goals and preferences. This is called personalized care.

Personalized treatment plans take into account all of these moving parts — the patient's genomic profile, the tumor's genomic profile and patient values — and merge that information with the known data from clinical trials to determine what combination of therapy and supportive care is likely to provide the best outcome for the patient.

Then and now: the evolution of personalized treatment strategies

Personalized treatment plans have always been a part of oncology. The difference between 10 years ago and now is the amount of information we have available, which enables us to make more refined decisions with the patient's individual needs in mind. Historically, patients were treated based on the original tumor site, the cancer stage and the patient's overall health and preferences.

Today, we know there is variation based on genetics in tumors arising from a single organ and that certain targeted drugs are helpful to patients with particular sub-types of cancer. For instance, a patient with HER2 overexpressed breast cancer may benefit from treatments that would not benefit a person with a breast cancer that does not overexpress HER2.

Personalized medicine allows us to get away from the "one size fits all" cancer treatment strategy, refining the diagnosis within a disease type and individualizing treatment plans.

Data makes personalized medicine possible

Data (in particular data stored in an EHR) make personalized medicine possible. Ideally, an EHR will contain clinical data — information such as diagnostic testing, genetic tests and tumor make-up — and may include information about the patient's individual values, preferences and lifestyle. The challenge is ensuring the EHR not only contains all critical patient information, but that it is organized efficiently so the oncology care team can use it to treat the patient optimally.

For example, consider a 70-year-old patient who has newly diagnosed metastatic, non-small cell lung cancer. He has had a test to find out whether his tumor has one or more mutations that make it sensitive to a specific drug and he wants to do whatever necessary to cure or control the cancer. Ideally, the clinician would look to the EHR, which contains a whole universe of information about that patient, his disease type and relevant biomarker testing to quickly find the specific information needed to select a treatment.

One of the opportunities for improvement comes in ensuring this data is accessible and comprehensive. Often, even if a hospital is on one EHR system, a patient's data is not stored in a single system. Typically, there is also medical history, test results and/or treatment history from other institutions in other systems. For this reason, interoperability among systems is crucial to obtaining a complete patient record. It's worth noting that Cerner is spearheading interoperability through several mechanisms, including CommonWell.

The future of personalized medicine and cancer treatment strategies

Personalized medicine will continue to expand with further innovation and discoveries in genomics. For example, there are ongoing clinical trials to determine whether a genetic mutation that is responsive to a treatment in one disease type is also responsive in another. As we understand more about the biology of these diseases, patient subsets are going to shrink and our treatment plans are going to become increasingly precise.

Industry initiatives are expediting the use of data for personalized medicine. For example, the National Comprehensive Cancer Network (NCCN) publishes clinical practice guidelines for treatment of 97 percent of cancers affecting patients in the United States. Multidisciplinary expert panels of surgeons, pathologists and other clinicians, as well as patient advocates, continually evaluate published data to establish whether changes are required. At Cerner, a collaboration with NCCN means embedding these guideline recommendations into oncology orders and plans to drive better patient care.

In the long term, we can expect cancer care to become more detailed, complex and patient-centered. Clinicians will increasingly have more information at their disposal, which will enable them to better personalize cancer treatment strategies. The care of the patient will become more targeted to the types of mutations that are in their tumor. To ensure the success of personalized medicine, clinicians require interoperable EHR systems that can help them manage this data in a useful and holistic way.

Do you want more HIT insights? Check out Cerner's Perspectives, a thought leadership publication.

Read more of our "Women in HIT" series:

ACA and Beyond: A Look at the Economics of American Health Care

How to Manage Change in a Health Care Organization