Behind the Buzzword: Precision Medicine
Today, we conclude our five-part Behind the Buzzword series! We’ve attempted to decode the often-confusing data analytic jargon out there today, looking at AI, Big Data, Predictive Analytics, and Machine Learning. In our last blog of the series, we explore another data analytics buzzword that’s changing the face of healthcare today.
When we get sick and go to the doctor, the doctor examines our symptoms and makes a diagnosis based on the “average patient.” This may be accurate for many of us – but not for all of us. Humans are so unique, each with differing lifestyles, biologics, and genetic histories. In healthcare’s quest to improve, they’ve found new solutions – and challenges – in data.
For example, imagine the massive data sets a hospital collects, even in one day. You’ll find your typical EHR data, including demographics, clinical orders, procedures, medications, notes, problem lists, diagnostic codes, and flowsheets. You’ll also find data from physiological vitals, Omics data, as well as waveform data from bedside monitors and ancillary devices. You can imagine the amount of information that can be collected from humans and machines alike. Ultimately, the data in healthcare is everywhere and organizations within the industry want to embrace all relevant data sources to provide better patient care.
Recognizing that every patient is unique, Precision Medicine is a medical model that utilizes advanced analytics to make customized healthcare decisions for individual patients based on their specific data. Doctors can tailor prevention methodologies and individualized medical treatments for a particular patient.
The Precision Medicine Initiative
Recognizing that this is potentially a revolutionary shift in healthcare, the White House launched the Precision Medicine Initiative (PMI) in 2015. The Initiative enables a new era of medicine through research, technologies, and policies that empower patients, researchers, and providers to work together toward the development of individualized care. PMI is arguably the ultimate big data project, linking together all the data medical researchers have been collecting for years. The projects are dominated by data collection, storage, and sharing. Analysis of this data can be used to help develop personalized cancer treatments or individualized diet plans for diabetic patients.
For example, multiple sclerosis (MS) is a chronic disease that varies greatly in how it affects individual people. The Johns Hopkins Precision Medicine Center of Excellence for Multiple Sclerosis focuses on providing targeted diagnosis and treatments to people with MS. They utilize a simple imaging test of the tissue that lines the back of the eye to identify the likelihood of rapid disease progression and may help determine the best course of treatment. This is based on collecting data from thousands of patients’ retina scans and using advanced data analytics to detect patterns.
Potential Benefits of Precision Medicine
- Improved ability to predict which treatments will work best for specific patients
- Better understanding of the underlying mechanisms by which various diseases occur
- Improved approaches to preventing, diagnosing, and treating a wide range of diseases
- Safely and security – new approaches for protecting research participants, particularly patients’ privacy and the confidentiality of their data, as well as improved oversight of tests, drugs, and other technologies to support innovation while ensuring that these products are safe and effective.
Evolving with Advanced Analytics
Precision Medicine is the opposite of today’s one-size-fits-all healthcare approach in that it is based on the “average patient.” This methodology was previously impossible without the innovative data analytics software tools and engineering that now exists. Harnessing the power of advanced analytics allows for improved decision making and is revolutionizing the healthcare industry. If your organization wants to learn more about advanced analytics, contact SWC to learn more.