Healthcare News & Insights

3 tools are making health care more personal

The time is now for the healthcare industry to embrace personalized health care and all of its benefits. How? In this guest post, Marc Helberg, managing VP at a consulting firm driven to create innovative, growth-oriented and people-first solutions, reveals three tools that are already helping make personalization a reality.

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The aggregation of consumer data taught businesses no two consumers are alike. In response, businesses have learned to personalize their products and marketing efforts to address their customers’ unique needs and preferences. No two patients are alike, either, which is why personalization in medicine and treatment has become just as important to modern healthcare experiences and overall outcomes.

For example, precision medicine – a specific type of personalized health care – involves the use of a patient’s genetic profile to customize disease treatment plans. Pharmacogenomics (the study of how genes affect pharmaceutical treatments) has proven successful in more than 100 clinical trials, and more are already underway. Oncologists can now use genetics and genomics to design cancer therapies guided by specific tumor markers.

In a broader sense, however, personalized health care is about more than just diagnoses and treatments. It also includes utilizing vast amounts of data to predict health risks or determine how a patient will respond to a certain wellness plan, offering a picture of a patient’s well-being more holistically than ever before.

Why the push for personalization?

When personalization took over most other business models, it wasn’t a necessity at first. Previous ones were fine; they just needed to catch up to the technology of the times. In the healthcare field, however, personalization is a necessity.

Consider this: Before the Patient Protection and Affordable Care Act of 2012, healthcare expenditures in the United States grew at a rate of 6.1% each year. That was twice the rate of the country’s entire gross domestic product growth, which hovered around 3%, and it cost the average U.S. family almost as much as housing. This brought about the shift to a value-based system centered on reducing costs by improving the paradigm of patient care.

Personalization is the engine driving that paradigm shift. The use of digital records led to the age of medical data aggregation, which in turn has led to the use of advanced technology to collect even more data. With artificial intelligence (AI) and machine learning systems, Internet of Things-connected devices, and wearable technology, providers now have access to unprecedented levels of information about their patients’ health histories.

They also have access to databases full of information about similar medical cases around the world. With a few targeted search queries, healthcare providers can find every reputable record of patients with similar histories who have shown similar symptoms. By comparing their patients’ conditions with related cases in the worldwide database, providers can use evidence-based medicine rather than guesswork to design appropriate treatment plans.

I’ve gotten to see this as a patient: I recently had data about my own medical care shared between two different healthcare groups for the first time, giving both parties a closer, more personalized understanding of my case. While my ultimate treatment plan may have been the same, everyone was informed, there was no need for follow-up calls or consultations, and my treatment plan was created with no delay. That’s a big step, and for it to be implemented on a broad, industrywide scale would be even bigger.

3 Tools currently creating change

Making this change will take movement from both providers and the organizations looking to advance healthcare tools. The healthcare industry isn’t always as quick as other industries when adopting new technology, but now the medical tech revolution is well underway, personalized health care is quickly becoming the new industry standard. These three tools are already helping make personalization a reality for health care as a whole:

  1. Data collection and integration platforms: To improve data analysis and patient care coordination, providers must establish a base of information against which they can assess and evaluate new data. This requires a data collection and integration platform that allows providers to access data as well as contribute new information from their own patients’ cases.
    For instance, a company we’ve partnered with has a “patients like mine” system that takes a closer, more granular look at individuals’ genomic makeup to more accurately assess treatment options for cancer patients. It takes treatment plans from an exercise in trial and error to a more scientific, thoughtful approach.
  2. Automated risk assessment tools: With such a wealth of data at their fingertips, healthcare organizations are making the most of it in several ways, and automated risk assessment is one of the most important. AI and machine learning programs curate and analyze the data in a healthcare database to provide comprehensive risk assessments based on history, lifestyle choices, demographics and the outcomes of patients with similar profiles.
    This is especially important because the chronic illnesses that contribute most to inflated healthcare costs are usually highly preventable. In the old framework, they simply weren’t well-managed. Chronic conditions like obesity, hypertension, diabetes and cancer are now being more successfully managed thanks to advanced risk assessment capabilities.
  3. Wearable sensors and smart devices: The ability to collect and analyze data requires patient engagement, and wearable medical devices are one of the most effective ways to promote it. Products like Apple Watch and Fitbit not only make data collection easy, but they’re also popular enough that patients actually want to wear them.
    More importantly, these wearables are as effective at boosting prevention and outcomes as they are at collecting health data. In a study sponsored by the U.S. Department of Veterans Affairs, researchers used wearable biosensors and AI-based physiology analytics to observe 100 heart failure patients in four different VA hospitals. IoT-connected smartphones allowed participants to continuously and remotely transmit their biosensor data in real time.

As technology becomes more advanced every day, providers can look much more deeply at each patient’s profile – and that’s a good thing. Patients will receive care that’s better suited for them, specifically, than we’ve ever experienced in human history. But in order to reap those benefits on a widespread scale, providers need to take the plunge and begin investing in tools and services that will further their personalization efforts.

Marc Helberg is the managing VP at the Philadelphia office of Pariveda Solutions, a consulting firm driven to create innovative, growth-oriented and people-first solutions.

 

 

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