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Future of Data Scientists in Healthcare

To understand how data scientists impact the healthcare industry, it is important to know more about the position and what it entails.

As the healthcare industry evolves and adapts to a customer-centric model, there has been a push toward digital transformation, which paves the way for technology and business integration to help deliver better patient care at a lower cost.

The healthcare industry faces many challenges on the path to digital transformation. These challenges can negatively affects customers, vendors, partner enterprises and other healthcare departments.

Obstacles include increasing costs, reductions in reimbursements, lack of efficiency in many systems, high levels of fraud and abuse, unnecessary waste, payment model changes and aging healthcare populations, just to name a few. When striving for digital transformation, each of these difficulties can be addressed through a more efficient use of data.

Data, commonly referred to as "big data," is abundantly available in our healthcare industry. The challenge is sifting through that data to find and correlate elements which can fuel improvements in the healthcare system, in patient populations and address the challenges mentioned above. To gain value from this unlimited data, healthcare entities must have someone in place who can provide analysis and understands how to use data to increase efficiency and solve problems. Data scientists are exactly the people for the job.

data scientists informatics Data Scientists 101

To understand how data scientists impact the healthcare industry, it is important to know more about the position and what it entails.

The term "data scientist" is relatively new and describes an individual with the knowledge and skills to bridge the gap between raw data and the resulting analysis. Data scientists can either work individually or with teams of analysts to decipher data and recommend data-derived strategies.

The outlook for data scientists is on the rise, particularly within the healthcare industry, which is currently adapting to technology and realizing the positive outcomes of data integration.

However, while the demand for this position grows, the supply of qualified individuals is lacking. This is partly due to a lack of awareness from those entering the job market, as well as declining interest in related fields like math and science.

SEE ALSO: New Health Informatics Credential

There is also a misconception by many who think such positions require technical education, like writing code or pursuing a medical degree, which can turn qualified individuals away.

While these misconceptions may hold true for some, the undeniable fact is demand for data scientists will continue to grow because the human element behind data is essential for interpretation and execution.

Data Scientists' Role in Healthcare

The role of data scientists in the healthcare industry is to provide data-driven analysis leading to recommendations that can help maximize operational efficiency and improve patient care.

This sounds straightforward, but given the budding frontier of big data and connected devices, this is not a simple task. Data scientists work in a linear fashion, beginning by collecting information, sifting through relevant data, analyzing the collective facts and providing actionable measures and recommendations.

This process uses "data harvesting," the act of collecting large amounts of data, to establish a baseline of information on a particular topic or issue. Once the data is collected, relevant information is established, and analysis and correlation are accomplished so the scientists can make recommendations to help solve an issue or measure efficiency.

An example of this process is a hospital that works with geriatric patients and is looking for ways to improve care while controlling costs. Data available to the hospital includes patient health records, patient lifestyle information and available support systems, living arrangements and real-time data from wearable devices, to name a few. A data scientist is able to take this information, distill it and provide analysis to create tailored health plans or recommend care management plans. This could possibly even demonstrate the statistical probability of falling injuries.

Benefits of Data Scientists

Data scientists decode business needs using everyday information, delivering benefits to the entire healthcare industry, ranging from patients to suppliers.

As I mentioned, the healthcare industry has operated as a series of silos where patients move through the system from silo to silo while information about that patient has been very difficult to share efficiently. We are now entering a time where regulations and incentives are aligned to force the efficient sharing of that information. Data scientists can take this data and provide recommendations that will reduce waste, decrease costs and provide better integration for communication between healthcare providers and suppliers.

Predictive analytics, which is information used to foresee future outcomes through data patterns, is a factor that can impact patients and providers alike. Data scientists use predictive analytics to tailor treatment plans for individuals, lower supply costs between providers and vendors, and even forecast the influx of patients during seasonal illnesses. These are just a few examples within the realm of possibilities for data scientists, and many of the potential benefits are based on current technology and available data sets.

data analytics doctor future Doctor Visit of Tomorrow

Imagine a visit to the doctor's office for an unexplainable illness. Traditionally, a patient would update their files in the waiting room, follow a nurse to take vital measurements, then meet with a doctor to briefly explain the symptoms or run a few tests. The doctor will provide a recommendation based on the patient's symptoms, experience and intuition, but if it does not work, the doctor will try another solution during a return visit.

Now imagine going to the same doctor, only this time the patient's personal data has been analyzed by a data scientist.

Upon entering the doctor's office and signing in, all necessary information is up to date because the healthcare provider has the relevant details from the insurance provider. Then the patient follows the nurse straight to the examination room because his or her vitals are tracked through mobile devices and wearables. Once the doctor comes to discuss the illness, he or she has access to an entire database of patient information ranging from family medical visits to the data tracked through mobile apps, like calorie logs and movement trackers.

The doctor will also have access to the entire patient database to compare symptoms and diseases to other unique situations, which enables a more complete view when prescribing treatment or medication. Care management, following the visit, can be supported with telehealth visits, wearable device monitoring and devices such as 'smart' prescription bottles, which can help to manage patient compliance to the care plan. 

Data Scientist Decision

The concept of having information centrally located is ideal for both businesses and individuals, especially within the healthcare industry, to drive efficiency in the system and manage costs. Data scientists play a key role in centralizing data and analyzing it for practical uses, passing the benefits along to patients, partners, vendors and other entities involved in the process.

As a healthcare practice or provider, I am sure you are looking at ways to securely collect, manage and analyze data to help improve patient care and control costs. Depending on the volume and types of data you have available, you will need a comprehensive data management program and the professional support of a data scientist or an entire data scientist team to help accomplish your goals.

Ralph Burns is president of Healthcare and Life Sciences Services at NTT DATA, Inc.


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Very insightful post - thank you, Ralph. The good thing about the emerging Data Science field is "most of the underlying techniques can be applied to solve problems in any field - healthcare, finance, cybersecurity, e-commerce, etc.". Data Scientists + SMEs (with Big Data/Cloud Technologies) = Solution to Billion (even Trillion) $ problems.

Nasir Uddin, Ph.D.,  Chief Data ScientistOctober 05, 2016




     

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