Posted November 2, 2017 by admin in articles
 
 

Top 5 Challenges of Big Data Analytics to Healthcare

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Exclusive article by Lindsey Patterson at EMRIndustry.com

 

Big data has proved to be one of the most disruptive technologies to after mobile technology and the internet. Every business wants to use big data to improve services, irrespective of the industry or where it’s based in the world. All business leaders know is that to have any chances of success, they have to collect lots of data from various internal as well as external sources, analyse the data, discover patterns, and then use their findings to improve delivery.

 

Big Data in Healthcare

The healthcare industry hasn’t been left behind in the big data craze. Healthcare facilities across the world have put data into their electronic health records (EHR) and are actually pulling actionable insight from these records. Findings made are applied to different initiatives with the goal of improving services and at the same time, increase profitability.

 

But the introduction of big data technology in healthcare hasn’t been without its fair share of challenges. In fact, big data analytics has turned out to be the most challenging endeavour the healthcare industry has sought to take on in recent history. Here are the top challenges an organization is likely to face in an attempt to boot up a big data analytics program in its quest to achieving a set of data-driven financial and clinical objectives.

 

Data Sharing

As the healthcare industry attempts to shift towards value-based care and population health management, the ability to share data with external partners is necessary. Very few persons receive their healthcare needs at a single facility and similarly, very few healthcare providers operate in a vacuum. The challenge is that there are fundamental differences in the design and implementation of ECR systems.

 

Interoperability

With the barriers that currently exist in data sharing, clinicians are often left without adequate data they need to follow up with the patient, make key decisions, and come up with strategies to improve service delivery. Interoperability is needed if changes are to happen in the healthcare industry. The movement data between disparate organizations needs to be made possible, easy and secure.

 

Updates

Health information needs to be up to date at all times. The data needs to remain current and relevant at all times. Therefore, most elements will require frequent updates. It’d be easier if we were dealing with static data here, but healthcare data is not static.

 

Some datasets such as marital status and home address change a limited number of times in a person’s life. Some other types of information need to be updated several times in a day. Such information may include a patient’s vital signs and related data.

 

Analytics

The ability to capture, analyse, and draw patterns from big data is becoming quite a challenge in the healthcare industry. Using Hadoop tools as a solution to the data infrastructure challenges in the healthcare industry can go a long way towards improved patient care. Implementing Hadoop solutions in healthcare data infrastructure helps store and analyse EHR data and improve patient care.

 

Security

When it comes to any type of confidential data, taking measures to ensure data security is essential. Healthcare data is vulnerable to an almost infinite array of security threats. These threats range from malware phishing attacks to ransomware episodes, hackings, and high-profile breaches. Data security should be prioritized in all healthcare facilities across the world.

 

Other common challenges in big data analytics for healthcare are in areas such as data visualization, querying, reporting, stewardship, and storage. Healthcare providers need to find ways to overcome these challenges if a stable big data exchange ecosystem is to be developed. Such system would see a meaningful, timely, and trustworthy connection between all members of the care continuum.



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