Healthcare organizations have humongous amounts of data at their disposal but not everyone can exploit this treasure trove of data.

The problem is not the lack of maturity of analytics technologies; almost every major healthcare provider today is leveraging analytics tools in one way or the other to glean the right insights. But constraints imposed by legacy, on-premises analytics tools come in the way of scaling and expanding analytics across surging use cases.

Read on to uncover why it’s time for healthcare organizations to move data analytics to the cloud, the challenges, and the tips and best practices an expert can help embrace.

The Benefits of Moving Data Analytics to the Cloud

In healthcare, data analytics plays a huge role in better understanding patient health and making decisions tailored to their medical needs and requirements. Analytics makes it easy for healthcare practitioners to make timely and accurate data-driven decisions. It also helps overcome skill shortages while helping doctors and physicians deliver better value for their patients.

With the healthcare environment expected to become even more complex over the next several years, traversing market dynamics, governmental regulation, and care expectations of patients will only get more difficult. As healthcare data grows, on-premises analytics tools must be more capable of scaling to expanding needs. Healthcare professionals that want to make smarter, more informed decisions and remain competitive in their communities will need to capitalize on the benefits of the cloud.

Moving data analytics to the cloud can open doors to several benefits, including:

  • Increased speed of decision-making, which, in the healthcare sector, can be the difference between life and death.
  • Improved cost savings by eliminating costly CapEx and streamlining OpEx.
  • Better collaboration between care professionals through easy, anytime, anywhere access to critical patient, medication, allergy, and research data.
  • Real-time insights into patient health that allows for accurate healthcare decisions across the care continuum.
  • Seamless scalability that allows healthcare practitioners to leverage resources on demand and improve decision-making across several use cases.
  • Better disaster recovery and business continuity as critical healthcare data is constantly backed up, secured, and encrypted.

Challenges Encountered Along the Way

Cloud analytics can help provide a more comprehensive view of a patient’s medical history to a wider group of people, allowing care providers to make more informed healthcare decisions. Yet, analytics on the cloud is becoming increasingly complex for healthcare organizations. The top challenges include:

  • The inability of IT Teams to present a strong business case for adoption across cutting-edge and innovative use cases.
  • Lack of executive funding or support from C-suite leaders.
  • A poorly defined cloud analytics roadmap.
  • Lack of an articulated data strategy.
  • Resistance to cloud adoption from key staff.
  • The seemingly long migration timeline.
  • Concerns over the security and privacy of data in the cloud.
  • Skills shortage and cloud incompetence of existing IT teams.
  • The fear of cloud sprawl can increase costs rather than limit them.
  • Making existing tools and systems cloud-ready

Tips and Best Practices

As the cloud plays a pivotal role in healthcare transformation, setting the right foot forward is extremely important. Here are some tips and best practices to keep in mind as you seek to embrace the many benefits of cloud analytics:

  • Build a cloud journey roadmap: Before you begin the migration process, build a cloud journey roadmap. This needs to be done via a thorough study of your in-house infrastructure. Such an assessment can help uncover gaps and challenges, understand requirements, and plan the next steps.
  • Procure the right cloud services: The market is full of different cloud vendors offering a plethora of cloud services. To ensure you invest in the right solutions, it is important to have a clear idea of your use cases and then procure cloud services based on your requirements and roadmap.
  • Craft the right architecture: If you want to make the most of healthcare analytics in the cloud, you need to craft the right architecture. Combine the expertise of your in-house IT team with skilled third-party resources to build an optimal solution.
  • Enable cloud data engineering: Once the architecture is in place, you need to design, code, and test your analytics applications carefully. You must also focus on maintaining the analytics infrastructure and systems required for cloud computing.
  • Ensure post-deployment support: Once the cloud analytics solution is deployed, it is also important to monitor it. Continuous monitoring can help in detecting performance or user experience issues while also uncovering areas for improvement/optimization.

The Role of an Expert Like Emergys

In the healthcare industry, cloud analytics goes a long way in improving patient analysis. At Emergys, we help healthcare organizations achieve their business goals using the best cloud technologies. Our team of talented professionals comprises cloud architects, administrators, and engineers working around the clock to craft solutions that best meet unique use cases.

With us as your Managed Services Partner, you can get access to skills across different cloud providers. We can help you efficiently set up and manage your cloud infrastructure while allowing you to minimize your TCO through best-practice implementation. We can also help you keep up with evolving cloud trends and developments.

Contact us today and enjoy a seamless experience as you embark on your cloud analytics implementation journey.

Emergys Blog

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