Is Analytics as a Service the Future for Healthcare Data Needs?
Data has already been dubbed as the “new oil” that drives the economy in today’s digital world. With rapid digitization in the healthcare sector in terms of electronic health records, telemedicine, and imaging, big data analytics is gaining importance as means towards enhancing the quality of service. With the volume of data in healthcare expected to dramatically grow in the future for healthcare data needs, in the coming years and the shift in reimbursement models towards value-based care, there is a growing emphasis on Analytics. Analytics in healthcare supports a wide array of healthcare functions right from diagnosis, disease surveillance, follow up care, population health management to clinical decision support.
With increasing need to lay a strong foundation for analytics, healthcare organizations are moving towards software as a service (SaaS) offering provided by technology companies. While this is great for organizations who have a clear strategy and experience in the execution of analytics capabilities, most struggle. It is well known that most data analytics projects fail. According to Gartner, 60% of big data projects in 2017would not go beyond the stage of piloting and experimenting and would be abandoned eventually. One of the critical reasons why data analytics projects fail is the “expertise gap”. A Gartner survey also showed 49% of participants saying difficulty in understanding or “figuring out” an analytics toolkit as the main reason behind the project failure. Lack of in-house expertise is another critical factor that hampers outcomes in healthcare settings.
Moving over to Analytics as a Service
What is Analytics as a Service?
A comprehensive Analytics as a Service uses analytics software technology, dedicated advisor support, and other needed solutions to optimize operations and offer a competitive edge. It also provides a 360-degree view to organizations to manage processes and healthcare delivery in an intelligent way.
How is it different?
The key difference Analytics as a Service brings is in terms of dedicated expertise and skill sets of data analytics, integration, and meaningful solutions.
Key benefits of Analytics as a Service Model
- Analytics as a Service solves the challenges of poor data quality, disconnected and fragmented data, and provide mature analytics that goes beyond just data management.
- It helps to drive better outcomes with advanced analytics and the optimization of administration, finance, operations, and clinical processes. The highlight of such as service model is the availability of a dedicated advisor who can make all the difference in deriving quick, reliable, and actionable insights.
In our personal experience, small-medium healthcare organizations benefit a lot from Analytics as a Service model to solve the analytics needs rather than utilizing a Software as a Service model.