Guide to examples of cloud computing in healthcare
A comprehensive collection of articles, videos and more, hand-picked by our editors
Because of the computing power, data storage, and network bandwidth that some modern analytics and simulations...
require, the healthcare industry wants more cost-effective and scalable solutions -- and cloud services offer a promising next step.
It's helpful to first define healthcare analytics as the tools, techniques and people required to reliably generate validated business and clinical insight. That definition describes both the traditional approach to analytics and the present fluid atmosphere, in which the use of clinical and business insight made possible by analytics permeates nearly every aspect of healthcare. Analytics can be used by executive leadership, and trickle down to mid-level managers and quality improvement practitioners on the front lines of patient care. Healthcare decision makers require clinical and business insight in real time and at the point of care.
The analytics that help support the information requirements of today's healthcare decision makers are quickly becoming outdated. Months-old data on static reports is no longer acceptable; clinical and business insight is increasingly based on advanced predictive algorithms that ingest large volumes of myriad types of data.
As the analytics needs of data scientists and healthcare analysts outgrow a hospital's ability to provide the software and hardware required, stealth implementations --such as rogue databases and unauthorized tools -- crop up. These approaches negate any efficiency that enterprise business intelligence (BI) and data warehouses create, and they introduce obvious security risks and support challenges.
The cloud-based solution for analytics
One option under investigation by many healthcare organizations is how cloud-based analytics can address cost and scalability concerns as part of an overall analytics solution. Healthcare organizations must consider many factors when exploring an emerging technology like cloud analytics offerings. According to a 2012 survey by Gartner Inc., the results of which still hold true, there are three main factors driving the adoption of analytics and BI in the cloud:
- Time to value: Given that IT departments are constrained by existing projects and shrinking budgets, having accessible and scalable analytics tools in the cloud may result in faster deployment of analytics solutions.
- Cost concerns: Cloud analytics are not necessarily less expensive than self-hosted options. Gartner's research indicates that cloud services "can be cheaper over the first five years, but not thereafter," and that the longer-term benefits of using the cloud manifest in other ways, such as improved cash flow and diminished IT support costs.
- Lack of available expertise: According to Gartner, prebuilt cloud analytics models can help firms that don't have someone in-house with the necessary skills to construct a custom analytics application.
Traditional approaches are outdated
Today's data comes from various non-traditional sources, and information gleaned from social media, global-positioning services, and machine-generated records is not all structured. The notion of extreme data management has put a strain on traditional data warehouse and BI systems, which are not well-suited to handle the massive volume and velocity requirements of big data applications, both economically and in terms of performance.
Likewise, a big challenge is that traditional BI is not well-suited for modern health information. EHRs contain large amounts of either structured (items selected from a drop-down list) or unstructured (text in free-form boxes) data, which can be difficult for traditional BI and data warehouses to work with. Throw in machine-to-machine and social media data and traditional analytical techniques leave healthcare organizations unable to derive maximum value from their data.
Advantages of cloud analytics
There are many advantages to including at least some component of cloud analytics in a healthcare organization's overall IT and analytics strategy. SmartData Collective lays out some of the advantages a healthcare organization can expect:
- Spend more time analyzing data: Before cloud came along, a BI or analytics installation required months of research, planning and customization. With cloud services, however, IT resources can now focus on actual problem solving and creating business insight.
- Access multiple tools: Cloud services offer the capability to access multiple kinds of tools and systems, and the cloud can pull data from other sources, including SQL databases, other public clouds, Hadoop clusters, databases, and mobile applications.
- Increase analytical flexibility: Analytics on the cloud allow analysts to perform more exhaustive research from the range of data they collect. Analytics tools are no longer constrained to proprietary systems; data scientists and analysts are now able to access tools such as Perl, Python, and others via cloud services.
Healthcare organizations need to investigate the various options, risks and benefits to determine if a cloud analytics deployment is a proper fit and an upgrade over traditional healthcare analytics software. Cloud analytics products are a viable consideration -- from a cost, efficiency and computing power perspective -- for IT directors facing increasing information demands and diminishing resources.
About the author:
Trevor Strome, M.S., PMP, leads the development of informatics and analytics tools that enable evidence-informed decision making by clinicians and healthcare leaders. His experience spans public, private and startup-phase organizations. A popular speaker, author and blogger, Strome is the founder of HealthcareAnalytics.info; his book, Healthcare Analytics for Quality and Performance Improvement, was recently published by John Wiley & Sons Inc.
Accountable care organizations invest in analytics
Use of healthcare analytics software brings HIPAA privacy concerns
Perceived security threats stops healthcare cloud in its track