Recently, I read some articles showcasing technology hype versus what organizations really need. While all sectors suffer from an overload of hype, healthcare’s complexity means it gets hit particularly hard.
For example, there’s a crescendo of noise surrounding Artificial Intelligence (AI) right now. One thing that often gets left out is an age-old maxim: garbage in, garbage out. If you want good results from AI, you need a solid data strategy and enterprise data layer. The more data – good data – that we can feed into the AI algorithms, the more useful they will become. That means we need accurate, harmonized data from all data sources across the continuum of care, including EHR data, machine data, and user-generated data.
This article synopsizes a recent ONC Report on the impact AI will have on healthcare. While recognizing some early AI successes, it also explores future challenges faced by organizations that want to realize its benefits. One significant danger: Putting AI projects in silos rather than looking at multiple AI projects holistically. (We’ve seen this happen before with population health and care management.) In an environment with multiple vendors, use cases, and requirements, it’s important to provide data that’s as consistent as possible across many different scenarios.
Another recent article is entitled, “Is the Traditional Data Warehouse Dead?” It’s a response to the hype that “big data” is the answer to data challenges a healthcare organization faces.
While big data technologies offer many benefits and should be part of your overall data strategy, they’re not a strategy in and of themselves. Healthcare data needs lots of cleansing, mastering, harmonizing, and grouping to be useful – which is why people built data warehouses in the first place – and dumping data into a data lake ignores all of those requirements.
These challenges are getting more recognition all the time. The keynote at this year’s HIMSS from Google’s Eric Schmidt was about the need for a data layer outside of the EHR to drive healthcare into the future.
So, if you need a data strategy that may include a data warehouse, a data lake, and data marts, what choice do you have besides building your own from scratch?
At Information Builders we have been working over the last five years with healthcare providers and payers to create a complete data management platform dedicated to healthcare requirements: Omni-HealthData. We build it with leading healthcare providers and payers – not in a lab. Our provider partner, St. Luke’s University Health Network, received a comprehensive set of quality dashboards in under four months and over forty analytical applications in eighteen months.
Omni-HealthData helps you accelerate your ability to transform data into information, while also future-proofing your organization with a data layer that will support the coming wave of AI, IOT, changing payment models, and increased consumerization of healthcare.
When you’re looking at the hype that surrounds the healthcare industry, remember that data and analytics is always a significant part of bringing any of it to reality. Omni-HealthData can help.