2 Trends and 2 Challenges with Modern Healthcare Analytics

Coming out of the HIMSS Annual conference, healthcare analytics was everywhere. While we’ve certainly seen a maturing of the healthcare analytics space, I still see a lot of organizations that are trying to figure out the right strategy for their healthcare organization. Looking at the modern healthcare analytics space, I’m seeing a couple of high-level trends and challenges.

Two Major Healthcare Analytics Trends: Cloud and Real-Time Analytics
The two biggest trends I see in healthcare analytics is the move to the cloud and the need for real-time analytics. When it comes to the cloud, the costs of storing, processing, and evaluating healthcare data across multiple systems just makes sense in the cloud. Cloud analytics easily scales to your processing and data storage needs when and where you need it. This flexibility helps organizations lower costs and avoids having expensive, high powered machines and large data arrays sitting there idle.

Along with cloud analytics making sense from a cost perspective, many healthcare organizations are using the cloud to enable innovation in their organization. The ability to easily roll out a new cloud analytics instance for someone in your organization often turns what would have been a denied request into an easily facilitated new analytics project. Modern healthcare analytics is about enabling your users to discover new insights instead of restricting the effort to a small group of data science experts.

The 2nd major trend I see in healthcare analytics is the move to real-time analytics. We’ve seen this coming for a while now, but the reality of real-time health data sharing is here. What used to be nightly, became twice a day which became hourly and is now near real-time updating of healthcare data.

This is a subtle, but powerful change for healthcare. While there has been plenty of value in retrospectively looking at healthcare data, the most valuable innovations in healthcare analytics require real-time analysis of the data which impacts the patient at the point of care. In many healthcare cases, you have to address the issue in real-time if you want to effectively address the problem. This is particularly true as you use real-time data to do predictive analytics on a patient.

Two Challenges with Healthcare Analytics: Security and Trusted Data
We all know that security is top of mind for most healthcare IT professionals. Protecting a patient’s protected health information (PHI) is of utmost importance. The real question is can you do real-time sharing of health data in a secure way that protects patient data? My answer to this is that you can, but the key is putting a secure process in place to maintain the security of that data. The more important question when it comes to security is whether you have the in house talent that can secure your healthcare analytics infrastructure or whether you need to lean on outside expertise to ensure your data is protected and secured. I most commonly see a mix of the two. In house expertise that holds your third party service providers accountable.

The second major healthcare analytics challenge is ensuring that the data is trusted. This is a task that’s much easier said than done. However, I’ve found two ways to help improve trust in your data. The first is to enable real-time updating of the data. It only takes one time for a clinician to see an outdated piece of data to wonder if all the data in the system is wrong. Having real-time data provides the most trust in that data.

The other way to improve trust in your data is to make sure that data available and visible to your organization. There is a domino effect that occurs when you expose data to clinicians who understand the data. First, they can point out where the data is wrong and needs corrections. Second, they can see first hand how their mistakes entering the data will impact them downstream. This often results in improved input of data in the first place.

What’s clear to me talking to healthcare organizations is that healthcare analytics is in all of their futures. The real question is how to do analytics effectively. If you want to learn more about some of the trends and challenges mentioned above, sign up for this FREE webinar hosted by Snowflake Computing and Microsoft. In this webinar, Chad Dotzenrod and Todd Crosslin will share how secure data sharing for healthcare analytics is possible today. They’ll also share how real-time analytics can happen in your organization in a secure way while leaving much of the data in place. Sign Up now to learn about Secure Data Sharing for Modern Healthcare Analytics.

Snowflake Computing is a sponsor of Healthcare Scene.

About the author

John Lynn

John Lynn

John Lynn is the Founder of the HealthcareScene.com, a network of leading Healthcare IT resources. The flagship blog, Healthcare IT Today, contains over 13,000 articles with over half of the articles written by John. These EMR and Healthcare IT related articles have been viewed over 20 million times.

John manages Healthcare IT Central, the leading career Health IT job board. He also organizes the first of its kind conference and community focused on healthcare marketing, Healthcare and IT Marketing Conference, and a healthcare IT conference, EXPO.health, focused on practical healthcare IT innovation. John is an advisor to multiple healthcare IT companies. John is highly involved in social media, and in addition to his blogs can be found on Twitter: @techguy.

2 Comments

  • Healthcare analytics, big data, etc. are often big-ticket investments as well. Providers would do well to ensure that their data is as clean as possible to avoid diluting these investments. The RightPatient platform helps to prevent data corruption by ensuring accurate patient identification. It also improves security and interoperability, which are indeed increasingly important with the recent rule changes and continued shift toward democratizing healthcare data.

  • Great comment Michael. Having an effective EMPI and ensuring appropriate identity management that works across systems is extremely important as well.

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