4 Options for Choosing the Best Healthcare Analytics Solutions (Executive Report)


Analytics is a buzzword in healthcare today. You hear it often: “What does an organization need to succeed in a value-based care environment? Robust analytics.”

But what exactly does that mean? Anyone who has looked into implementing “analytics” for their organization knows that a multitude of options for healthcare analytics are available—and each vendor touts its approach to analytics as the best.

I’d like to take a moment here to summarize four primary analytics options available to healthcare organizations today. While doing so, I’ll not only highlight the options for healthcare analytics but also the pros and cons of each.


Some health systems choose to outsource all of their analytics work to analytics service providers like Humedica or Explorys. This approach is best suited for organizational cultures that want to avoid the details of healthcare analytics and data management but still aspire to improve basic internal and external reporting. This approach doesn’t require any investment in hardware or software, nor does it require developing in-house expertise in analytics processes. Another advantage is that it offers comparative analytics and benchmarking with other healthcare organizations. Inter-organizational benchmarking and comparative analytics is a major part of the business model and service provided by the vendors in this space.

So what are the limitations of this model? Organizations adopting this type of service are very limited in terms of the kinds of analytics they can perform. The analytics in this option are targeted at either Level 3 or Level 4 of the Analytic Adoption Model below. They are locked in to the basic reporting capabilities offered by the vendor and are unable to adapt the functionality to meet their specific needs. In addition, substantive return on investment of this approach is neither well documented nor widely acknowledged.




Another option for healthcare organizations is to adopt best-of-breed point solutions like Crimson, Midas and Medventive to target specific analytic opportunities. These very specific analytics applications can be advantageous because they leverage targeted expertise in business and clinical areas that are not always available in other options. However, the very specificity of such applications is also the disadvantage of this approach. The applications may provide detailed analytics for a specific domain, but they don’t provide a single healthcare analytic perspective on patient care and costs. Also, a collection of point solutions does not facilitate data integration. And having a wide variety of solutions is costly and complicated to maintain.


Since providers have already invested heavily in their EMR, many look to their EMR vendor for analytics capabilities. This approach offers the possibility of “closed loop analytics”—driving analytics back to the point of care in the EMR and clinical workflow. However, there is no proven track record with analytics to date from the EMR vendors. In fact, the track record is abysmal. This approach tends to be very focused on analytics that are specific to the EMR vendor’s data versus an integrated view of clinical, financial, patient satisfaction, and administrative data. They are much less flexible and adaptable to new sources of data and analytic use cases, especially complex use cases at Level 6, 7, and 8 of the Analytic Adoption Model.


The final of my options for healthcare analytics—and the one that I recommend after years of working in data warehousing— is to buy and build from an analytics platform vendor. These solutions offer the highest degree of analytic flexibility and adaptability, up to Level 8 of the Adoption Model. By implementing and owning a healthcare Enterprise Data Warehouse (EDW), an organization creates a foundation on which to run analytics applications and drive an analytics strategy for years to come.

For this approach to be successful, a healthcare organization must have a data-driven culture with high aspirations that views analytics as a clear business differentiator. The approach is also best suited for a culture with a commitment to a higher degree of data literacy and data management skills throughout the organization.

Most vendors in this space have been plagued by a slow initial time to value. Because of this, the approach’s ROI track record is inconsistent—sometimes very high, sometimes negative. Across all industries, the average ROI from successful EDW projects is 431%. It is not consistently that high in healthcare yet because the field is emerging as a specialty.

Health Catalyst is an analytics platform vendor that has found a way to create quick time to value for our clients. Unlike other platform vendors, who typically aren’t able to demonstrate ROI for at least two years, we structure our implementation and pricing to demonstrate ROI in three-month increments. This means that clients are able to recognize the ROI from different phases of implementation before committing further investment in the solution. You can learn more about this approach.

You can also download a slide that summarizes these four options, so you can use it and modify it as you gather and present your own strategic options.

strategy and analytics options