Cut Through the Confusion: The 5 Types of Healthcare Analytics Solutions

healthcare analytics solutions Organizations across the United States are looking to healthcare analytics solutions to help them comply with CMS’s cost-cutting and reporting requirements. This is because analytics offers a way to tap into the valuable insights locked deep within the vast stores of an organization’s data.

But reaching the point where a health system can significantly bend the cost curve requires more than a quick purchase and installation of yet another piece of software. Instead, it could take 10 to 15 years for the health system to implement a comprehensive analytics solution. This lengthy time frame is necessary because of healthcare data’s unique challenges: there’s a lot of data from many different source systems that needs to be brought into the analysis system to establish a single source of truth. Such a large implementation simply can’t occur overnight.

Because of the long-term nature of completing a robust analytics initiative, it’s important for health systems to carefully choose their future partner, especially when there are several types of vendors, each with pros and cons.

5 Analytics Options

How does a health system know which analytics solution will serve them best and provide an optimal return on investment (ROI) — now and in the future? First, it helps to understand the five options available in today’s marketplace. Then, by understanding each solution’s advantages and disadvantages, health systems can make the choice that best fits their needs.

Option 1: Buy from a Large Non-Healthcare-Specific Technology Vendor

IBM and Oracle fall in the large non-healthcare-specific technology vendor category. These organizations have extensive data warehouse expertise across many industries.

One of the greatest strengths in choosing to partner with one of these large vendors is the health system will likely be expanding on a relationship that already exists. For example, the vendor may have helped the health system establish their infrastructure, and through this work, they already know the health system.

Another strength is the vendor’s ability to leverage the investments they’ve made in technology for their own success. For example, IBM has performed a great deal of work in the areas of Big Data and supercomputing. While neither discipline is healthcare-specific, the knowledge they’ve gained from investing in these fields can be applied to other organizations that purchase their products.

When planning a lengthy journey with a partner, it’s important to consider whether or not they will have the staying power to be there through the end of your needs. There is little doubt that companies such as these will still be viable for the next few decades.

Yet these companies’ greatest strength — their breadth of experience across many industries — is also their greatest potential weakness. Their data warehouses are not tailored for the specific needs of healthcare. This is an important consideration because the data warehouse architecture that has been effective for other industries, such as manufacturing and retail, isn’t appropriate for healthcare’s unique needs.

Healthcare data is unique because of the huge number of constantly changing variables — even between patients with similar conditions. All of the data elements (age, weight, vital signs, family status, comorbidities, the science of how to treat a particular condition, etc.) require adjustments at a faster pace than industries with static data. Such volatility requires a flexible data warehouse architecture.

Another aspect to consider is how committed the vendor is to designing analytics solutions that are specific to the healthcare industry. While some technology organizations move to a market and remain committed to providing long-term solutions, others have a history of swinging their interests back and forth between a horizontal market and a vertical market. For example, when the vendor is focused on providing solutions for a vertical market, they spend more time and energy customizing their products for particular industries. But then they’ll shift their focus to standardizing those solutions for a larger business sector when they move to a horizontal goal.

Changing priorities for different markets often helps companies drive excellence within their own organization, but it can be problematic for their partners if the focus changes in year four of a 10-year plan. It doesn’t mean a large non-healthcare-specific technology vendor should be dismissed as an option, but the potential waxing and waning of commitment level should be factored into the decision.

Option 2: Buy from a Hosted Analytics Service Provider

Some health systems choose to outsource all of their analytics work to service providers like Humedica or Explorys. This approach is best suited for health systems that want to avoid setting up an analytics or data management system but still aspire to improve basic internal and external reporting.

There are several advantages to buying from a hosted analytics provider. The health system won’t need to invest in hardware or software, nor will they need to develop in-house expertise in analytics processes. Hosted analytics service providers also offer comparative analytics and benchmarking with other healthcare organizations.

So, what are the limitations of this model? Hosted analytics service providers only offer basic reporting capabilities, not adaptable solutions that can be tailored to fit the health system’s specific needs. By choosing this option, health systems will only be able to reach Level 3 or Level 4 of the Analytics Adoption Model. In addition, substantive ROI of this approach is neither well documented nor widely acknowledged.

Analytics Adoption Model

Healthcare analytics adoption modelThe eight levels of the Analytics Adoption Model provide a framework for health systems to understand and leverage the capabilities of analytics.

Option 3: Buy from Single-Solution Analytics Applications from Developers

Another option for healthcare organizations is to adopt single-solution applications like Crimson, Midas, or Medventive to target specific analytic opportunities.

The advantage of choosing a single solution analytics application is the developers generally have deep expertise in a particular area, such as supply costs, risk management, physician productivity, etc. Using these types of specialized applications can help advance a health system’s knowledge of a specific area. The affordability factor of a single solution may also have appeal.

Despite the advantages of a single-solution analytics application, their functionality is limited. This is because such applications are unable to provide analyses for the more complex, multifaceted problems health systems face, such as determining how the size of staffing and patient loads affects the hospital’s supply consumption. Also, a collection of single-solution applications does not facilitate data integration.

To be successful in driving organization-wide change — the type required to become an accountable care organization (ACO), take on more risk, and manage population health — dozens or maybe a hundred or more of these applications are necessary, a costly and complicated solution. With this option, the CIO is now responsible for managing dozens or hundreds of analytics applications. Plus, these applications still need to have data fed to them, which means building some form of data warehouse.

Option 4: Buy from Your EMR Vendor

Since providers and health systems have already invested heavily in their electronic medical records (EMR) system, many look to their EMR vendor for analytics capabilities. Major EMR vendors, such as Epic, Cerner, and McKesson, all offer EMR solutions.

This approach offers the possibility of “closed loop analytics” — driving analytics back to the point of care in the EMR and clinical workflow. EMRs also have domain expertise in healthcare and a very strong commitment to the industry.

Because of the significant investment health systems have already made to purchase an EMR, the EMR vendors will often make their clinical analytics applications available for a very small, incremental cost. At a time when healthcare IT departments are already considerably challenged to implement mandated technologies, the ability to add analytics through the EMR vendor is appealing.

There is, however, a tradeoff to using an EMR as a healthcare analytics solution. EMRs are designed to capture and process large amounts of data, not to analyze or make sense of it. Understanding trends and patterns, and using the insight to drive clinical improvements, requires more depth than an EMR’s analytics application can provide.

Even if an EMR does include an analytics solution, leadership won’t be able to understand what needs to change or how to make those changes. Change management is necessary to drive new workflows through the organization — especially when the organization is asking a physician to change the way he or she prefers to work. Change management has generally not been a strength of EMR vendors in the past.

Then there’s the challenge of heterogeneous environments. EMR analytics applications tend to work best when they are drawing data from within their own systems. But with consolidation occurring between healthcare providers, there are many situations where two, three, or more types of EMRs are being used within the same organization. Often the EMR vendors will do a good job of bringing their own data into the data warehouse, but will find it difficult to consume the data in systems from other vendors.

One other consideration is how tightly you want to tie your operation to a single vendor. The EMR is already a significant investment. Using that same vendor to provide an analytics solution creates a dependency on a single player.

If a health system is just testing the waters with clinical analytics, the EMR vendor’s applications aren’t a bad place to start. However, there is no proven track record with analytics to date from the EMR vendors. In fact, the track record is abysmal because these applications tend to be focused on analytics that are specific to the EMR vendor’s data versus an integrated view of clinical, financial, patient satisfaction, and administrative data. In addition, 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 Analytics Adoption Model.

Option 5: Buy and Build an Analytics Solution from a Healthcare-Specific Enterprise Data Warehouse Vendor

The final option is to buy and build from a healthcare-specific enterprise data warehouse (EDW) vendor. These vendors offer solutions with the highest degree of analytic flexibility and adaptability, up to Level 8 of the Adoption Model.

Healthcare-specific EDW vendors also have in-depth knowledge of healthcare (which means their solutions are geared specifically toward those rapidly-changing needs). And they understand how to leverage their expertise in building EDWs to incorporate data from many different systems to make it available to all of the various analytics applications. In addition, companies such as Health Catalyst and Health Care DataWorks (HCD) are fully committed to healthcare, so their focus won’t move elsewhere if the market shifts. 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, though, a healthcare organization must have a data-driven culture with high aspirations that views analytics as a clear business differentiator. The organization’s culture should also have a commitment to a higher degree of data literacy and data management skills.

Most healthcare-specific EDW vendors have been plagued by a slow initial time to value and typically can’t demonstrate ROI for at least two years. But at Health Catalyst, we structure our implementation and pricing to demonstrate an ROI in three-month increments. This means that health systems are able to recognize an ROI from different phases of implementation before committing further investment in the solution.

Since organizations like Health Catalyst haven’t been around as long as the top technology companies, though, there’s no guarantee they’ll still be here in 20 years. That’s why it’s important to consider other attributes of the vendor, such as the strength of their business models, their momentum, and the successes of their early customers.

Choosing a partner in this category also means adding another relationship to manage. You must decide whether the benefits are worth the cost.

Many Options for Healthcare Analytics Solutions

No single analytics solution is right for every healthcare organization. But there’s good news: there are several options to choose from. The key is to determine which vendor best fits your organization’s clinical analytics needs, not just now but for the long term. A lot can change in 10 to 15 years, especially in healthcare, so be sure whatever solution you choose has the flexibility to make adjustments in the future too.

Planning on a lengthy journey is important. Most organizations typically work with data from 30 to 40 different source systems from across the enterprise that must be consolidated into a single source of truth, which is time-intensive, resource-intensive, and expensive. Managing this system-wide, function-wide, department-wide data requires the strong data foundation a healthcare-specific EDW provides.

Are you struggling to identify which analytics solution is right for your healthcare organization? If so, what are your main concerns? I’d love to hear from you.

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