Editor’s Note: Nora Lissy, RN, BSN, MBA is the Director of Healthcare Information at Dimensional Insight
Analytics plays an important role for many healthcare organizations, from reducing operational costs, optimizing IT systems and infrastructure, and helping clinicians make the best decisions for their patients.
Though, for many in the healthcare industry, the problem is that managing a successful analytics program can easily become overwhelming. For starters, analytics either requires a disproportionate amount of hours or materials, which in some instances can increase the possibility that something will be done wrong. In addition, organizations might be using the completely wrong tools, while others may have the right tools but are using them the wrong way. Overall, gaining actionable insights in healthcare is harder than it may seem given the industry is unique and complex. These are just some of the reasons why so many analytics programs fall short.
However, while healthcare analytics may be complex, there are ways to make using analytics easier. By taking into account a few key factors, organizations will be able to attain the right insight to move the needle on outcomes. So, whether you are an executive at a healthcare organization, a clinician, or a provider, you should be aware of the common pitfalls of analytics and how to successfully leverage these types of tools to avoid any missteps.
Here are the three cornerstones for success with healthcare analytics.
1. Define Clear Business Rules
Defining clear business rules is the first step to analytics success. Without setting correct business rules, an analytics solution is worthless. Whether it has to do with industry definitions that your organization does not currently use, or definitions that are inconsistent across your organization’s various departments (such as operational vs. financial measures), the technology is only as good as what you put into it.
For example, the definition of readmission can vary across the organization – because of this, it’s important that you define clear business rules so you can avoid conflicting or inaccurate data. Additionally, if the business rules are inconsistent, the data being used won’t be good enough to adhere to the strict measures your organization is trying to meet. This affects everything you are using the tool for in the first place.
In determining the “correct” or “agreed upon” business rule, there must be consensus amongst stakeholders on the final decision. In order to hold someone accountable based on data, you have to give them data they can believe in.
2. Integration of Multiple Data Sources
One of the biggest challenges to healthcare analytics is integrating data from multiple sources in order to discover meaningful correlations. To be clear, no organization is using just one source of data. In fact, there are many discrete data sources that must be managed and assimilated for successful business analytics. Financial, clinical, and operational data are usually all managed in separate systems, but in order to get meaningful information, they must be integrated.
An EHR, for example, offers a limited view of information specific to different domains. The common solution – a data warehouse – is an expensive one that comes with a lengthy implementation process, and can be unnecessary depending on the type of analytics tool.
Instead, comprehensive healthcare analytics should have prebuilt connectors to sources. That way, data across the entire organization can be aggregated and analyzed for comprehensive clinical, operational, and financial reporting.
3. Combine Technology with Expertise
While solving the healthcare analytics puzzle is complex, it can be done successfully by employing a combination of the right technology and expertise. This is especially true when it comes to evaluating different tools. While user-driven evaluations do allow you to decide what type tool you prefer based on aesthetics, they fall short of helping you determine which tools are best for meeting your organization’s analytical needs. To do this, it is important to pair the expertise of those within your organization with the technology needs of the business and look beyond the “pretty pictures” to determine what solution is best. Identifying a tool that can do both the “heavy lifting” and display it in a user-friendly environment that allows for deep analysis is crucial.
In addition, just like with any important business decision, clear communication is a must. The technology preferences of all those in the organization should be taken into account, but there also should be an understanding that not all of everyone’s needs may be met. However, by balancing expertise with technology, the end result will be selecting the right healthcare analytics solution that benefits everyone across the organization.
Healthcare environments are complex and unique, ultimately making healthcare analytics even more complicated. To be able to see the true benefits of healthcare analytics – such as reduced operational costs and better care decisions for patients – it is important to consider these three cornerstones. By avoiding common pitfalls, your organization will improve ROI and be closer to achieving its end goals.