Every health system has Financial Leakage. In 28 years we have never seen anyone without it, so you’re not alone. Financial Leakage is caused by a lack of visibility into your systems called Dark Data. This Dark Data hides from you between software sytems, in silos, within your data, within supplier data, in many departments, and more. It is exasperated by changge, complexity, compliance, and now COVID-19.

Why is Dark Data everywhere but completely invisible? Because no one (except us) is able to compare all systems, your data, and suppliers data. Bringing light to Dark Data is imparitive your system. By illuminating your Dark Data you gain more control, more clarity, and more cash. You can even use that extra cash to fund other projects in your health system.

Learn More About the Change, Complexity, and Compliance
Learn More About How to Contain Financial Leakage

Read About Dark Data Here

Let’s shed a little light on the reasons why Dark Data exists by discussing the Top 5 Places Dark Data exists within your system.

1.    The integrity of Tools – In a recent study by Kaufman Hall 70 percent of finance executives in a recent survey reported that they don’t have the proper tools in place to effectively reduce costs in their health system.

2.    Disparate Systems and Process – The process of purchasing goods and services can be centralized or span across your network. How many steps are in your process? How many different software systems or methods are involved? The handoffs between departments and the lack of an enterprise-wide view are where control gaps exist, and they are not visible.

3.    Lack of Integration – A common enterprise-wide software system that did everything has been a desire of many hospital executives ever since the first EHR and ERP systems were developed. However, necessary integration is still a challenge for even the most integrated of health systems. There are just too many people involved in the process. The lack of integration means you cannot see the full impact of the process. It says limited visibility and limited ability to make changes or corrections.

4.    The integrity of Data – An additional insight from recent articles is the belief held by 56% of healthcare executives, they don’t believe their data is accurate. This lack of useful information pulled from data hides control gaps and makes it difficult to make changes or improvements.

5.    Limited Reporting – Departmental differences with personal and systems causes holes in the process. There is not an easy way to know if the different methods are causing issues or losses. You probably must run multiple departmental reports and then manually merge the data to gain just a limited view. A lack of visibility allows Dark Data to hide the problems.

The cure to Dark Data is Visibility. A clear view of your enterprise spending coupled with a system to identify outliers gives you control. With visibility and power, you can make changes that close the control gaps and improve your financial fitness.

Before we can have this conversation, we first need to outline what we mean by “Dark Data.” In the simplest terms, “Dark Data” can be defined as the information embedded in the cost cycle that is not easily visible, sometimes not accessible, and rarely timely.

The main causes for this lack of visibility are that this critical cost cycle data is being kept in disparate systems; there is a lack of integration between systems; there is limited reporting across systems; there is significant delay between transactions and information; and there is overwhelming complexity in the healthcare industry overall.  The list goes on and on – we are just scratching the surface as to why this is such a persistent problem.

Over time, much of the system data, which you may assume you have access to, will severely decay and, in many cases, it will become nearly impossible to get to.  This lack of quality and visibility is extremely costly.

Let’s inspect the impact that dark data has had on just one industry – Recovery Auditing.  For years, a traditional recovery audit would return an average of between $400K-900K per every $1B in annual spend.  These estimates are observable through countless samples of traditional audit results.  By contrast, a deeper end-to-end review of light and dark cost cycle data can deliver up to $4M per every $1B in annual spend.  These are quantified results from dozens of huge hospital systems over the past several years. Just think about the impact of these dollars to a hospital’s bottom line.

Getting to the “Dark Data” is difficult, but consider how much of a demonstrable impact it has in this one example.  In the example above, we are talking about the difference of $900K in value versus $4M in value. (per $1B in annual spend) This is of massive and material importance.

Despite the steep benefit to reviewing “Dark Data,” few firms and companies can source the elusive datasets and the massive available value frequently goes undiscovered and unrealized.  That said, a change will soon be coming to the marketplace as anecdotal evidence of the value becomes available and as financial executives are becoming more knowledgeable and more curious about the impact of better data on their operations.

In a recent poll by Health Care Financial News to uncover the top priorities of CFO’s throughout the healthcare space it was revealed that over half of CFO’s and Executives acknowledge that their organizations “lack access to clean, consistent, and trusted data.”  In addition, 90 percent of CFO’s think their hospitals “should be doing more to leverage Financial and operational data to inform strategic decisions.”

The point I would like to leave people with is that the pursuit of uncovering or exposing the “Dark Data” within the cost cycle is a more complete approach to providing visibility to the full berth of financial leakage throughout the cost cycle.  An inspection of “Dark Data” requires a paradigm shift where financial professionals are looking to the review the data that they do not have access to, rather than the records that they are accustomed to reviewing.  In one sense this requires a leap of faith that this “Dark Data” is source-able and when finally sourced will unlock massive savings and efficiency potential.

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