By Jonathan Farr
Today, healthcare leaders recognize the need to “tune up” operational systems by turning to the unique advantages of real-time data analytics, especially now that increased mergers and acquisitions have left hospitals, hospital systems and Integrated Delivery Networks struggling to retrieve, review and compare data from incompatible platforms.
The answer is an efficiency platform that overlays existing systems to help healthcare organizations compare massive amounts of data across their total enterprise, detect exceptions and problems, and guide interventions to improve efficiency that optimizes financial, clinical and operational performance.
Key Trends Make Real-Time Data an Imperative
Among the various types of data, only real-time data enables hospital leaders to take action and follow up on that action to correct inefficiencies, denials and revenue leakage. In fact, key trends in hospital analytics are shifting toward real-time analytics as the step beyond problem definition:
- Merging separate platforms in pre- and post-mergers and acquisitions analytics to generate an enterprise-level view cost effectively
- Pushing adjusted or new data back into operational systems
- Analyzing revenue and cost by diagnosis, and value proposition in terms of revenue divided by cost, and then divided by diagnosis
- More accurately analyzing actual revenue variance by origin through price, volume and mix calculation, with mix being defined by patient, payer or diagnosis
- Prescriptive analytics follows predictive analytics to actively suggest how organizations can best take action
- Looking forward: incorporating big data in the context of the healthcare Internet of Things (IoT), predictive analytics and block chain as a distribution ledger.
While the industry has excellent operational systems that perform 95 percent of necessary tasks quite well, they only serve as a base system that must be audited on a continuous basis. Hospital systems should seek a platform that overlays existing operational systems, and functions as a permanent, protective 24/7 auditing and reporting “umbrella.”
Real-Time Analytic Tools in Action
The good news for mid- to large-size hospital enterprises concerned with revenue cycle management (RCM) is that they can now increase net revenue by three to four percent, with ROI multiples of between eight and ten by adding a real-time data analytics platform.
This is important because healthcare leaders often know the issues related to RCM, but are overwhelmed by exceptions, and lack the tools to discover variances and manage actions to correct them. Real-time data analytics is where hospital organizations gain the ability to define the rules and set validations to audit transactions as they occur.
Consider this example: If a drug treatment is changed to one that requires pre-authorization, an alarm is sounded, so the pre-authorization can be requested. The alarm is triggered by data originating from the pharmacy system (or module if incorporated within an EHR) and matched to the third-party payer’s requirements for pre-authorization. Without this capability, payment is denied.
Sophisticated real-time data analytics systems allow a hospital to use any data from any operational system to set up sophisticated alarms to detect issues immediately.
For instance, an analyst using an RCM optimization tool with the right action-driven features has the reconciliation and analytical tools to rapidly respond to any alert. Instead of channeling the issue up through all of the relevant departments, which is time-consuming and demands the attention of a number of people, the analyst can simply guide an alarm to the appropriate staff to “fix,” resolving the problem quickly, and improving the bottom line.
Fewer Claim Denials
Real-time data analytics address and solve problems in virtually every aspect of operations, especially in the area of claim denials based on treatment authorizations. These denials occur primarily when there is a deviation in the plan of care, and they burden clinical and operational teams to secure authorizations for treatment necessitated by a change in the patient’s health status.
Too often, these approvals are not processed with the payer for a variety of reasons. While the screens on the existing overall operating system register the charges that would drop on the claim, the system fails to confirm payer authorization. The claims are denied, even though the care was rendered and the expense incurred — which leads to a write-off for the hospital system. In the end, documenting medical necessity to ensure reimbursement lifts the burdens of claim denials that result from documentation failure.
By simply overlaying a robust real-time data analytics system, managers can quickly gain control of aggregating data, and detecting/resolving issues that impact revenue integrity, as well as clinical and operational performance, in a way that is the most cost-effective.
Jonathan Farr is Senior Vice President, North America for EFFY.