Healthcare News & Insights

Hospital analytics: Key trends and optimizing revenue cycle management

With increased mergers and acquisitions, hospitals, hospital systems and integrated delivery networks must retrieve, review and compare data “ no matter the size, data incompatibility or platform complexity.

Among the various types of data, only real-time or near real-time data analytics can enable hospital leaders to act and follow up on it to correct inefficiencies, denials and revenue leakage. In this guest post, Jonathan Farr, senior VP North America of a provider of healthcare operating systems, explains what real-time data is, trends driving its use and how to take advantage of those trends to optimize revenue cycle management.


Real-time data analytics in a hospital enterprise can process massive amounts of data quickly, automatically testing data against norms or pre-determined values. In this way, variances that jeopardize the capability to put out a clean claim, identify non-compliance with contractual requirements or threaten clinical performance can be quickly identified and rapidly addressed.

This innovative system overlays existing operational systems to deliver a cleaner, smarter and cost-effective solution. It important to understand, however, exactly what śreal timeť means.

Defining real-time data in hospital RCM

Real time isn possible in the context of revenue cycle management (RCM) solutions, but it possible in some scenarios to receive and audit data multiple times per day.

Another factor is that a transaction can be reviewed until it processed in the transaction system in which it is used.If the transaction system is batched for a nightly process then, by definition, real time is the next day. Therefore, real time means the first time data is available in an operating system for extraction or to be read. This isn necessarilythe time a data point is entered into a system.

Organizations define the rules and set validations, and when linked to real-time data create the ability to act immediately. Access to accurate data, fast, allows for the ability to answer questions, drill down to see all the component parts that make up a number and, ultimately, achieve a better revenue cycle for hospitals.

Trends driving real-time analytics

These key trends in hospital analytics are shifting toward real-time actionable analytics as the step beyond problem definition:

  • Merging separate platforms both pre- and post-merger to generate an enterprise-level consolidated view of key statistics, cost-effectively
  • Pushing adjusted or new data back into a transactional system after it has been extracted, audited and adjusted
  • Predicting the costs of caring for a population by knowing the costs associated with diagnoses and then multiplying by the propensity of diagnosis within a population
  • More accurately understanding revenue variance by calculating the sub-components of price, volume and mix, with mix being defined by patient demographics, payer or diagnosis
  • Prescriptive analytics follows predictive analytics to actively suggest how organizations can best act, and
  • Looking forward: incorporating big data in the context of the healthcare Internet of Things (IoT), prescriptive analytics and block chain, and distribution ledger technology.

Taking advantage of trends to optimize RCM

Hospital leaders should look for an efficiency platform that overlays existing systems to help them 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.

All of these actions should function as a permanent, protective 24/7 auditing and reporting umbrella. This approach eliminates the need to replace one operational system with another similar product with a new set of issues. It also streamlines back-end processes, and relieves stress and time constraints imposed on the clinical staff.

Real-time actionable data analytics represents the forward trend in RCM optimization: helping hospitals increase net revenue by 3% to 4%, with ROI multiples of between eight and 10.

What more, hospitals can use any data from any operational system to set up sophisticated validations to detect issues immediately. By simply overlaying a real-time data analytics system, managers can quickly gain control of aggregated data, and detect/resolve 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 VP North America at