1. How Cleveland Clinic Transformed Revenue Cycle Analytics and Saved Millions
November 14, 2018
Bob Gross, MBA, CPHIMS
Director, Revenue Cycle Analytics

2. Agenda What is the “Revenue Cycle”
Revenue Cycle as an analytical use case
Buy Versus Build
Analytics as a core competency
The importance of cohesive teams

3. What is the “Revenue Cycle”
“All administrative and clinical functions that contribute to the capture, management, and collection of patient service revenue.”
Healthcare Financial Management Association (HFMA)
In other words, the Revenue Cycle reflects the entire life of a patient account from creation to payment.
“What is the Revenue Cycle”:
Revenue Cycle Diagram:

4. What is the “Revenue Cycle”
Characteristics of Revenue Cycle Data
Voluminous - Each step in the Revenue Cycle creates data “exhaust” that can be harvested and converted into actionable information
Complex - Trends and root cause analysis can be elusive due to the nuanced nature of the data
Structured – Fortunately, much of the data in the Revenue Cycle has been codified and structured
“What is the Revenue Cycle”:
Revenue Cycle Diagram:

5. Revenue Cycle as an Analytics Use Case
Cleveland Clinic began to experience challenging conditions in the Revenue Cycle in 2014, including
Insurance Denials
Increasing Patient Responsibility
Resource constraints
Advanced analytical capabilities were seen as a way to understand and manage these challenges
A vision of a Revenue Cycle driven by advanced analytics was embraced.

6. Revenue Cycle as an Analytics Use Case
Gartner Analytics Maturity Model
In 2014, Revenue Cycle Analytics at Cleveland Clinic were highly descriptive, often focusing on report generation
Our new vision would drive us higher on the analytical maturity scale
Shift focus towards root cause analysis to understand the “why"
Predictive analytics could be developed to
Prevent insurance denials
Improve patient collections
Prioritize our workforce on most valuable patient accounts
2014
Gartner Analytics Maturity Model:

7. Buy Versus Build
A Software as a Service provider was selected in mid 2014 to implement an analytics platform capable of achieving the vision
Software as a Service (SaaS) Experience
Some of the quick wins with the SaaS analytics provider were
Ingesting and visualizing patient accounting data
Developing analytical views on insurance claims data
However, it became clear that in order to develop advanced analytical capabilities, the SaaS arrangement would require much more investment and customization
As more investment in time and capital was made, we began to ask the question “Should we build this ourselves?”

8. Revenue Cycle as an Analytics Use Case
Gartner Analytics Maturity Model
In 2016, Revenue Cycle Analytics at Cleveland Clinic were revealing root cause trends in denials and payment delays
Although detailed analysis was now possible, engraining those learnings in our operations required manual intervention
Predictive analytics would require large investments with the SaaS vendor
2016
2014
Gartner Analytics Maturity Model:

9. Buy Versus Build
In 2016, Cleveland Clinic made a substantial investment in technologies that could enable the development of an in-house Revenue Cycle Analytics Platform.
Making the “pitch” to leadership
An in-depth assessment of resource requirements and timing was conducted
Feasibility studies were also performed – “Can we actually accomplish this?”
We proposed creating a partnership between our Enterprise Analytics and Revenue Cycle Management teams to build a replacement to the SaaS platform over 18 months.
An investment in software developers, quantitative analysts, and business analysts was made to support the project.
Net of the personnel investment, the project would achieve a $1.8M annual ROI upon completion.

10. Buy Versus Build
We successfully completed the implementation of our Revenue Cycle Analytics platform in June, 2018, enabling us to eliminate the need for SaaS based analytics.
Analytical Capabilities Achieved
With the implementation of the in-house developed solution, the following capabilities now exist
Data Modeling – New data sources can be ingested using an enterprise standard “data vault” methodology
Visualization –Dashboards and drill down analytics can be developed and published enterprise wide
Machine Learning – Predictive models are being developed to predict denials prior to billing claims, and scoring patients for propensity to pay.
All capabilities are unified with consistent tools and connectivity

11. Revenue Cycle as an Analytics Use Case
Gartner Analytics Maturity Model
Predictive and Prescriptive Analytics are now capabilities of Revenue Cycle at Cleveland Clinic
Models are being deployed to predict denials and calculate patient propensity to pay
Our predictive models are connected to our patient billing system (Epic) to drive workflows and actions, completing the analytics cycle
2016
2014
2018
Gartner Analytics Maturity Model:

12. Analytics as a Core Competency
Advanced Analytics are now viewed as a core competency within Revenue Cycle Management at Cleveland Clinic
Building our platform in-house enabled us to transform our Revenue Cycle by creating and deploying predictive and prescriptive analytics
Advanced analytical capabilities give us a competitive advantage in managing insurance denials and facilitating patient payments
Using analytics is good, but competing on analytics is better
- Thomas Davenport

13. The importance of Cohesive Teams
Building a cross-functional and matrixed team is challenging
A foundation of vulnerable trust enables teams to embrace constructive conflict, commit to decisions, hold each other accountable, and focus on results

14. Summary
The Revenue Cycle covers the entire life of a patient account, providing rich data “exhaust” to harvest for analytics
Advanced analytics can play a major role in solving today’s Revenue Cycle challenges
Trade-offs exist between buying and building analytical solutions
Advanced analytics can provide a competitive advantage
Cohesive teams enable organizations to achieve results

15. Contact Information
Bob Gross, MBA, CPHIMS
Director, Revenue Cycle Analytics
Cleveland Clinic