Navigating the Data Matrix and How to Make Sense of Hospital Data to Maximize Financial Opportunity From CJR
Selected hospitals across the country began the mandatory implementation of the Comprehensive Care for Joint Replacement (CJR) model on April 1, 2016. CJR is a 5-year pilot program run by the Centers for Medicare and Medicaid Services (CMS) testing bundled payments for lower extremity joint replacement (LEJR) clinical episodes. By including hospitals from 67 Metropolitan Statistical Areas (MSAs) around the country, CMS hopes to learn more about how to incentivize valued-based care and reduce spending across diverse locations and patient populations.
On the spectrum of government healthcare initiatives, bundled payment models are nothing new. CMS implemented several pilot programs during the 1980s, such as the Acute Care Episode (ACE) demo, to assess the effectiveness of bundled payments for various clinical episodes in order to determine if this payment model can reduce cost and overutilization of services while maintaining and increasing quality health outcomes. Further, CMS is currently implementing the Bundled Payment for Care Improvement (BPCI) Initiative that is testing the same idea with a variety of clinical episodes, including both elective and trauma LEJR.
In order to profit on a bundled payment model, hospitals and physicians need to continually analyze processes and data as well as coordinate multiple systems. As convener for the largest number of orthopedic physician groups in BPCI, Signature Medical Group (SMG) has gained the experience and knowledge needed to be successful with bundled payments. It can be overwhelming to know where to start when implementing a bundled payment model, but one thing we know for sure: you need to know your data inside and out.
In order to succeed in CJR, it is essential for hospital administrators to understand three things about the data:
1) The target price is a combination of hospital-specific data and aggregate regional hospital data, and it will change over time.
2) An experienced team can help interpret data, generate meaningful reports, and drive effective strategy and decision-making.
3) The correct analysis is essential. This data can be interpreted (and misinterpreted) in many ways.