The risk adjustment track at RISE West provided attendees with useful information and innovative strategies to strengthen their programs. This article looks at the success that Brown & Toland Physicians have had with three partnerships that provided HCC Analytics, Natural Language Processing, and the Annual Health Assessment Program.
PALM SPRINGS, CALIF.— Representatives from Brown & Toland Physicians, a leading network of 2,500 primary care physicians and specialists in the San Francisco Bay area, spoke during a breakout session at RISE West 2018 about three initiatives that helped them boost and sustain their risk adjustment program.
The network’s risk adjustment history goes back to 2011 when it secured a limited Knox-Keene license, which enabled it to contract in full-risk arrangements with Medicare Advance Plans. Over the next two to three years, it grew its membership under the full-risk umbrella and executed clinical quality programs. But three years ago, the group noticed a decrease in its risk adjustment factor(RAF) scores, which it attributed to changes in the hierarchical condition category (HCC) model and challenges with physician/biller coding. As a result, they’ve spent the last two years turning around its clinical quality programs, based on high intensity pilot activities that occurred in the fourth quarter of 2016.
Sean O'Sullivan, manager, population health, at Brown & Toland Physicians, said the group focused on three partnerships that provided HCC Analytics, Natural Language Processing (NLP), and the Annual Health Assessment (AHA) Program.
In 2016, he said, the group changed its HCC Analytics partner to use a tool that provided more insight into risk scores. Its previous vendor processed CMS data for the sole purpose of giving the organization its current RAF score. But the new HCC tool allows the group to obtain an HCC gap analysis to Model Output Report (MOR)/Risk Adjustment Processing System (RAPS) files. This allows the group to see gaps in its HCC each month, he said.
The NLP technology helped Brown & Toland identify gaps in HCC submissions by comparing new codes to RAPS return files; increased coder productivity during busy Sweeps seasons; and reduced provider abrasion by excluding NLP review from health plan chart cases. The algorithms helped the group learn from all projects, not just the provider data. “We can review 60 percent of Medicare lives without asking physicians for anything,” he said.
Prior to initiating the 2016 pilot, Brown & Toland had its physicians conduct the annual wellness visit. But the group decided to partner with nurse practitioners in the fourth quarter of 2016 and have them take on the AHAs. That partnership helped the network strengthen its end-to-end oversight of coding and documentation, explained Jenny Tu, director, population health. This has allowed it to review chart notes and ensure the correct coding is captured before the group submits the claim to health plans.
Furthermore, she explained, smart EMR integration is built into custom templates so the nurse practitioners spend less time documenting to capture HCCs and HEDIS and Star measures in the visit. Data mining is performed pre- and post-visit by either the nurse practitioner or RAF coders.
Tu said that groups that want to take on a similar process should consider the corporate culture. The organization needs to understand that many teams impact risk adjustment, she said. Brown & Toland emphasized this by establishing cross-departmental workgroups to gather and come up with process improvements. The organization discussed the progress during all-hands updates and made the progress visible with scoreboards in high-traffic areas so employees would notice it. Tu said that the group provided continuing education during brown bag lunches to educate primary care providers about the different work the organization was doing. The key, she said, is to emphasize accuracy, not to increase RAF scores.