How do I predict a CMS TEAM penalty before the 30-day episode ends?

Most hospitals don't know they've triggered a TEAM penalty until 60–90 days after discharge. The key is tracking three metrics in real time: surgical complication rate, post-acute care spending, and unplanned readmission within the episode window. Episodes where post-acute spend exceeds the benchmark by week 3 have an 80%+ probability of a final penalty — and that window is still correctable with targeted care management.

The CMS Transforming Episode Accountability Model (TEAM) assigns hospitals a fixed benchmark payment for each surgical episode — hip/knee replacement, surgical hip fracture, major bowel procedure, CABG, and spinal fusion. If total episode spending (including 90-day post-acute care) exceeds the benchmark, the hospital absorbs the difference. If it comes in under, the hospital earns a share of the savings.

The structural problem is timing. Claims data from post-acute facilities — SNFs, home health agencies, outpatient rehab — arrives 30 to 90 days after the care is delivered. By the time a hospital knows that an episode is trending over benchmark, the patient has already been discharged, readmitted, or cycled through three post-acute providers. There is no intervention possible at that point.

The hospitals that consistently perform under TEAM benchmarks don't have better surgeons or healthier patients. They have earlier warning systems. They flag high-risk episodes at the time of discharge planning, not at claims reconciliation.

The data that most hospitals review for TEAM compliance is claims data — and claims data is retrospective by definition. What the data doesn't surface automatically is the predictive signal that's already in your discharge dataset.

Three variables in your EHR export predict TEAM penalty risk with high accuracy before discharge: (1) LACE score above 10 (predicts post-acute overutilization), (2) discharge disposition to SNF vs home (SNF episodes average 2.3x the post-acute spend of home health episodes), and (3) documented surgical complications such as wound infection, DVT, or prolonged ileus (each adds $4,000–$9,000 to episode cost on average).

Generic BI tools show you aggregate episode costs after the fact. They don't show you which episodes currently in your system are on a trajectory to breach the benchmark — because that requires combining discharge data with benchmark math in real time.

The fix operates in three phases. First, establish episode-level benchmarks at the procedure level. CMS publishes TEAM benchmarks by MS-DRG category. Map your surgical volume against these benchmarks to know which procedures are highest-risk in your patient population.

Second, flag high-risk episodes at discharge planning. Any patient with LACE ≥ 10, discharge to SNF, or documented complication should trigger a care management protocol — proactive SNF selection (quality-rated facilities have lower readmission rates), shorter SNF stay targets, and scheduled follow-up call at day 7 and day 14. The CMS evidence base shows that structured post-discharge contact within 7 days reduces episode costs by 8–14%.

Third, build a 90-day episode cost tracker using your EHR discharge data combined with any available care management logs. Even without real-time claims feeds, documenting post-acute placement, estimated SNF stay length, and readmission events gives you a running estimate of episode cost within 10–15% accuracy — enough to identify outlier episodes while intervention is still possible.