Medicare can claw back up to 9 percent of a clinician's pay for failing a quality program that was never designed for the patients they treat. Steve Buslovich, a geriatrician and post-acute care executive at PointClickCare, breaks down how MIPS forces nursing home doctors into conflicting documentation, gameable measures, and real financial and legal risk, and why chasing the wrong numbers can actually hurt frail patients instead of helping them.

⏱️ Chapters:
0:00 Introduction
1:11 What MIPS is and how it quietly turned punitive
2:32 The 9 percent penalty that can end a practice
3:05 Why MIPS was never built for nursing homes
4:43 When a single wound creates conflicting records
5:49 The immunization data that never reaches the doctor
6:23 The financial and legal threats facilities face
7:28 Too many scorecards, not enough staff
8:58 Syncing the records so nothing gets missed
9:41 What it looks like when the system actually works
11:00 The fix: measure frailty, not just disease
13:43 Why some quality measures can be gamed
14:13 What an individual clinician can do right now
15:53 Take home messages

About this episode:
Steve Buslovich is a self-described born geriatrician who practiced as a medical director in post-acute and long-term care, founded a care management and physician EHR company that was acquired by PointClickCare, and now serves as its chief medical officer for senior care. He argues that Medicare's Merit-based Incentive Payment System, built for healthier community practices, maps badly onto nursing home residents who often carry 15 chronic conditions. He walks through concrete failure points: a wound staged one way by a physician and another way on a facility's federally required minimum data set, immunizations logged in the facility record that never sync to a doctor's third party EHR, and disease-specific targets like tight A1C control that the literature shows can harm frail patients. He explains how conflicting documentation drags down a facility's five-star rating, threatens Medicare reimbursement, and becomes ammunition in a litigious environment. His proposed fix is twofold: CMS should build frailty-based quality measures that risk-stratify patients by physiological decline, life expectancy, and goals of care, and technology should automate data collection so clinicians can get back to the bedside. He closes on the role of AI in tying the ecosystem together across transitions of care, and on a blunt piece of advice for clinicians: learn the rules of the game and choose your measures wisely.

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