MACRA Using Data to Capture the Quality Mark

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MACRA: Using Data to Capture the Quality Mark Blessing, CPA, FHFMA, Managing Director Zach

MACRA: Using Data to Capture the Quality Mark Blessing, CPA, FHFMA, Managing Director Zach Remmich, Managing Consultant

Roadmap 1 2 3 2 MACRA Overview Key Elements Affecting Reimbursement in Value-Based Environment

Roadmap 1 2 3 2 MACRA Overview Key Elements Affecting Reimbursement in Value-Based Environment Engaging Physicians Using Data Analytics

WHY MACRA IS IMPORTANT 3 Ø Eliminated sustainable growth rate (“doc fix”): Ø Locks

WHY MACRA IS IMPORTANT 3 Ø Eliminated sustainable growth rate (“doc fix”): Ø Locks clinician payment rates at near zero growth Ø Phased out current Medicare physician payment programs: Ø Physician Quality Reporting System; Value-Based Modifier, Meaningful Use Ø Created two new physician incentive programs: Ø Merit-based Incentive Payment System (MIPS) Ø Advanced Alternative Payment Models (Adv APMs) – MACRA term Ø Program incentivizes participation in value-based, coordinated care models requiring EHR utilization

MACRA PARTICIPATION – YEAR 2 OUTLOOK MACRA 2018 – CMS slow walking implementation Ø

MACRA PARTICIPATION – YEAR 2 OUTLOOK MACRA 2018 – CMS slow walking implementation Ø Ø 4 Merit-Based Incentive Payment System (MIPS) Ø Quality, Cost, EHR, Improvement Activities Ø More providers excluded Ø Low volume threshold increased Ø More participation in APMs Ø Additional scoring and reporting flexibility Advanced APMs Ø 5% annual bonus Ø Advanced APM track criteria unchanged Ø More models included (MSSP Track 1+) 2018 MIPS Scoring 15% Quality 50% 25% 10% Cost ACI IA

2018 MIPS COST MEASURES Medicare Spending per Beneficiary Total Cost per Capita 5 Ø

2018 MIPS COST MEASURES Medicare Spending per Beneficiary Total Cost per Capita 5 Ø Specialty-adjusted measures that evaluates overall efficiency of care Ø Includes Medicare Part A and B Ø Attribution based on largest share of primary care services provided or specialist if beneficiary didn’t visit a PCP Ø Cost of Medicare Part A and B services during a 30 day episode Ø Not adjusted for specialty Ø 35 case minimum or no score Ø Attribution based on plurality of Part B claims during inpatient stay

MACRA IMPLICATIONS Ø MACRA five-year reimbursement risk on stand-alone basis likely less than cost

MACRA IMPLICATIONS Ø MACRA five-year reimbursement risk on stand-alone basis likely less than cost of infrastructure required to fully maximize reimbursement effect Ø Efforts to maximize MACRA reimbursement effect could have opposite (& potentially more material) downstream reimbursement effects for various providers in FFS environment Ø Practices need the necessary infrastructure & expertise to manage data reporting, care coordination & clinical outcomes before taking on payment risk Ø Total cost of care management for Medicare beneficiaries likely to be a significant differentiator 6

KEY ELEMENTS AFFECTING REIMBURSEMENT IN VALUE-BASED ENVIRONMENT 7

KEY ELEMENTS AFFECTING REIMBURSEMENT IN VALUE-BASED ENVIRONMENT 7

HISTORIC: FEE FOR SERVICE REIMBURSEMENT Ø Clinical procedure performed = add’l reimbursement Ø Profitability

HISTORIC: FEE FOR SERVICE REIMBURSEMENT Ø Clinical procedure performed = add’l reimbursement Ø Profitability considerations: Ø Add’l expense of procedure offset by add’l reimbursement Ø Since reimbursements typically exceed direct expense of procedure, performing MORE procedures &/or HIGHER INTENSITY procedures helps cover indirect (overhead) costs Ø CPT procedural code drives reimbursement as opposed to ICD-10 diagnosis codes Ø Medicare DRG reimbursement is largest historic example of non-FFS reimbursement – what was its effect? Ø Significantly reduced average lengths of stay Ø Significantly increased diagnosis coding efforts 8

VALUE BASED REIMBURSEMENT Ø Patient episode = additional reimbursement Ø Patient episode definitions vary

VALUE BASED REIMBURSEMENT Ø Patient episode = additional reimbursement Ø Patient episode definitions vary greatly, but basic way to define: Ø For Primary Care, attributed beneficiary total care for medical issues (Capitation) Ø For Specialists, referred beneficiary total expenditures for a specific issue, for a specific time after an initiating event (Bundle) Ø Reimbursement adjustments for “Value”: Ø Patient HCC Score: Higher score, higher reimbursement (“sicker”) Ø Quality & Outcomes: Higher score, higher reimbursement (“better care”) 9

VALUE BASED REIMBURSEMENT Continued… Ø Profitability considerations: Ø Clinical procedure performed – no additional

VALUE BASED REIMBURSEMENT Continued… Ø Profitability considerations: Ø Clinical procedure performed – no additional reimbursement Ø Since no additional reimbursement, performing FEWER procedures &/or LOWER INTENSITY procedures helps profitability because of saved direct costs for procedures Ø ICD-10 diagnosis codes drive reimbursement as opposed to CPT procedural codes because of effect on HCC Score 10

HOW ARE CLINICIANS BEING AFFECTED Ø Different flavors of CMS initiatives Ø Accountable Care

HOW ARE CLINICIANS BEING AFFECTED Ø Different flavors of CMS initiatives Ø Accountable Care Organizations (ACO) Ø MACRA Ø Bundle programs (BPCI; Comprehensive Joint Replacement, etc. ) Ø Medical Home models Ø Many others Ø Commercial insurers are beginning to come along with Medicare 11

HOW ARE CLINICIANS BEING AFFECTED Continued… Ø New abilities become more important to profitability

HOW ARE CLINICIANS BEING AFFECTED Continued… Ø New abilities become more important to profitability as VB reimbursement percent of business grows: Ø Diagnosis coding (HCC code effect) Ø Management of episode claim costs across all providers Ø Management of quality & outcome measures Ø What are organizations doing to develop & implement the above abilities? Ø Case management (control episode costs for high expense patients) Ø Clinical protocol development (control episode costs) Ø Coding initiatives such as AWV process (properly reflect HCC Scores) 12

ENGAGING PHYSICIANS USING DATA ANALYTICS 13

ENGAGING PHYSICIANS USING DATA ANALYTICS 13

ENGAGING PHYSICIANS USING DATA 14 Ø The transition from FFS to value-based care can

ENGAGING PHYSICIANS USING DATA 14 Ø The transition from FFS to value-based care can be summed up in two words: risk transfer Ø Multiple ways payers are transferring risk to providers: Ø Episodes of care (bundled payments) Ø ACO/MSSP Ø Hospitals must begin to think like insurance companies in terms of managing risk

ENGAGING PHYSICIANS USING DATA 15 Ø Clinical decision making becomes key financial driver- new

ENGAGING PHYSICIANS USING DATA 15 Ø Clinical decision making becomes key financial driver- new business model Ø Standardize care, lower unwarranted variations, focus on complications and readmissions, drive down cost (Medicare and internal) Ø Must have management systems in place to gather, analyze and share data with physicians Ø Physician salary constitutes 20% of health care spending but the decisions they make influence an additional 60% of spending¹ Ø What about small, rural hospitals with only one specialist? Incenting n=1

DEVELOPING A PHYSICIAN COLLABORATOR STRATEGY 16 Ø Analyzing data for variation and impact Ø

DEVELOPING A PHYSICIAN COLLABORATOR STRATEGY 16 Ø Analyzing data for variation and impact Ø Identify high-level systemic care redesign needs Ø Identify collaborator quality guidelines Ø Integrate leadership physicians in strategy process Ø Gauge current level of interest Ø Consider how their practice will be affected Ø Evaluate potential internal cost savings Ø Compliance (FMV, Stark, IRS excess benefit)

ENGAGING PHYSICIANS Challenges you may face Ø Ø Ø Development challenges (Multi-group, employed and

ENGAGING PHYSICIANS Challenges you may face Ø Ø Ø Development challenges (Multi-group, employed and independent) Consensus on protocols and standardization Skepticism in data and measurement Concern with clinical decision making Perception of profit-sharing Lack of trust Establishing trust with physicians “Above all, success in business requires two things: a winning competitive strategy, and superb organizational execution. Distrust is the enemy of both. I submit that while high trust won't necessarily rescue a poor strategy, low trust will almost always derail a good one. ” Stephen MR Covey, The Speed of Trust 17

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ENGAGING PHYSICIANS WITH DATA 24

ENGAGING PHYSICIANS WITH DATA 24

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