Total Cost of Care (TCOC) Workgroup. January 30, 2019

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Transcription:

Total Cost of Care (TCOC) Workgroup January 30, 2019

Agenda Introductions Updates on initiatives with CMS Y1 MPA (PY18) Implementation Timing Y2 MPA (PY19) MPA Operations Reporting and Attribution Stability Y3 MPA (PY20) Y3 Design Focus Areas Y3 Refinement 2

Updates on Initiatives with CMS December 2016 CMS Data Update Other Updates 3

Y1 MPA (PY18) MPA Implementation Timing 4

Y1 MPA Implementation Timing The HSCRC is waiting for 2018 claims to run-out and for CMS data quality to improve before calculating the Y1 MPA Steps Moving Forward: To implement the MPA, HSCRC calculates the MPA and tells CMS what percentage adjustment to make to hospitals' Medicare payments CMS implements adjustment with the Medicare Administrative Contractor (MAC) The MPA does not go into rates, does not affect hospitals' GBR, and is not reflected in rate orders 5

Y2 MPA (PY19) MPA Operations Y2 Timing Overview MPA Liaison Listserv Review Period Y2 Reporting and Attribution Stability 6

MPA Information Submission and Review Timeline Estimated Timing Action December 2018 Required for ACOs: Hospitals provide HSCRC with ACO Participant List for Performance Year 2019 (also used for Base Year 2018) Voluntary: Hospitals participating in multi-hospital ACOs designate which ACO providers should be linked with which ACO hospital. Voluntary: Hospitals provide HSCRC with a list of full-time, fully employed providers January 2019 Performance year begins HSCRC combines hospital lists and identifies potential overlaps HSCRC runs attribution algorithm for Base Year 2018 and Performance Year 2019, and provides hospitals with preliminary providerattribution lists February 2019 Official review period for hospitals of 2 weeks following preliminary provider-attribution lists. HSCRC reruns attribution algorithm for implementation March 2019 Voluntary: Hospitals wanting to be treated as a combination under the MPA submit a joint request to HSCRC 7

MPA Operations: Provider Submission Duplications 33 hospitals submitted provider linkage data 55 providers were duplicated across hospitals (not bad!!) MDPCP - 0 ACO - 34 Employed - 21 Hospitals will be emailed to clarify providers that were duplicated 8

MPA Liaison Listserv The HSCRC is working with MHA and individual hospitals to develop a MPA Liaison Listserv Purpose: Streamlined and consistent operational MPA emails Provider Linkage Data Referral Pattern Attributed Providers Review Period Coordination MPA Reporting Webinars and Updates NOT a policy listserv policy will continue to be developed through the TCOC WG Hospitals can request that multiple individuals be added Email HSCRC. TCOC@Maryland.gov to be added 9

February 2019: Review Period and Unique Situations 1. Review Period to resolve issues for attribution to work as intended For example, if a provider is inadvertently attributed to two hospitals Not for fundamental changes to the attribution methodology 2. Review Period for unique situations that may merit alternative approach For example, if two hospitals agree to share responsibility for certain physicians and their beneficiaries Not for fundamental changes to the attribution methodology Any changes based on submissions during Review Period would require HSCRC approval 10

March 2019: Options to Combine for MPA Multiple hospitals are permitted to work together to address TCOC Process: The MPA attribution will still be performed for all hospitals individually. Then, for hospitals being combined for purposes of the MPA, the total cost of care and beneficiaries will be pooled The combined total cost of care per capita will be used to assess performance. The adjustment calculated on the combined total cost of care per capita will be applied to each hospital in the combination Hospitals outside of the combination will not be affected The HSCRC will review and work with hospitals to refine options for a combined MPA assessment 11

Consistency in Provider Linkage in MPA Performance Assessment Over Time Background: Providers attributed to a hospital in a performance year in Y1 may not always be included in that hospital s base year Example: Dr. Jane is attributed to Hospital A in CY19 (performance year) through referral-linkage but does not show up in Hospital A s base period because she was attributed to Hospital B in CY18. In MPA Y1, only ACO-like providers were held constant between the performance period and base years. In MPA Y2, providers linked to hospital through MDPCP-actual, ACOlike and Employment will be held constant, but PCP-like is TBD. Question: To what extent, in Y2, should providers in a hospital s performance year attribution be included in their base year for performance assessment? 12

Consistency in Provider Linkage in MPA Performance Assessment Over Time, cont. Based on discussion, staff is moving forward Option 2 for the Referral Pattern linkage in Y2: 1. No Change: As occurred in the Y1 policy, clinicians (except for MDPCP and ACO participants) and beneficiaries are relinked/attributed separately for the base year vs. performance year 2. Provider Consistency: Clinicians attributed to a hospital in the performance year are automatically attributed to that hospital for the base year but beneficiaries recalculated/reattributed for each year 3. Beneficiary Consistency: Beneficiaries are attributed to a hospital in the performance year are automatically attributed to that hospital for the base year 13

Y3 MPA (PY20) New: MPA Efficiency Adjustment, Attainment Options Refine: Attribution Algorithm, Processes 14

MPA Year 3 Focus Areas New: MPA Efficiency Adjustment Development of an Attainment Target TCOC Benchmarking Quality Updates Refinements: Attribution Algorithm Submission Processes 15

MPA Efficiency Proposal to Achieve Medicare Savings and Incentivize Care Transformation

Executive Summary TCOC Model requires the State to save $300 million annually in Medicare expenditures by 2023 The State has several tools to get these savings, but: 17 Uncertainty in whether savings apply to Medicare target (Update Factor, PAU Savings, MPA, removing excess capacity, hospital efficiency, etc.) Savings may come from: All-payer tools vs. Medicare-specific tools Price levers vs. care transformation Under this proposed approach, the State will: Continue to set Maryland hospital revenue at an economically sustainable rate for all payers Meet Medicare savings targets using MPA Efficiency Adjustment Allow savings from other policy levers can be reinvested

Requirements of the TCOC Model Total Cost of Care Contract Requirements: 1. Limit Maryland Medicare FFS total cost of care grows below the national total cost of care growth a) No more than national Medicare TCOC +1% in any year b) Do not exceed national Medicare TCOC growth over 2 consecutive years c) Keep All-Payer hospital revenue growth <3.58% (10 year GSP) 2. Achieve Medicare specific savings, reducing Maryland annual Medicare expenditures by $300 million in 2023 18

Translating Medicare TCOC Requirements Requirement 1 address controlling overall TCOC costs, growth, and sustainability for all payers This requirement will be meet using tools like the Update Factor, Quality policies and Potentially Avoidable Utilization (PAU) policy Requirement 2 requires reductions of Medicare excess costs to bring Maryland in line with economically similar states. This requirement will be met using Medicare specific tools CMMI s expectation is that these savings are generated through care transformation and not achieved solely through price levers 19

Proposed Approach for Meeting the TCOC Model Requirements The HSCRC will meet the TCOC growth requirements by: Setting the annual Update Factor so that: 20 Maryland Medicare grows less than national Medicare TCOC growth, and All-payer hospital revenue growth remains economically sustainable The Update Factor is not intended as the tool to obtain the required incremental Medicare savings The HSCRC will meet the incremental Medicare Savings requirement by: Using the MPA Efficiency Adjustment to meet the incremental savings requirement Allocate the savings to hospitals in order to incentivize care transformation efforts

Medicare Performance Adjustment (MPA) MPA has two components, both implemented as a percentage adjustment to hospitals Medicare payments. Can be titrated semi-annually with the Update Factor 1. Traditional MPA: TCOC attribution algorithm, ±1% Medicare revenue 2. MPA Efficiency Adjustment: Move money to/from hospitals on a Medicare-only basis, e.g.: A. To hospitals for performance in episode-based CRP track, ECIP B. From hospitals to get CMS their required Medicare savings 21

Medicare Specific Savings Requirement: Incremental Savings to Add Up to $300M Increase the current run rate (from 2013 base) to $300M by the end of 2023 Year 2019 2020 2021 2022 2023 Required level of TCOC savings Incremental savings from prior year $120M $156M $222M $267M $300M $0 $36M $66M $45M $33M In other words, increase in annual Medicare TCOC Savings of $180M from 2019 to 2023 22

Proposed Approach for Incremental Medicare Savings under the TCOC Model The MPA Efficiency Adjustment will target incremental Medicare savings necessary beyond the current total cost of care run rate Rationale: Uses a Medicare specific tool vs All-payer tool Allow Medicare savings to be allocated equitably across hospitals Increase accountability for care transformation (i.e., minimizes the free rider problem of hospitals relying on others to achieve savings) Strengthens incentives to invest in care transformation Hospitals have the opportunity to recoup payment reductions from the MPA Efficiency Adjustment (earn MPA Payments) through participating in care transformation efforts 23

Applying the MPA Efficiency Adjustment Prospectively determine how the MPA Efficiency Adjustment will be allocated among hospitals If $36M in additional Medicare savings are required, and Hospital A has a 10% share, Hospital A s MPA Efficiency Adjustment = $3.6M Different allocation methods are feasible (hospital share of Medicare payments, Care Redesign opportunity, etc.) Allow hospitals to recoup their savings through care transformation efforts such as ECIP For example, if a Hospital A earned a $5M ECIP reconciliation payment, then they would received a net MPA Payment of $1.4M 24

Price vs Care Transformation Levers CMS approved the TCOC Model to achieve both sustainable Medicare spending and to enable care transformation. The State agrees and is seeking to operationalize policies that incentivize these complementary approaches. Achieving Medicare savings through the MPA Efficiency Adjustment uses a price lever that will be allocated to incentivize care transformation efforts If a hospital earns an MPA payment, that payment will be offset by other hospitals. This ensures that hospitals less engaged in care redesign bear a greater share of any savings required through the MPA Efficiency Adjustment 25

Measuring Existing Care Transformation The HSCRC will work with hospitals to quantify existing or new care transformation efforts and factor those efforts into the MPA accounting In order to quantify care transformation efforts and factor them into the MPA accounting, those efforts must have: An identifiable patient population Clearly identifiable care redesign interventions A measurable impact on the TCOC 26

Timing of MPA Adjustments and CRP Tracks MPA Efficiency Adjustments will begin in the calendar year corresponding to the required Medicare savings CRP Tracks should begin a year prior in order to allow hospitals to earn offsetting MPA payments Year 2019 2020 2021 2022 2023 Required Savings $120 $156 mil. $222 mil. $267 mil. $300 mil. CRP Track goes live CRP Reconciliation Payments ECIP Y1 ECIP Y2 New CRP?? ECIPY1 ECIPY2 New CRP? 27

28 Additional Slides

Background: Hypothetical Hospital A not Participating CRP Expected annual Medicare hospital payments: $200M 1. Traditional MPA: Yields +1% adjustment = +$2M 2. MPA Efficiency Adjustment Allocation ($3.6M) Calculation: Allocation Share = 10% of $3.6M 3. MPA Savings Accounting Traditional MPA +$2M MPA Efficiency Adjustment ($3.6M) Total: ($1.6M) Result: Hospital A Medicare payments (%): $198.4M 29

Background: Hypothetical Hospital B Participating CRP Expected annual Medicare hospital payments: $200M 1. Traditional MPA: Yields +1% adjustment = +$2M 2. MPA Efficiency Adjustment Allocation= +$1.4M Calculation: Allocation Share = 10% of $3.6M = ($3.6M) Positive Reconciliation Payment through ECIP = $5M 3. MPA Savings Accounting Traditional MPA +$2M MPA Efficiency Adjustment +$1.4M Total: +$3.4M Result: Hospital A Medicare payments: $203.4 M 30

Example with MPA Efficiency Adjustment and ECIP Participation Producing Savings 2019 2020 2021 Beginning Yr TCOC Savings $120 million $125 million $171 million ECIP Reconciliation Payment N/A -$5 million -$15 million TCOC Savings Target $120 million $156 million $222 million MPA Adjustment $0 $156-(125-5) = $36 million $222-(171-15) = $66 million End of Year TCOC Savings $120 +5 for ECIP = $125 million 1. ECIP does not increase cumulative TCOC savings. But ECIP does a. Increase the share of savings from care transformation rather than price levers, and b. Create an opportunity for savings to come from non-hospital providers. 2. The MPA Efficiency Adjustment is allocated to hospitals prospectively so that hospitals can keep the care transformation savings they produce. 31 $125-5+36 +15 for ECIP = $171 million $171-15+66 + 0 for ECIP = $222 million

Summary: Matching TCOC Contract Requirements with HSCRC Tools and Policies All-Payer Update Factor Used to: Ensure that health care costs growth at an economically sustainable rate for all payers The Update Factor will be set to keep Medicare TCOC growth less than national and all-payer growth less than GSP Rationale: Sustainable growth in healthcare costs is an all-payer objective consistent with the HSCRC s statute MPA Efficiency Adjustment Used to: Reduce excess Medicare spending to bring Maryland in line with economically similar states The MPA Efficiency Adjustment will be used to meet the required incremental savings Rationale: Can be allocated prospectively to incentivize care transformation efforts Ad-hoc Policies Used to: Address outlier spending, reduce excess capacity, improve efficiency, fund capital improvements, etc. Rationale: Allow excess savings to be reinvested into the system Allow for flexibility in developing custom solutions for unique populations and regions 32

Tools to be Successful Under TCOC Model MPA Reporting Suite MADE and CRP Analytics Medicare claims for attributed beneficiaries State shares in cost of developing and operationalizing CRP tracks Process of identifying innovative ideas (Stakeholder Innovation Group) and improving them and ensuring they meet needs (CRP Steering Committee) 33

34 National Benchmarking Initiative

National Benchmarking Initiative Benchmarking: Why? Benchmarking: How? Specific Policy Approaches and Timelines More on the How: Considerations in benchmark group development Key Statistics - Medicare comparison 35

Benchmarking: Why? December 2016 36

Benchmarking: Why? Policy Needs Build understanding of national per capita trends and achievements Obligations under the model Setting statewide goals and targets Establish comparison points for setting targets and evaluating hospitals performance under an attainment approach 37

Benchmarking: Why? Policy Application Multi-payer Benchmarking: Initial focus where data is most available: Medicare Fee-for-service (MC FFS), includes patients covered by the traditional Medicare program, not including those covered under a Medicare Advantage program. Private Payer, for this project private payer includes commercial group and individual markets but not Medicare Advantage or Medicaid MCOs. Look to expand in the future Potential Applications: Medicare Performance Adjustment (MPA) support an attainment approach and trend factor targets Inter-hospital Cost Comparison (ICC) include total cost of care per capita performance in evaluation Quality Benchmarking support a per capita attainment approach with national/comparison benchmarks Others? 38 More on these later, but first....

Benchmarking: How? December 2016 39

Benchmarking: How? Broad Goal Allow comparison of Maryland performance to national performance while recognizing differences that drive legitimate variation. Because Maryland has a significant concentration in high cost urban areas, Maryland s costs relative to national averages look significantly higher when geographies are not matched. Maryland regional differences account for ~10% of variation versus national MC FFS average 40

Benchmarking: How? Evaluation Unit Focus for this effort is member/beneficiary geography: Geographies align best with per capita measures. Selection of comparison group relies on measures that are available on a geographic basis. Different site of service mixes makes it important to consider total cost of care, not just hospital per capita costs. Since most HSCRC methodologies are hospital based will need to determine a weighting approach to blend per capita results into each methodology. 41

Benchmarking: How? Primary Components 1. Establish a valid comparison group for each geography/beneficiary group we want to evaluate. Relies on a combination of general non-healthcare data (e.g. population demographics) and healthcare data (e.g. HCC*). Focus on factors that are not controlled by the healthcare system (e.g. general cost of living), exclude factors that are artifacts of the system (e.g. place of service mix). 2. Calculate metrics for comparison between the target geography/beneficiary group and the identified comparison group. 42 Relies primarily on healthcare claims data. Normalize for differences not normalized through selection of the comparison group. *Hierarchical condition category (HCC) coding is a risk-adjustment model originally designed to estimate future health care costs for patients, which is used by CMS for Medicare patient risk adjustment.

Timelines and Specific Approaches December 2016 43

Benchmark Development Timeline Q4 2018 Initiated MC FFS benchmarking Contracted for expertise on methodology development Q1 2019 Complete MC FFS Benchmarking Contract with vendor for Private Payer* Benchmarking Begin methodology development to incorporate benchmark outcomes Q2 2019 Complete Private Payer Benchmarking Begin roll out of specific methodologies *For this project Private Payer includes commercial group and individual business but not Medicare Advantage or Medicaid MCOs. Future: Medicaid Annual updates Implement into further methodologies Opportunity analysis based on national comparison 44

Approach and Timeline MPA Approach Year 3 MPA adjustment may be based on a blend of achievement and attainment targets, attainment targets will be derived from MC FFS benchmarking. Likely Timeline Exact approach and process will be finalized in Q3 and Q4 of 2019 for implementation in MPA Year 3 (2020). Key Technical Considerations Mapping MPA attribution methodology-based outcomes to appropriate benchmarks 45

More on the How: Considerations in Benchmark Group Development December 2016 46

Considerations in Benchmark Group Development Definition of the geographic unit of analysis. Further explanation of the benchmark development process and key questions to be addressed. 47

Process Flow and Key Questions Key Questions: Establish a valid comparison group Select comparison characteristics to define similar (e.g. age, income) Calculate values for all possible comparisons Aggregate individual characteristics and select comparison group What characteristics should be used to define similar? How similar is similar enough? Calculate cost and quality metrics Calculate metrics for comparison (e.g. per capita cost, readmission/k, days/k) Normalize metrics to eliminate remaining externally-driven differences What differences should be normalized out within the comparison group? 48

What Characteristics should be used to define similar? Medicare FFS Approach Initially evaluated a wide variety of factors such as demographic, health status, economic and healthcare system (e.g. academic presences) Current Thinking Medicare FFS Population size Population density Median Income Cost of Living (RPP) HCC Scores % Deep Poverty Why These? Less is More Face Validity Co-linearity Research base Data availability/quality Contractor running revised models, the list is not final. Should Private Pay use same benchmark groups? 49

How similar is similar enough? Medicare FFS Approach Most Similar County 1 Least Similar County 3,000 Current Thinking - MC FFS Approach : Top 20 for 5 largest MD counties, 40 for remaining counties. Goal is to allow for performance comparison within a range. Balance similarity with need for a performance range. All 5 large MD counties are in the top 4% nationally for population and density, therefore there are a limited number of potential valid comparisons. Large areas less susceptible to random variation so can limit number of comparison areas. Because closest Maryland cost comparisons are higher cost areas adding more comparisons tends to make Maryland total variation from MC FFS look larger. RTI Approach: Only 2 or 3 most similar comparison points included. Goal was to create a point estimate to compare to Maryland. Not sufficient for intrastate needs 50

What differences should be normalized out within the comparison group? The comparison group is already similar to the target geography by definition. However, where we have accurate metrics we can then adjust to normalize for remaining differences if desirable. Applicable to things that directly impact costs like HCC or wage levels. Currently propose to normalize for HCC scores in MC FFS comparison. Less concern about coding changes that affect year-over-year results. May need to consider other items in private payer work like benefit structure. 51

Additional Slides December 2016 52

Preliminary State Level Outcomes MC FFS 53 Selected Metrics Maryland MC FFS (A+B benes) versus National Using Current Benchmark Groups 1. HCC Adjustment applied to comparison county amounts to match Maryland County HCC 2. IP HCC Adjustment assumed to apply entirely to stays per 1000 3. All costs excluding IP acute and OP hospital costs Outcomes are preliminary. More comprehensive comparison underway. Data derived from CMS Geographic Variation PUF. National comparison reflects simple average of peer group (20 or 40 counties) for each MD county aggregated to a state level based on MD county MC FFS beneficiaries. Further work will include generating this analysis at a county level adding quality measures as well as a complete cost profile.

Options for Geographic Unit of Analysis Zip Code HRR/HSA/PSA County MSA/Geozip Description Hospital Referral Regional and Hospital Service Area are national zip code based hospital service areas definitions similar to MD PSAs. Zip codes can be mapped to county although there is some overlap Metropolitan Statistical Areas (MSA) and Geozip (3-digit zips) are regional aggregations. Match to MD PSAs Can be aggregated to = PSA Conceptually Equivalent Generally larger, match is strong in rural areas less so in suburban and urban Includes multiple hospital PSAs. MC FFS Data Availability Available Build from zip code Available Build from Zip Code Private Payer Data Availability Demographic Data Availability Current Thinking MC FFS Approach Preliminary Employer Commercial Approach Typically unavailable due to data sharing restrictions and data scarcity Potentially available in some areas Potentially available in some areas Available Varies by characteristic Build from zip code Available for most Available Exploring use for Maryland urban areas Primary May use for urban areas May use for urban areas Primary 54

Future meetings TCOC Work Group meetings Feb. 27 March 27 April 24 May 29 June 26 HSCRC Commission meetings March 13 April 10 55

Next meeting: February 27, 2019