Policy and Analytics
How Maryland’s Total Cost Of Care Model Has Helped Hospitals Manage the COVID-19 Stress Test (Health Affairs Blog, October 7, 2020)
By Chris L. Peterson and Dale N. Schumacher
As the COVID-19 pandemic emerged, hospitals have been the centers of care for patients. Maryland’s unique Total Cost of Care model has helped hospitals manage the peaks and troughs of care and reimbursement. “We believe the COVID-19 pandemic represents an important opportunity to assess this global budget model under stress—with implications for future health care financing.”
“How Maryland’s Total Cost Of Care Model Has Helped Hospitals Manage The COVID-19 Stress Test,” Health Affairs Blog, October 7, 2020.DOI: 10.1377/hblog20201005.677034
By Dale N. Schumacher, MD, MPH
The Maryland Total Cost of Care (TCOC) program, one of the nation’s most innovative advanced alternative payment (APM) models, has entered year two. Finance leaders across the nation can benefit from a closer look at how this state-level program works and its implications for the future direction of healthcare financing nationwide.
Under the TCOC program, for the first time, a state under a global budget is accountable for the total cost of care of all Medicare fee-for-service beneficiaries. The program warrants finance leaders’ attention because the innovative way it addresses the challenge of reining in the rising costs of nation’s healthcare system: All Medicare fee-for-service beneficiaries must be attributed to primary care physicians and/or a hospital —whether or not the beneficiary has received services that year. Competing hospitals and systems form geographically based networks to ensure regional and statewide coverage. The Medicare performance adjustment (MPA) tracks each hospital’s total cost of care with a 1% upside or downside incentive. To the extent the program is successful, it could provide a basis for future Medicare reform nationwide.
With its second year, the program has seen its first round of annual update factors and annual performance adjustments. Here we provide a review of the essential elements of this major financing and policy initiative, which is a transformation from Maryland’s earlier hospital All-Payer Model (svee the sidebar on page 54 for details on the evolution of the TCOC Program).
See additional details of essential TCOC elements in full blog article.
Additional Policy Related Activities
- Responding to Federal Register CMS-1715-P request, we provided documentation that the Medicare Spending Per Beneficiary (MSPB) program initiated in 2013 and expanded by IMPACT 2014 supports CMS needs for a rapid start of MIPS Value Pathway (MVP) program. September 27, 2019
- Comments to HSCRC Regarding – Developing National Benchmarks for Maryland Hospital Markets. Medicare Spending Per Beneficiary (MSPB) documents wide efficiency performance ranges among benchmark market area hospitals. Bergen County, NJ at 1.079 was least efficient and Hennepin County, MN at 0.9304 was most efficient. This suggests potential bias in use of benchmark county data when comparing with Maryland counties. April 29, 2019
- Strengthening Clinician Users of CRISP
Measures or approaches include: improve homogeneous grouping; develop frailty measure; enhance physician descriptors; develop coordination of care metrics; develop an ECIP data central; automate physician NPI/TIN lookups; retrospective review to identify physicians providing unnecessary patient care; and begin implementation of patient relationship codes. Establish separate analyses for hospitalists and Primary Care linkages. Internal RI white paper. December 2018
- Maryland Hospital Association – TCOC and Opportunities. The Maryland Agency Model. Need to identify hospital variance and persistent variances and develop clinical interventions with fidelity and impact. August 13, 2018
- Letter to HSCRC re Methodological Observations on Draft Recommendations of the Maryland Health Services Cost Review Commission regarding Hospital Acquired Conditions for 2018 for Rate Year 2020. We explored the impact of low frequency PPCs – did the decreasing frequency result from changed utilization patterns or improved quality? January 10, 2018
- In a DOH Duals ACO (D-ACO) we modeled spillover as a D-ACO program impact. We focused on 2013 Medicare fee for service (FFS) beneficiaries’ transition to Medicaid from Medicare. Conclusion – We projected spillover from improved Duals ACO management would yield an additional $41,000,000 in savings. Our numbers are conservative approximations. We believe spillover is a viable concept and should be refined and included in future duals impact analyses. February 2017
- Primary Care – Schumacher DN, Beilenson PL, Carlson R. Resourcing Primary Care in An Era of Health Care Change – A White Paper Discussing the Challenges and Solutions to Enhance the Availability and Affordability of Quality Primary Care in the Howard County, Maryland Area. February 22, 2010
- Prospective Payment for Psychiatry – Feasibility and Impact (National Policy) -We investigated the ability of the psychiatric DRGs to predict the hospital length of stay and costs by retrospectively analyzing 8816 charts randomly selected patients from 32 hospitals throughout the United States.
- The psychiatric DRGs reduced the total variance in length of stay by 3.9 percent. Our best alternative grouping – based on major diagnostic categories, whether the patient was transferred from another facility, age, and psychiatric complications and comorbidities – reduced the variance by 7.8 percent. DRGs do not adequately predict length of stay or costs in psychiatric hospitals. All models we tested would create large financial “winners” and “losers” and thus introduce inappropriate incentives. NEJM Med 1986; 315:1331-6.
- Hospital Cost Per Case – Analysis Using a Statewide Maryland Data System -We (Schumacher, Horn, Solnick, Atkinson and Cook) established relationships between hospital cost per case and the independent variables: case mix complexity, case mix severity, factor input prices, and hospital characteristics. Two hundred and sixteen thousand discharges from Maryland’s acute general hospitals are grouped into 383 Diagnostic Related Groups which are used to compute an information theoretic measure of case mix complexity. Multiple linear regression equations are developed which predict up to 88% of the variance of between-hospital cost per case. The most highly significant predictors of cost per case are complexity, patient age, proportion of high-risk patients, average length of stay, and nonphysician salary levels. Two distinct groups of hospitals, metropolitan and rural, are defined and models are developed for each. We discuss the implications of these findings for the identification and regulation of unexpectedly high cost hospitals and for prospective cost per case reimbursement. Medical Care October 1979