Al Alter ernate e Paymen ent Model els for Be Behavi vior - - PowerPoint PPT Presentation

Al Alter ernate e Paymen ent Model els for Be Behavi vior

• ral Health

th Servi vices s – Pa Past, Present, and Future Po Policy Ro Roundtable

June 2, 2019 Academy Health Annual Research Meeting Washington D.C.

Presenters

• Andrew D. Carlo, MD
• Senior Research Fellow, University of Washington
• Nicole M. Benson, MD
• Clinical Fellow in Child and Adolescent Psychiatry, Massachusetts General Hospital and McLean Hospital
• Zirui Song, MD, PhD
• Assistant Professor of Health Care Policy and Medicine at Harvard Medical School
• Internal Medicine Physician at Massachusetts General Hospital
• Katherine Hobbs Knutson, MD, MPH
• Chief of Behavioral Health, Blue Cross North Carolina
• Adjunct Assistant Professor in the Department of Psychiatry and Behavioral Sciences, Duke University School
• f Medicine
• Benjamin F. Miller, PsyD
• Chief Strategy Officer for Well Being Trust
• Adjunct Faculty, Stanford University School of Medicine
• Senior Advisor, Eugene S. Farley, Jr. Health Policy Center, University of Colorado School of Medicine

Disclosures

• Andrew D. Carlo, MD
• None
• Nicole M. Benson, MD
• None
• Zirui Song, MD PhD
• None
• Katherine Hobbs Knutson, MD MPH
• BCBS Employee
• Benjamin F. Miller, PsyD
• None

Outline

• Define alternative payment models (APMs)
• Review existing behavioral health APM literature
• Results from commercial payer accountable care organization (ACO)
• Discussion of alternate payment for behavioral health integration
• Description of APM within an ACO
• Discussion of Future Directions

Alternative Payment Models (APMs)

• Payment models with incentive payments tied to quality and

value

• Apply to a specific clinical condition, care episode, or population
• Heterogeneous, divided into groups by payment (fee-for-

service or population-level) and category of risk (none, penalties, bonuses, or both)

• APMs ideally align system-, practice-, and provider-level

incentives to facilitate higher quality, integrated, and more cost-effective health care

State of the Field

• Paucity of literature empirically evaluating the impacts of APMs on

MH/SUD outcomes

• Long history of studying other payment models not tied to quality/value
• Existing literature with mixed findings
• Most commonly evaluated APMs included P4P, condition-specific

population payments and shared savings with one- or two-sided risk

• Strongest findings in processes-of-care, fidelity, utilization and

spending outcomes

• Clinical outcome data are lacking

APM Mental Health Examples

• P4P for Washington State’s Mental Health Integration Program (MHIP)
• P4P patients had a significantly higher likelihood of having (Bao et al, 2017):
• At least one follow-up contact
• At least one psychiatric case review
• At least one PHQ-9
• P4P patients also (Unützer et al, 2012):
• Were more likely to receive timely follow-up
• Had more rapid depression symptom improvement
• Had a higher likelihood of achieving treatment response.

APM Mental Health Examples

• Maine Addiction Treatment System (MATS) – condition-specific

population payment

• APM WAS associated with higher odds of successful matching with a treater,

higher odds of referral, and a higher likelihood of receiving effective and efficient care (Lu et al, 2003; Commons et al, 1997)

• APM NOT associated with significant changes in time to outpatient

assessment or time to treatment (Brucker et al, 2011)

• APM WAS associated with possible adverse selection and gaming (Shen et al,

2003; Lu et al, 2002; Lu et al, 2006)

APM Mental Health Examples

• Medicare Shared Savings Program:
• Initially, one-sided risk only
• NO significant differences in process-of-care outcomes, health care spending,

service utilization, or adverse selection (Busch et al, 2015)

• Slight changes in amount of antidepressants prescribed (Busch et al, 2016)
• Medicare Pioneer ACO:
• Two-sided risk
• Slight reduction in total mental health spending in the first year ONLY (Busch

et al, 2015)

• Slight changes in amount of antidepressants prescribed (Busch et al, 2016)
• Some evidence for adverse selection (Busch et al, 2015)

AcademyHealth Annual Research Meeting June 2019

Zirui Song, MD, PhD Harvard Medical School Massachusetts General Hospital

2007 2008 2009 2010 2011 2012

Health care reform: individual mandate & insurance exchanges Blue Cross Blue Shield of Massachusetts Alternative Quality Contract: 7 organizations join in 2009, 4 more organizations join in 2010. By 2012, 613,000 enrollees are in the AQC. Medicare Pioneer ACOs: 5 provider organizations with 150,000 beneficiaries. State Cost Control Legislation: (1) Global payment (2) Accountable Care Organizations (3) Regulation of insurance premiums (4) Medical malpractice reform Special state Commission: global payment within 5 years Tufts Health Plan and Harvard Pilgrim Health Care announce plans to expand global payment. Insurance coverage expands to over 97%

• f the state population

Attorney General reports: variations in provider payments

• Figure. Health care reform in Massachusetts

State Senate bill & State House bill: Global payment

Payment Reform in Massachusetts

Governor Patrick Signs Health Care Cost Containment Bill August 6, 2012 “Massachusetts has been a model for access to health care. Now, we become the first to crack the code on costs.”

• ACO model (5 years)

– MDs and hospitals – Continuum of care

• Spending growth controls

– Global budget (2-sided model) – Budget growth benchmarks – Shared savings & risk tied to quality

• Pay-for-Performance

– 64 quality metrics (process, outcome, experience) – Large financial incentives: up to 10% of budget

Alternative Quality Contract (AQC)

Accountability for Spending

฀฀฀ ฀฀฀฀ ฀฀฀฀฀ ฀฀฀฀฀฀ ฀฀ ฀฀฀ ฀฀฀฀ ฀฀฀ ฀฀฀฀ ฀฀

฀ ฀ ฀ ฀ ฀

฀฀฀฀

Last year This year Next year Spending

• 1-sided

ACO

฀฀฀฀฀

2-sided ACO — Penalty Reward Reward

} }

฀

• ฀
• ฀
• Target

Ambulatory Measures

Measure Gate 1 Gate 5 Weight Depression 1 Acute Phase Prescription 65.3 80.0 1.0 2 Continuation Phase Prescription 49.6 70.0 1.0 Diabetes 3 Hemoglobin A1c Testing 69.9 83.2 1.0 4 Eye Exam 58.0 72.1 1.0 5 Nephropathy Screening 79.7 91.4 1.0 Cholesterol Management 6 Diabetes LDL-C Screening 85.3 93.8 1.0 7 Cardiovascular LDL-C Screening 85.3 93.8 1.0 Preventive Screening/Treatment 8 Breast Cancer Screening 77.1 90.0 1.0 9 Cervical Cancer Screening 83.5 92.4 1.0 10 Colorectal Cancer Screening 65.2 83.3 1.0 Chlamydia Screening 11 Ages 16-20 45.9 63.7 0.5 12 Ages 21-24 50.1 67.3 0.5 Adult Respiratory Testing/Treatment 13 Acute Bronchitis Reporting Only 2009, 2010 1.0 Medication Management 14 Digoxin Monitoring 83.9 91.6 1.0 Pedi: Testing/Treatment 15 Upper Respiratory Infection (URI) 90.6 97.7 1.0 16 Pharyngitis 83.1 99.6 1.0 Pedi: Well Care Visits 17 First 15 Months of Life 91.8 99.3 1.0 18 3-6 Years of Age 85.5 99.2 1.0 19 Adolescent Well Care Visits 60.0 87.7 1.0 Diabetes 20 HbA1c in Poor Control 45.0 4.7 3.0 21 LDL-C Control (<100mg) 33.4 75.6 3.0 22 Blood Pressure Control (130/80) 30.9 47.3 3.0 Hypertension 23 Controlling High Blood Pressure 71.6 82.5 3.0 Cardiovascular Disease 24 LDL-C Control (<100mg) 33.4 75.6 3.0

Outcome Measures Process Measures

Quality

2006-2016 Claims 2007-2016 Quality

Changes in Health Care Spending and Quality 4 Years into Global Payment

Zirui Song, M.D., Ph.D., Sherri Rose, Ph.D., Dana G. Safran, Sc.D., Bruce E. Landon, M.D., M.B.A., Matthew P. Day, F.S.A., M.A.A.A., and Michael E. Chernew, Ph.D.

n engl j med 371;18 nejm.org october 30, 2014

By Colleen L. Barry, Elizabeth A. Stuart, Julie M. Donohue, Shelly F. Greenfield, Elena Kouri, Kenneth Duckworth, Zirui Song, Robert E. Mechanic, Michael E. Chernew, and Haiden A. Huskamp

The Early Impact Of The ‘Alternative Quality Contract’ On Mental Health Service Use And Spending In Massachusetts

Mental Health Exhibit 2

Adjusted Annual Probability Of Use And Average Spending By Blue Cross Blue Shield Of Massachusetts (BCBSMA) Enrollees In The Comparison And Alternative Quality Contract (AQC) Groups Across Person-Years, 2006–11 With AQC Without AQC Difference 95% CI Probability of mental health use 16.04% 17.45% −1.41%*** (−2.06, −0.76) Behavioral health risk 15.21 17.30 −2.09*** (−3.29, −0.99) No behavioral health risk 17.14 17.30 −0.16 (−1.27, 0.95) Average mental health spending conditional on mental health use $3,063 $3,078 −$15 (−61, 91) Behavioral health risk 3,030 3,056 −26 (−126, 75) No behavioral health risk 3,134 3,056 78 (−51, 208) Average total health care spending conditional on mental health use $8,137 $8,316 −$189** (−368, −9) Behavioral health risk 8,078 $8,316 −238** (−468, −9) No behavioral health risk 8,207 8,316 −109 (−300, 81)

SOURCE BCBSMA claims data, 2006–11. NOTES Two-part models adjusted for sex, age category, risk score, year, and AQC cohort and estimated using propensity score

• weights. Cost estimates have been adjusted for inflation. Difference-in-differences estimation used to account for secular trends. CI is confidence interval.

**p < 0:05 ***p < 0:01

• Slightly less likely to use

mental health services

• Conditional on mental

health service use, small decline in total spending but no difference in mental health spending

• Effects concentrated in
• rgs with financial risk

for behavioral health

Health Affairs. 2015;34(12):2077-85.

Among organizations that took on risk for behavioral health, no effects on:

• Prob of SUD service use
• SUD spending
• SUD performance metrics

(identification, initiation, and engagement)

• Addiction. 2017;112(1):124-133.

Effects of Global Payment and Accountable Care on Tobacco Cessation Service Use: An Observational Study

Haiden A. Huskamp, PhD1, Shelly F. Greenfield, MD, MPH2,3, Elizabeth A. Stuart, PhD4, Julie M. Donohue, PhD5, Kenneth Duckworth, MD6, Elena M. Kouri, PhD1, Zirui Song, MD, PhD7, Michael E. Chernew, PhD1, and Colleen L. Barry, PhD, MPP4

Table 2. Probability of Tobacco Cessation Treatment Use With and Without AQC Across Person-years, 2006–2011 With AQC Without AQC Difference p value [95 % Conf. Interval] Overall Population Probability of any tobacco cessation treatment use (%) 2.02 % 1.87 % 0.13 % <0.0001 0.09 to 0.21 Probability of varenicline or bupropion use (%) 1.60 % 1.51 % 0.09 % 0.001 0.04 to 0.15 Probability of nicotine replacement therapy use (%)* 0.14 % 0.15 % −0.01 % 0.26 −0.03 to 0.01 Probability of tobacco cessation counseling visit use (%) 0.43 % 0.33 % 0.10 % <0.0001 0.07 to 0.12 Probability of combination therapy use (%) 0.13 % 0.10 % 0.03 % <0.0001 0.01 to 0.04 Probability of ≥90 day supply of tobacco cessation pharmacotherapy,† among users (%) 10.42 % 10.11 % 0.31 % 0.54 −0.70 to 1.34 Probability of >1 counseling visit, among counseling visit users (%) 21.82 % 19.89 % 1.93 % 0.21 −1.05 to 4.86 Population at Risk for Smoking-Related Complications Probability of any tobacco cessation treatment use (%) 4.97 % 4.66 % 0.31 % 0.03 0.02 to 0.58 Probability of varenicline or bupropion use (%) 3.85 % 3.67 % 0.18 % 0.19 −0.09 to 0.43 Probability of nicotine replacement therapy use (%)* 0.47 % 0.52 % −0.05 % 0.28 −0.15 to 0.04 Probability of tobacco cessation counseling visit use (%) 1.17 % 0.86 % 0.31 % <0.0001 0.16 to 0.41 Probability of combination therapy use (%) 0.39 % 0.28 % 0.11 % 0.003 0.03 to 0.17 Probability of ≥90 day supply of tobacco cessation pharmacotherapy,† among users (%) 11.85 % 12.73 % −0.88 % 0.41 −3.05 to 1.25 Probability of >1 counseling visit, among counseling visit users (%) 28.53 % 27.79 % 0.74 % 0.81 −5.37 to 6.83 Behavioral Health Service Users Probability of any tobacco cessation treatment use (%) 3.67 % 3.25 % 0.42 % <0.0001 0.22 to 0.60 Probability of varenicline or bupropion use (%) 2.98 % 2.61 % 0.37 % <0.0001 0.17 to 0.53 Probability of nicotine replacement therapy* use (%) 0.34 % 0.33 % 0.01 % 0.76 −0.54 to 0.07 Probability of tobacco cessation counseling visit use (%) 0.78 % 0.55 % 0.23 % <0.0001 0.13 to 0.29 Probability of combination therapy use (%) 0.29 % 0.17 0.12 % <0.0001 0.05 to 0.14 Probability of ≥90 day supply of tobacco cessation pharmacotherapy,† among users (%) 16.94 % 17.40 % −0.46 % 0.70 −2.84 to 1.91 Probability of >1 counseling visit, among counseling visit users (%) 25.32 % 22.82 % 2.50 % 0.42 −3.58 to 8.51 All significant findings are robust to adjustment for multiple comparisons using the Benjamini-Hochberg (1995) approach to control the false discovery

J Gen Intern Med. 2016;31(10):1134-40.

TABLE 3. Adjusted Annual Changes in Any Use of Medication Treatment for Addiction Among Adults With Opioid Use and Alcohol Use Disorders

AQC Comparison Difference 95% CI P Adjusted rates of use Opioid use disorder 38.7% 39.1% 0.4% 3.8 to 3.0% 0.82 Alcohol use disorder only 6.3% 6.5% 0.2% 1.3 to 0.8% 0.64

TABLE 4. Adjusted Annual Changes in Number of 30-day Prescriptions for Medication Treatment for Addiction for Adults With Opioid Use Disorders and Alcohol Use Disorders

AQC Comparison Difference 95% CI P Full sample Number of prescriptions filled Opioid use disorder 3.10 3.19 0.09 0.63 to 0.44 0.73 Alcohol use disorder only 0.64 0.64 0.00 0.18 to 0.18 0.97 Only enrollees with any use Number of prescriptions filled Opioid use disorder 9.10 8.99 0.11 0.57 to 0.80 0.75 Alcohol use disorder only 6.98 7.28 0.30 1.37 to 0.75 0.57

TABLE 5. Adjusted Annual Changes in Spending on Medication Treatment Conditional on Any Use for Adults With Opioid Use Disorders and Alcohol Use Disorders

AQC Comparison Difference 95% CI P Annual spending Opioid use disorder $2807 $2758 $49 $227 to 325 0.73 Alcohol use disorder only $1053 $942 $111 $134 to 356 0.37

Effects of Global Payment and Accountable Care on Medication Treatment for Alcohol and Opioid Use Disorders

ORIGINAL RESEARCH

No differential change:

• Any use of MAT
• 30-day prescriptions
• Spending on MAT

Donohue JM, Barry CL, Stuart EA, Greenfield SF, Song Z, Chernew ME, Huskamp HA J Addict Med. 2018;12(1):11-18.

Financing and sustaining integrated primary care

Benjamin F. Miller, PsyD @miller7 Chief Strategy Officer Well Being Trust

2

Our problem and our solution

2

Mental Health

Medical

Kathol, R. G., Butler, M., McAlpine, D. D., & Kane, R. L. (2010). Barriers to Physical and Mental Condition Integrated Service Delivery. Psychosom Med, 72(6), 511-518.

3

Payment Reform

• Financial issues cited as the #1 barrier to integrating

care1

• There is life beyond FFS – unlearning the old ways may

be hard

1Kathol, R. G., Butler, M., McAlpine, D. D., & Kane, R. L. (2010). Barriers to Physical and Mental Condition Integrated Service Delivery. Psychosom Med, 72(6), 511-518.

4

5

• Sustaining Healthcare Across integrated Primary care

Efforts

• A partnership between Collaborative Family Healthcare

Association, Rocky Mountain Health Plans, Colorado Health Foundation, and University of Colorado School of Medicine Department of Family Medicine

• To evaluate a global payment model to sustain behavioral

health in primary care

6

• To test a different payment method to financially

support and sustain behavioral health in primary care;

• Any and all patients who present to primary care with

behavioral health need

• Primary care practices predominately consist of family

medicine/internal medicine (pediatric practices coming on now)

• To test the real world application of a novel payment

methodologies on novel primary care practices who have integrated behavioral health with the end goal to inform policy.

The set up

7 Sunrise Mountain Family MidValley Foresight Primary Care Partners Axis

Experimental

• Foresight
• Mountain

Family

• Primary Care

Partners Intervention

• MidValley
• Axis
• Sunrise

8

Results

Raw frequencies (n) Patients (n) pre post InterventionForesight 5064 5926 Mountain Family** 6674 10141 Primary Care Partners^ 5422 7316 Intervention 17160 23383 Control MidValley 1183 1023 Axis 207 378 Sunrise** 10149 12543 Control 11539 13944

8

8.0% 5.6% 12.8% 6.1% 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% 12.0% 14.0% Intervention Control

Percentages of Eligible Patients with Depression Diagnosis within Pre and/or Post intervention

*OR:1.5 (95%CI: 1.41, 1.57), p-value <0.0001

Pre % Post % 5.1% 4.2% 7.9% 5.2% 0.0% 2.0% 4.0% 6.0% 8.0% 10.0% Intervention Control

Percentages of Eligible Patients with Anxiety Diagnosis Unique to Pre or Post intervention *OR:

OR:1.48 (95%CI: 1.39, 1.58), p-value <0.0008

Pre % Post % 3.5% 2.9% 4.9% 3.8% 0.0% 1.0% 2.0% 3.0% 4.0% 5.0% 6.0% Intervention Control

Percentages of Eligible Patients with Substance Abuse Diagnosis *OR: 1.4 (95% CI: 1.27, 1.49) p-value

0.40

Pre % Post %

9

• Substantial, independently evaluated total cost of care differentials
• Normalized for differences in population, demographics, risk and price

Comprehensive Care = Cost Savings

Medicaid Medicare

• 5.5%
• 3.0%
• 5.4%

Medicare-Medicaid Beneficiaries

• 4.8%

Combined cost savings

Ross, K. M., Gilchrist, E. C., Melek, S. P., Gordon, P. D., Ruland, S. L., & Miller, B. F. (2018). Cost savings associated with an alternative payment model for integrating behavioral health in primary care. Translational Behavioral Medicine, iby054-

• iby054. doi:10.1093/tbm/iby054

10

Payment recommendations

• This is not about changing the way we pay for

behavioral health; this is about changing the way pay for primary care that includes behavioral health

• Make sure the delivery setting is getting paid by

keeping the patient healthy, not per patient visit (e.g. move as quickly as possible away from fee for service)

• Make sure there are incentives in place to

encourage primary care clinicians to work with behavioral health (e.g. hold them accountable for certain behavioral health conditions)

11

Additional considerations

• How can the population be stratified by severity (e.g.

SPMI vs mild/moderate)?

• Measurement (e.g. how many more people were seen, at

what cost, and where?)

• How is care financed to support model? How do

payment models limit what can done in practice?

• What are the minimal training

requirements/competencies based upon setting?

• How are social determinants factored in?
• How is information shared across the community?

12

Thanks!

• ben@wellbeingtrust.org

@miller7

• www.makehealthwhole.org

12

Confidential and Proprietary – Not for Distribution

Alternative payment models for behavioral health

Academy Health Annual Research Meeting June 2, 2019 Katherine Hobbs Knutson, MD MPH Chief of Behavioral Health, Blue Cross North Carolina Adjunct Assistant Professor, Duke University School of Medicine

2 Confidential and Proprietary – Not for Distribution

Disclosures

None.

3 Confidential and Proprietary – Not for Distribution

Topics for discussion Objective: Describe a developing alternative payment model for behavioral health. Agenda Behavioral health in ACOs Blue Cross NC BH APM Summary Blue Cross NC ACO

Confidential and Proprietary – Not for Distribution

Blue Cross North Carolina ACO model

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Changing How We Pay for Care

Fee-for- Service

Performance Based Incentives

Bundled / Episode Payments Capitation

Quality Outcomes Total Cost of Care Health Event Level

Shared Savings Shared Risk

Accountable Care Organizations: Total Cost of Care Member Level

Degree of Provider Accountability

Innovations in Value-Based Care and Payment Models

Value-Based Continuum

Blue Premier continues the shift toward total accountability Level of Provider Financial Risk

6 Confidential and Proprietary – Not for Distribution

Blue Premier: ACO/Health System Payment Model

7 Confidential and Proprietary – Not for Distribution | 7

NETWORK STRATEGY

Multipronged Focus

Blue Premier

Outcomes-Based Reimbursement

+ Large Health Care Systems

808,000*

MEMBERS

70,000–80,000**

MEMBERS

Independent Primary Care

+ Non-system affiliated + PCP & multispecialty

Advanced Primary Care

+ Partnership with vendor(s) to expand primary care base across state

12,000–20,000**

MEMBERS

Confidential and Proprietary – Not for Distribution

Behavioral health in the context of ACOs

9 Confidential and Proprietary – Not for Distribution

Behavioral health disorders drive total healthcare spending.

In the United States, for individuals with behavioral health disorders across all lines of business, total medical expenses are higher by an average of $875 pmpm compared to those without behavioral health disorders.

SOURCE: Melek, Stephen and et al. Potential economic impact of integrated medical-behavioral healthcare. [Online] Jan.2018. http://www.milliman.com/uploadedFiles/insight/2018/Potential-Economic-Impact-Integrated- Healthcare.pdf

Prevalence and total cost of care by line of business (national estimates) 681 1,278 1,214 875 500 1,000 1,500 Medicaid Medicare Commercial Average 17 9 25 16 10 20 30 % population, Percentage with BH disorders Delta vs. No BH, $

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Behavioral health disorders drive total healthcare spending.

There is an estimated 9%-17% annual savings opportunity attainable through integration of physical and behavioral health care.1

SOURCE: Melek, Stephen and et al. Potential economic impact of integrated medical-behavioral healthcare. [Online] Jan.2018. http://www.milliman.com/uploadedFiles/insight/2018/Potential-Economic-Impact-Integrated- Healthcare.pdf

Higher total medical expenses for individuals with behavioral health disorders are driven by spending on physical health conditions.

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Behavioral health treatment is effective, but access to care is limited.

NAMI mental health facts in America https://www.nami.org/nami/media/nami-media/infographics/generalmhfacts.pdf

Treatment in America 100 60 20 40 80 Use of mental health services Nearly 60% of adults with mental health disorders did not receive mental health services in the previous year.4 Nearly 50% of youth aged 8-15 years with mental health disorders did not receive mental health services in the previous year.1 African American & Hispanic Americans used mental health services at about ½ the rate of Whites in the past year and Asian Americans at about 1/3 the rate.1

60% 50%

Whites African Americans Hispanic Americans Asian Americans

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Opportunity

Given the burden of behavioral health on total health and cost, when health systems are accountable for population health and reductions in total cost of care through value-based reimbursement structures, they have increased incentive to focus on behavioral health.

Confidential and Proprietary – Not for Distribution

Blue Cross NC behavioral health APM

14 Confidential and Proprietary – Not for Distribution

Key components of behavioral health systems that add value within ACOs.

• 1. Integrated behavioral health and primary care.
• 2. High performing

behavioral health specialists that a) provide consultation for primary care providers and b) treat individuals with severe mental health and substance use disorders.

• 3. Case management across the continuum and between levels of care.
• 4. Accountability for total health and cost outcomes across the continuum.

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Behavioral Health Strategy: Key Transformational Activities

Optimized behavioral health network Integrated behavioral and physical health Best-in-class solutions

▪

Provide practice support for ACOs and independent providers to integrate behavioral and physical health services.

▪

Drive implementation of Quartet that enables integrated care.

▪

Incorporate the HEDIS measure Depression screening and follow up for adolescents and adults into ACO contracts with financial risk by 2022 to incentivize delivery of integrated care.

▪

Develop an alternative payment model for Behavioral Health

–

Basic: Higher FFS rates for improved quality and access.

–

Advanced: Prospective payments tied to quality for an attributed population.

▪

Recruit (within state and/or nationally) behavioral health specialists to provide both in- person and telehealth/tech-enabled services.

▪

Outpatient treatment for substance use disorders.

▪

Substance use residential treatment centers (RTCs).

▪

Integrated care.

▪

Telehealth and digital Cognitive Behavioral Therapy (CBT).

▪

Case management for serious mental illness and substance use disorders.

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Key Transformational Activities: Optimized network

▪ Develop a value-based payment model for behavioral health

– Basic: New foundation for network providers linking fee-for-service payments to

quality.

– Advanced: Prospective payments tied to quality for an attributed population. ▫ Includes payment for team-based care, consultation to primary care, and the case

management functions necessary to help members engage in outpatient treatment and reduce avoidable use of ED and inpatient services.

▪ Recruit (within state and/or nationally) high-performing behavioral health

specialists to provide both in-person and telehealth/tech-enabled services.

17 Confidential and Proprietary – Not for Distribution

Blue Cross NC behavioral health APM

Basic APM Advanced APM Population Mental health & SUD Mental health & SUD Attribution Patient panel Blue Premier health system and/or geography Functions Treatment only Treatment, consultation to primary care, case mgmt. Size Any size Large practice Payment method FFS+bonus Prospective Risk None Prospective payment at risk based on total cost of care Outcome measures Process, clinical, and patient experience. Process, clinical, patient experience, and cost/utilization

18 Confidential and Proprietary – Not for Distribution

Outcome measures

Basic APM Performance Measures

1 Access: Meeting standards for outpatient behavioral health services (24h acute, 72h urgent, 14d non-urgent, measured via Quartet) 2 PCP Integration: Frequency of behavioral health provider communication with primary care (measured via Quartet)

MH Only SUD only

3 BH NCQA, HEDIS Diabetes and CVD screening and monitoring for people with schizophrenia or bipolar disorder (SSD, SMD, SMC) HIV screening rates for individuals with substance use disorders 4 HEDIS Adherence to antipsychotic medications for individuals with schizophrenia (SAA) Hep C screening rates for individuals with substance use disorders 5 BH NCQA, HEDIS Metabolic monitoring for children and adolescents on antipsychotics (APM) Rate of initiation of buprenorphine or methadone for individuals with opioid use disorders 6 American Psychiatric Association level 1 cross cutting measures for adults and youth. Adherence rate for buprenorphine or methadone for individuals with opioid use disorders 7 HEDIS Initiation and engagement of alcohol and other drug abuse or dependence treatment (IET)

19 Confidential and Proprietary – Not for Distribution

Outcome measures

Basic APM Performance Measures

1 Access: Meeting standards for outpatient behavioral health services (24h acute, 72h urgent, 14d non-urgent, measured via Quartet) 2 PCP Integration: Frequency of behavioral health provider communication with primary care (measured via Quartet)

MH Only SUD only

3 BH NCQA, HEDIS Diabetes and CVD screening and monitoring for people with schizophrenia or bipolar disorder (SSD, SMD, SMC) HIV screening rates for individuals with substance use disorders 4 HEDIS Adherence to antipsychotic medications for individuals with schizophrenia (SAA) Hep C screening rates for individuals with substance use disorders 5 BH NCQA, HEDIS Metabolic monitoring for children and adolescents on antipsychotics (APM) Rate of initiation of buprenorphine or methadone for individuals with opioid use disorders 6 American Psychiatric Association level 1 cross cutting measures for adults and youth. Adherence rate for buprenorphine or methadone for individuals with opioid use disorders 7 HEDIS Initiation and engagement of alcohol and other drug abuse or dependence treatment (IET)

HE DIS Mental health utilization (MP T, includes inpatient, IOP , PHP, outpatient, E D, telehealth) HE DIS Follow-up after hospitalization for mental illness (FUH) HE DIS Follow-up after E mergency Department visit for mental illness (FUM) HE DIS Identification of alcohol and other drug services (IAD, includes inpatient, IOP, P HP , E D, telehealth) HE DIS Follow-up after E mergency Department visit for alcohol & other drug abuse or dependence (FUA) HE DIS Initiation and engagement of alcohol and other drug abuse or dependence treatment (IE T)

Additional cost/utilization measures for advanced APM:

Confidential and Proprietary – Not for Distribution

Conclusion

21 Confidential and Proprietary – Not for Distribution

Summary

With ACOs, there is an enhanced

• pportunity for

focus on behavioral health. Developing financial models to incentivize effective behavioral health treatment is important.

1 2 3

Challenges include outcome measurement, attribution models, and levels of risk for providers.

Discussion