INNOVATION VAL ALUE UE Implementing Behavioral Health Homes to Improve Patient- Centered Outcomes for Adults with Serious Mental Illness June 25, 2017 Cara Nikolajski, MPH; James Schuster, MD, MBA; Patricia Schake, MSW, LSW; Tracy Carney; Charles Reynolds, MD; Chaeryon Kang, PhD; Jane Kogan, PhD; Michele Mesiano, MSW
Presentation overview • The role of a payer in supporting changes in care delivery across a network of community mental health centers • Overview of two system-level models of care aimed at improving the health of adults with serious mental illness (SMI) who are at high risk for chronic disease • Patient-centered comparative effectiveness research (PC- CER) study conducted to evaluate the impact of the two models on patient-centered outcomes • Next steps: analyses and dissemination 2
UPMC Insurance Services Division (ISD) & UPMC Center for High-Value Health Care (Center) • UPMC Center for High- Value Health Care – Non-profit research division of the UPMC ISD – Evaluates and translates UPMC’s work into evidence - based practice and policy change – Work supported through grants/contracts and conducted in partnership with patients and family members, community organizations, researchers, and government agencies 3
Community Care Behavioral Health • Largest nonprofit behavioral health managed care organization in the country and largest insurance provider of Pennsylvania Medicaid beneficiaries for behavioral health services • Manages behavioral health services for nearly 1 million members in 39 of 67 PA counties • Works closely with their large provider network including community mental health centers (CMHC) to deliver comprehensive, recovery- oriented, services 4
Challenges faced by community mental health centers • Resource and care delivery limitations due to financial-, personnel-, and policy-related barriers • Often a frequent or the only point of contact with healthcare system for vulnerable individuals with serious mental illness (SMI) • Individuals with SMI experience or are at risk for a range of challenges, including physical health comorbidities, making behavioral/physical healthcare integration critically important within the CMHC setting 5
Morbidity and mortality among individuals with SMI • Impacts approximately 4% of the U.S. adult population (9.8 million individuals) annually • Decreased life expectancy of up to 25 years compared to general population • Physical comorbidities greatly contribute to this disparity – Increased rates of cardiovascular disease and metabolic syndrome compared to general population • Key contributors to morbidity/mortality – Heavy tobacco use – Metabolic effects of atypical antipsychotic medications – Access to care – Untreated health conditions – Poor diet – Sedentary lifestyle References: NIMH, 2015: https://www.nimh.nih.gov/health/statistics/prevalence/serious-mental-illness-smi-among-us-adults.shtml Parks, 2006 https://www.nasmhpd.org/sites/default/files/Mortality%20and%20Morbidity%20Final%20Report%208.18.08.pdf 6
Creating behavioral health home models to support integrated care delivery in CMHCs • Community Care, providers, and other stakeholders developed behavioral health home (BHH) model in 2010 with a focus on: – Enhancing capacity of behavioral health providers to serve as health homes – Comprehensive care management – Care coordination and health promotion – Linkage of service-users to community resources • To promote model scaling, needed to understand how a less resource intensive BHH focusing on disease self-management resources compared to a nurse-supported BHH with a more formalized consultation and care coordination focus – Provided the basis for our CER study supported with funding from the Patient-Centered Outcomes Research Institute (PCORI) • Stakeholder input obtained to inform all elements of the research process (research questions, study design, implementation, analysis, dissemination) 7
Using CER to Examine Impact of the Behavioral Health Home Models 8
Study Methods and Design • Cluster-randomized design with mixed methods approach • Models implemented in 11 community mental health centers (CMHC) over 2 years starting in 2013 • Research participant inclusion criteria: – Medicaid enrolled – 21+ years of age – Diagnosed with a serious mental illness – Receives services at community mental health center within Community Care’s network • Institute for Healthcare Improvement’s Learning Collaborative Model used to support implementation Reference: Institute for Healthcare Improvement Breakthrough Series: http://www.ihi.org 9
Enrollment in CER Study 11 provider sites Provider- Self-Directed Care randomized Supported Care (6 sites) (5 sites) Eligible: n=632 Eligible: n=811 Site 1: 97 (15.3%) Site 1: 87 (10.7%) Site 2: 127 (20.1%) Site 2: 135 (16.6%) Site 3: 91 (14.4%) Site 3: 49 (6.0%) Site 4: 67 (10.6%) Site 4: 350 (43.2%) Site 5: 134 (21.2%) Site 5: 190 (23.4%) Site 6: 116 (18.4%) Enrolled: n=516 Enrolled: n=713 Site 1: 55 (57.6%) Site 1: 83 (95.4%) Site 2: 112 (88.2%) Site 2: 114 (84.4%) Site 3: 78 (85.7%) Site 3: 27 (55.1%) Site 4: 40 (59.7%) Site 4: 313 (89.4%) Site 5: 133 (99.3%) Site 5: 176 (92.6%) Site 6: 98 (84.5%) 10
Who participated in the research? Provider-Supported Self-Directed Total Characteristic N % N % N % Total 713 58.0% 516 42.0% 1,229 100% Age (mean/range) 43.47 19-72 42.37 18-76 43.01 18-76 Gender Female 428 60.0% 341 66.1% 769 62.6% Male 285 40.0% 175 33.9% 460 37.4% Race White 622 87.2% 487 94.4% 1104 90.2% Black 72 10.1% 21 4.1% 93 7.6%% Other 19 2.7% 8 1.6% 27 2.2% Ethnicity Non-Hispanic 710 99.6% 512 99.2% 1222 99.4% Hispanic 3 0.4% 4 0.9% 7 0.6% Diagnosis MDD 227 31.8% 234 45.3% 461 37.5% Bipolar 193 27.1% 137 26.6% 330 26.9% Schizoaffective 131 18.4% 64 12.4% 195 15.9% Schizophrenia 86 12.1% 40 7.8% 126 10.3% Other 67 9.4% 31 6.0% 98 8.0% None 9 1.3% 10 1.9% 19 1.5% 11
Patient-centered outcomes & data sources 12
Data collection & completion Provider- 11 provider sites Self-Directed Care Supported Care (6 sites) randomized (5 sites) Eligible: n=632 Eligible: n=811 Enrolled: n=516 Enrolled: n=713 Data Collection Loss to Follow-Up Data Collection Loss to Follow-Up (Cumulative) (Cumulative) TP1: self-report n=514; claims n=441 N/A TP1: self-report n=713; claims n=649 N/A TP2: self-report n=337; claims n=456 15 (2.9%) TP2: self-report n=552; claims n=652 23 (3.2%) TP3: self-report n=282; claims n=448 41 (7.9%) TP3: self-report n=489; claims n=619 49 (6.9%) TP4: self-report n=269; claims n=420 71 (13.8%) TP4: self-report n=437; claims n=601 73 (10.2%) TP5: self-report n=220; claims n=310 88 (17.1%) TP5: self-report n=386; claims n=582 102 (14.3%) 13
Overview of study findings 14
Patient activation improved in both study arms but at different times and differed by gender • Why patient activation? – Measures an individuals level of engagement in their own health care using Patient Activation Measure – A single point increase in PAM score correlates to a 2% decrease in hospitalization and 2% increase in medication adherence • Our findings: – Provider-Supported led to more immediate and stable improvement in patient activation (significant treatment X time interaction observed; p<0.0001) – Subgroup analysis revealed that male gender associated with a greater improvement in Self-Directed arm and female gender associated with faster and greater improvement in patient activation in the Provider-Supported arm Reference: Insignia Health: http://www.insigniahealth.com/ 15
Perceived mental health status improved and perceived physical health status declined • Why health status? – SF-12 used to measure perceived physical and mental health status – Even a small score change can impact mortality rates and other health-related factors • Our findings: – Mental health status score increased, particularly at month 6 (p<0.0001) – Physical health status score decreased over time, particularly after month 12 (p<0.0001) Reference: Bjorner, 2013 16
Engagement in primary/specialty care increased significantly in both arms • Why engagement in primary/specialty care? – Annual mean # of primary/specialty care visits measured using claims data – Increased rates of primary/specialty care utilization can lead to increased receipt of preventive and treatment measures • Our finding: – While the two interventions did not differ significantly in their impact on this outcome, both showed improvement over time (p<0.0001) References: Druss, 2001; Banta, 2009 17
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