Madeleine Schlefer & Dov Marocco

Agenda Overview of Santa Clara Valley Health and Hospital System Center for Population Health Improvement (CPHI) Overview The need for an understanding of high utilizers Lessons learned Next Steps

Santa Clara Valley Health & Hospital System Santa Clara County Santa Clara Valley Health & Hospital System Valley Medical Center Behavioral Health Valley Health Plan Custody Health Public Health Department Emergency Medical System CPHI Collaborative Leadership requires everyone to come to the table around a shared purpose. CPHI has taken on the HUMS project as a way to foster collaborative leadership.

Historical Overview of High User/Super User Programs 10-15 high utilizer programs at various stages High utilizer programs worked off of “lists” that may be outdated Sometimes look at one system or one population Data matching is often done with the help of outside consultants and/or laborious processes Population Health seen as hospital-centric for specific disease states and often only include paneled patients

Center for Population Health Improvement: Overview VISION The CPHI will integrate HHS priorities using data to address social inequities & assist vulnerable populations Major categories of projects Data access & analytics Program planning & evaluation Population health research & assessment Improvement & innovation

High Utilizers of Multiple Systems as Use Case for Enterprise Data Warehouse Target Populations requires knowing and understanding your patients across systems and is a key component of population health. Our plan was sparked by the work of Maria Martinez & and others at the County and City of San Francisco HUMS/CCMS Program We started slowly with just combining behavioral health data with physical health because we had that data accessible. Several brainstorming meetings were required to develop a common definition of high utilizers.

Enterprise Data Warehouse as a Platform for Shared Data Done! Identification of HUMS Patients Epic Data Hospital Data (ED, Inpatient & Urgent Care) Behavioral Health Data (Emergency Psych Services, Acute Psych) Non-Epic Data VHP Claims Data Custody Health Data EMS Data Patient records from all of the systems are matched using a matching system built into the EDW Done! In Progress New Possibility: Import Acute Psychiatric Admission data for Pay 4 Success Part 2 Program Next Priorities

Event Type/Number of Points High User Point System The point system evaluates the number of clinical events for each patient and assigns a number of points for each event. The total number of points for all clinical events in the past 12 months can be used to rank patients from highest to lowest use. By assigning more points to emergency visits, patients who use these services move to the top of the list. Event Type/Number of Points Example Points Inpatient Stay - 1 point per day 5 day stay in defined timeframe = 5 ED Admission - 3 points per event 1 ED event in defined timeframe = 3 Emergency Psych Admission (EPS) - 3 points per event 1 EPS event in defined timeframe Acute Psych care facility (BAP) - 1 point per day 2 day stay at BAP in a defined timeframe = 2 Urgent/Express care - 1 point per event 5 urgent care events in a defined timeframe   = 16

High User Point System Length of Stay points were capped for each inpatient at the 75th percentile. This was done so that the total score of a patient who was in and out of the hospital for multiple inpatient stays would accrue more points than a patient who experienced one, long inpatient stay. Department LOS Cap VMC BAP 400 19 VMC BAP 500 14 VMC Burn Center 12 VMC MICC 7 VMC 4 Med 6 VMC Medical ICU VMC 4 Surg 5 VMC TCNU VMC Trauma ICU VMC 3 Surgical VMC Coronary Care 4 VMC MSSU VMC Surgical 3

High User Point System Validation We are truly capturing high users of multiple systems 80% of the top 100 high users used both mental health and physical health services within our system 50% of the top 1,000 high users used both mental health and physical health services within our system 1% of the general SCVMC patient population uses both health and physical health services This point system captures different patients than if we based high use off of charges 10% of the top 1,000 high users based on the point system are also in the top 1,000 patients based on highest charges 9% of the highest cost patients used both mental health and physical health services The point system will get more robust as we add additional data sources An informal study of a sample of our high users found that roughly 75% of the highest users were accessing emergency services at other hospitals

82 Encounters in 1 Year High Utilizers Sharing Data to support care coordination, program planning and evaluation 57 Encounters in ED 24 Encounter in EPS 1 Encounter in MPC Adult Express Filters Longitudinal Span of Patient Encounter History Gap

Studying High Utilizers to Plan For Whole Person Care Use Patterns of High Users and the Patient Population   Top 1,000 Users SCVMC Population Patients with the highest use of services based on a point system to identify patients utilizing urgent/emergent services All patients with 1 or more in-person visits to hospital or clinic in the past year, excludes those in the column to the left Number of Records 1,000 179,829 % of Patients with ED Visit 94% 32% Avg. # of ED Visits 8.7 0.5 % of Patients with EPS Visit 49% 3% Avg. # of EPS Visits 2.5 0.04 % of Patients with both EPS and ED Visits (emergency visit) 45% 1.3% % of Patients with BAP stay 24% <1% % of Patients with inpatient stay 46% 8% % of patients with behavioral health and physical health visit (ED and/or inpatient + EPS and/or BAP) 50% 1% The highest users access emergency services at a much higher rate than other patients. This suggests a need for programming that addresses these patients’ needs before they determine they need emergency services. The highest users access behavioral health services far more than the general population, suggesting these are high users of multiple service types. The addition of VHP claims data, Behavioral Health data, Custody Health, and EMS data will allow us to know when, why, and how often high utilizers use different parts of our system and other County resources.

Studying High Utilizers to Plan For Whole Person Care

Studying High Utilizers to Plan For Whole Person Care

Studying High Utilizers and Payer Trends for Financial Planning High Users are more likely to be in Medical Managed Care so there is no incentive to keep them as high users.

Data For Program Planning Analysis has shown that while the level of use of the highest users remains relatively constant, the individuals who are the highest users at any given time is changing. Reducing high use of the system means monitoring use of the system as a whole, not use by individuals. To reduce high use of the system we need to identify patients who are about to become high users and intervene early. Regression to the mean How can we identify these patients sooner? Regression to the mean

Coordination of Care Across Sectors Care Coordination and Transitions Program An interdisciplinary team that will identify and engage with SCVHHS high utilizers to ensure clients receive services that are effective in helping them reduce the need for care in an acute, emergency, and/or hospital setting The team’s proposal identified seven new positions including a part-time medical director, a public health nurse, behavioral health specialists, a medical social worker, and others that are needed in order to create an effective team Will assess, stabilize and connect complex clients to community-based care, with a goal of eliminating preventable readmissions and recidivism into acute settings Engage with existing programs to prioritize capacity and resources effectively Augment current efforts by providing staff time, system knowledge, and resources as those needs are identified in the context of care planning with individual clients

Lessons Learned SCVHHS is moving towards being a more integrated system and this unique opportunity for WPC created a clear purpose to jointly develop a standard definition of high utilizers. Matching data is not as hard as it used to be. Epic provides an advantage but other programs are available. The key for us was just to start and run small tests of change. The point system you decide to use can be based on other similar models (Thank you SF) and then adapted for your needs. The size of the high utilizer population and the information you know about them will grow over time. As the requirements grow so will the consideration regarding combining data, issues around data governance, and re-disclosure. Combining behavioral health data can be a sensitive issue but is necessary and can be done; it may be helpful to do this under a Public Health lens. Typically the problem is not getting the data but rather disclosure to others. Our approach with County Counsel is to explain the problem we wanted to solve and ask them how to get there….there is always a way.