Improving Care Transitions from Inpatient Psychiatric Settings Alan Podawiltz, DO Chair of Psychiatry, JPS Health Network Chair of Psychiatry, University of North Texas Health Sciences Center Wayne Young, MBA, LPC, FACHE Senior Vice President, Behavioral Health

Learning Objectives Learning Objective #1: Participants will be able to describe one approach to utilizing data and risk stratification to improve outcomes in behavioral health populations.  Learning Objective #2:  Participants will be able to discuss 5 strategies of pre-and post-discharge engagement that contributes to improved care transitions. Learning Objective #3: Participants will be able to identify 3 benefits to involving people to disease specific lived experience as a part of care transitions

BEHAVIORAL HEALTH @ JPS

JPS Behavioral health 2016 Behavioral Health volumes: 20,000 psychiatric emergency visits 2,800 psychiatric observation days (2,526) 3,700 inpatient psychiatric admissions (4,126) 39,000 psychiatric inpatient days (43,093) 5,900 partial hospitalization days (6,468) 28,500 psychiatric outpatient visits (36,396) 80,000 depression screenings - PCP Our Behavioral Health Team: 525 Team Members 60 Master’s Level Clinicians 9 Peer Support Specialists 20 Psychiatrists 17 Psychiatric NP’s / PA’s 18 Psychiatry Residents 5 Psychologists Seven Behavioral Health focused 1115 Waiver Projects Four partial hospitalization programs Psychiatric Emergency Center Day rehab for the homeless Two psychiatric hospitals (96 and 36 beds) Virtual Behavioral Health Clinical Guidance Integrated Medical Unit Eight primary care clinics with embedded behavioral health specialists Six behavioral health clinics Walk-in behavioral health clinic Eight Peer Support Specialists Three behavioral health school- based clinic Psychiatry residency program

Why does it matter? Ten conditions with the most all-cause, 30 day readmissions for MEDICAID patients (aged 18-64) Source: Weighted national estimates from a readmissions analysis file derived from the Agency for Healthcare Research and Quality (AHRQ), Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project (HCUP), State Inpatient Databases (SID), 2011.

Why does it matter more to us? Ten conditions with the most all-cause, 30 day readmissions for UNINSURED patients (aged 18-64) Source: Weighted national estimates from a readmissions analysis file derived from the Agency for Healthcare Research and Quality (AHRQ), Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project (HCUP), State Inpatient Databases (SID), 2011.

Why does it matter even more to JPS? We had nearly 4000 discharges from our inpatient psychiatric facility at the time the project initiated We have over 20,000 psychiatric emergency room visits annually We transferred 3,100+ patients to other facilities because we lacked capacity We paid over $3.1M last year for other facilities to care for our patients

Alignment to chna findings Unique community need identification numbers the project addresses: CN.4 – Lack of access to mental health services CN.5 – Insufficient integration of mental health care in the primary care medical care system CN.10 – Overuse of emergency department (ED) services CN.11 – Need for more care coordination

Project goals After implementing an effective Discharge Management Program for behavioral health patients, we will improve care transitions and coordination of care from inpatient to outpatient, post-acute care, and home care settings so that patients will experience post-discharge community engagement and stability, reducing the risk of readmission due to their conditions worsening.

Efforts to Create Culture Change

Team: PROJECT leadership team We chartered a cross-continuum team comprised of clinical and administrative representatives from acute care, ambulatory case, behavioral health and community-based non-medical supports Goal: This project is to provide a comprehensive Behavioral Health Discharge Management Program based on evidence-based models. After implementing of this program for behavioral health patients, we will improve care transitions and coordination of care from inpatient to outpatient; post-acute, care and home care settings so that patients will experience post-discharge community engagement and stability, reducing the risk of readmission. Core members of the charter included: Chair of Psychiatric Department Member of Inpatient Social Services Senior Vice President Director of Psychiatric Nursing Behavioral Health Project Manager (PHP) Director of BH Social Services Medical Director of Adult Inpatient Services Member of the Patient and Family Council Member of Inpatient Nursing Ad Hoc members will be invited to bring their expertise to address specific topics or concerns. Member of the Psychiatric Emergency Center

Team: Transition coordinators We hired a team with a mixture of care transition, disease management, and behavioral health expertise. Most of the team members were master’s level social workers with varied backgrounds. Subsequently, we converted some positions to bachelor prepared roles to better ensure people were working to the maximum of the licensure.

TEAM: Peer Support Specialists We conducted a study to determine feasibility of providing a peer support program on hospital campus for patients with high-risk diagnoses. Today: We have 9 peer support specialist roles We have developed a mutual support program through our EAP to mitigate the stress of working in our acute environment The peers are now deployed in emergency, inpatient, PHP, Day Rehab, and outpatient settings. We implemented in stages – piloted two people, had consultants come in to prepare culturally.

Team: patient and family advisory council We created a behavioral health specific Patient and Family Advisory Council to provide advice to our system on factors influencing care transition and strategies for improving care transition. Key Points: This group has huge influence. Very few policy decisions are made without going through this committee. Every major educational or performance improvement initiative has membership that includes at least member of this committee. They are on-boarded with parking and badges as any employee, volunteer, or board member.

Team: External assistance NASMHPD/SAMHSA Consultant assisted with helping assess our needs to be prepared for peers and culture changes necessary to engage in a focus around a recovery oriented model of care Institute for Behavioral Health Improvement provided consultation to assist with early culture and needs assessment as well as providing guidance and support for our early rapid cycle PDSA’s and related improvement efforts.

DMAIC Journey Define Measure Analyze Improve Control Define the problem & opportunity Define the process Understand the customer Plan the project S I P O C VOC CTQ Measure Understand the process Collect data Evaluate process performance III II I III I IIII I II II IIII Analyze Analyze the process Identify potential root causes Analyze the data Validate root causes Improve Generate solutions Select solutions Test solutions Implement solutions FMEA Control Standardize the process Monitor results Document and close the project SOP DMAIC Journey

Readmissions Analysis Phases

Phase 1: readmitted patient interviews 10 Patients were interviewed using a standard format adapted from commonly used acute care tool. Key Points: Readmission Time 0 – 5 Days: 4 Patients 6 – 15 Days: 3 Patients 16 – 30 Days: 1 Patient 31+ Days: 2 Patients

Phase 2: 250 chart reviews We conducted an analysis of the key drivers of 30-day hospital readmissions for behavioral health conditions using a chart review tool (e.g. the Institute for Healthcare Improvement’s (IHI) State Action on Avoidable Re-hospitalizations (STARR) tool) and patient provider interviews.

Data Collection – Modified Staar Tool May 2009 IHI launched the State Action on Avoidable Rehospitalizations (STAAR) initiative. The STAAR initiative focus is to reduce rehospitalizations. Data Collection – Modified Staar Tool

PHASE 2: 250 Chart Reviews

PHASE 2: 250 Chart Reviews

Legal Status PHASE 2: 250 Chart Reviews

Phase 3: 30 day readmit calculation Key Factors: Patients with multiple readmissions within 30 days of index admission were only counted once Readmission rate is for adults only Excluded any patient transferred to another hospital (including state hospital)

Phase 4: observed over expected The information below are the identified predicators of readmission per the review of our EMR system of 3585 records. We initiated a process to established statistically significant predicators for readmission. The first step was to compare the presence of the variables being reviewed to what would be expected given the make up of our population. The variables reviewed include: Age Gender Zip Code Race Ethnicity Diagnostic Class

Phase 4: observed over expected O/E means Observed over Expected: The Expected Frequency for each Demographic Variable is calculated as the predicted number of diagnosis based on the patients’ level of illness (higher Severity of Illness - SOI has a higher expected value) This is the denominator population The Observed Frequency for each Demographic Variable is calculated as the number of patient diagnosis for those with one or more readmit. This is the numerator population. The O/E Ratio is the Observed Frequency divided by the Expected Frequency Example: if the Age 50-64 range was 15% of the denominator (expected) and 25% of the numerator (observed) then the O/E ratio = .25/.15 = 1.67

Phase 4: Severity of illness assessment SOI is still commonly used throughout the United States to adjust for patient complexity, so that physicians and other groups can compare resource utilization, complication rates, and length of stay. Severity of Illness: Low Severity Medium Severity High Severity Very High Severity Note about Severity of Illness - The proprietary 3M APR DRG methodology includes a “Severity of Illness” ranking algorithm based on both comorbidities and complications. Our HIM software is from 3M so those ratings automatically get assigned to all Inpatient cases that have been coded by HIM.

PHASE 4: Observed Over Expected

PHASE 4: Observed Over Expected We then began to refine our analysis by looking at variables that appeared to be particularly high risk by gender. PHASE 4: Observed Over Expected

PHASE 4: Observed Over Expected We then refined our analysis by looking at rates for readmission by multiple variables (gender, age range, & diagnosis). PHASE 4: Observed Over Expected

Phase 5: Predictors for readmission The Predictive Model analysis process: Identified the independent demographic and clinical variables that were present on admission of each Index visit: Identified the dependent variable: “Index with 1 or more Readmits” Segmented the values in each independent variable into meaningful groups that had sufficient volumes to make a statistically significant impact on the dependent variable Identified the “Reference Group” for each independent variable as the group with the lowest Observed over Expected (O/E ratio) Age Range: 61-65 Gender: Female Zip Code: 76102 Race: Caucasian Ethnicity: Hispanic Diagnostic Class: Other

Phase 5: Predictors for readmission The Predictive Model analysis process cont’d: Ran a Logistic Regression analysis to determine the contribution coefficients – odds ratio (Exp(B)) - of each of the independent variable groups on the dependent variable Assign a weighted risk score to each independent variable group with a contribution coefficient > 1 Exp(B) 1.0 to 1.49 = 1 point Exp(B) 1.5 to 1.99 = 2 points Exp(B) 2.0 to 2.49 = 3 points Exp(B) 2.5 or greater = 4 points 7. Determine the Risk classification scale based on total Risk Score per visit 8. Calculate the Percentage and Readmit Rates for each Risk Classification

Readmission Data Analysis Summary PHASE 3 PHASE 2 PHASE 1 PHASE 5 PHASE 4 Observed over Expected 18-40 yo Males more likely Dx: Schizophrenia, bipolar, substance abuse, medical, psychosis LOS: 4-10 days Race: AA, PI, Asian, AI Ethnicity: Not Hispanic or Latino 10 Interviews Key Points: Readmission Time 0-5 Days: 4 pts 6-15 Days: 3 pts 16-30 Days: 1 pt 31+ Days: 2 pts 250 Chart Reviews Reviewed days from DC to readmit Age & Gender Dx Categories Financial Status General Themes Zip Codes 30 Day Readmission Rate Baseline Rate of 6.56% Predictors of Readmission Dx: Bipolar, Psychosis, Schizophrenia, substance abuse Age: 55-60 yo Race: Black & Asian Ethnicity: Not Hispanic Zips: 76116, 76010 Readmission Data Analysis Summary

Readmission Tool

Predicators For Readmission

Predicators For Readmission OVERVIEW – READMIT RISK RATE Risk Category Readmit Risk Score Count Low 192 1 34 2 210 Medium 3 922 4 450 5 961 High 6 700 7 85 8 9 26 10 Total   3585 Predicators For Readmission

Risk for Readmission Assessment Tool CRITERIA Patient meets Criteria Score Diagnosis   Bipolar Disorder NO Psychosis Schizophrenia Substance Abuse Age 56 - 60 Race BLACK OR AFRICAN AMERICAN ASIAN Ethnicity NOT HISPANIC OR LATINO Zip Code 76116 76010 Total Risk Score: Risk for Readmission: Low SCORE ≥ 6 HIGH RISK for readmission SCORE 3-5 MODERATE RISK for readmission SCORE ≤2 LOW RISK for readmission Risk for Readmission Assessment Tool

Our Process and Improvement Efforts

READMISSION RISK RECORDED IN EHR One Risk screening is complete, the patient list is updated and viewable to all team members READMISSION RISK RECORDED IN EHR

INITIAL INTERVENTIONS ARE INITIATED NOTE: WE HAVE STANDARD INTERVENTIONS BUT ALWAYS ADD TO MEET INDIVIDUAL PATIENT NEEDS INITIAL INTERVENTIONS ARE INITIATED

INITIAL INTERVENTIONS ARE INITIATED If the current admission is a 30-day readmission, we modify our process! NOTE: WE HAVE STANDARD INTERVENTIONS BUT ALWAYS ADD TO MEET INDIVIDUAL PATIENT NEEDS INITIAL INTERVENTIONS ARE INITIATED

CURRENT READIMISSIONS ARE HIGH FOCUS If patient is a Readmission in the last 30 days a Peer Support Specialist will meet with patient 1:1 and complete a standard readmission survey. NOTE: WE HAVE STANDARD INTERVENTIONS BUT ALWAYS ADD TO MEET INDIVIDUAL PATIENT NEEDS CURRENT READIMISSIONS ARE HIGH FOCUS

PEER SUPPORT FOCUS ON GOALS Peer Support will initiate an orientation to inpatient admission and start to capture patient goals NOTE: WE HAVE STANDARD INTERVENTIONS BUT ALWAYS ADD TO MEET INDIVIDUAL PATIENT NEEDS PEER SUPPORT FOCUS ON GOALS

HIGH RISK READMISSION INTERVENTIONS

Care transition models We set out to identify evidence-based frameworks that support seamless care transitions and impact preventable 30-day readmissions.  The team reviewed best practices for improving care transitions from four evidence-based or evidence informed models. Model 1: The Andersen Behavior Framework Model 2: Donabedian’s Quality Framework Model 3: The Organizational Design Framework The Wagner’s Chronic Care Model (example) Model 4: The Relational Coordination Framework Ultimately there were little models or programs with a behavioral health focus so we adapted best practices from these models to create our program.

Education We had a goal to educate 75% of the appropriate clinical staff on key contributing factors to preventable readmissions. We considered appropriate clinical staff to be all providers and master’s level clinicians (just over 100 team members in total). We educated 89% of our clinical staff members about the readmission project, findings from analysis and interventions to reduce readmissions. Today we include patients and families in our staff education sessions both as learners and as teachers.

Interventions (partial list) Appointment with an Embedded Behavioral Health Specialist (EBHS) Group Therapy with an EBHS Appointment for counseling Appointment with psychologist Group Therapy Session with Transition Coordinator (TC) Telephonic Supportive/Mentoring 10-15 minutes phone appointment Telephonic Supportive/Mentoring 20-30 minutes phone appointment Attend appointment with patient at their 1st visit with psychiatrist Assist w/navigation of DC meds Family Education/Consultation Support Disease Management Education Recovery Messages sent by mail or email Setup appointment for home visit Consultation w/Pharm D regarding meds Assistance with establishing a Primary Care Appointment Assistance with establishing with JPS Connection Programs Facilitate process with after care at a Substance Abuse Treatment Center Facilitate process with other community support groups Referral to Partial Hospitalization Program This is not an all-inclusive list for interventions. Interventions will be added per the needs of the care plan.

PDSA’s (as a way of life) We have completed 43 rapid cycle improvement projects in 4 years Improving the electronic reporting of readmission data – 5 cycles Improve JPS Connection application assistance – 4 cycles AIDET – 4 cycles MHMR Liaison meeting in PEC – 4 cycles Multi-disciplinary Treatment Team meeting & Documentation – 2 cycles Discharge planning checklist/scripting – 3 cycles Long Acting Injections: Transition from inpatient to outpatient – 3 cycles BH follow-up appointment: Text or email reminders – 2 cycles BH follow-up appointment: Attendance assistance – 2 cycles BH follow-up appointment: Bridge visit by TC’s for High Risk – 1 cycle BH follow-up appointment: Peer support reminders & group – 3 cycles Aftercare services focus group: increase referrals to PHP/IOP – 2 cycle Aftercare group facilitated by Peer Support – 2 cycles PEC Discharge: Transition aftercare info sheet – 3 cycle Post follow-up 1:1 visit w/SW & I am Wellness transition sheet – 2 cycle My Passport Recovery folder: Guide to care continuum – 1 cycle

“Meds to beds” Originally, we started out with high risk psychiatric inpatients receiving medications in hand at time of discharged. This was initially facilitated by our per support specialists waiting at the pharmacy. It was seen as so successful, all patients in TSP began getting actual medications at discharge with no need to go to the pharmacy. Currently, all inpatients (medical/surgical and psychiatric) at JPS receive medications at discharge with the process hardwired through pharmacy.

Peer Support specialists We developed our peer specialist positions to focus on providing emotional support and practical guidance regarding the discharge and recovery process. Techniques include: teaching patients techniques, such as keeping wellness journals or recovery inventories meeting with patients individually and in recovery support groups conducting panel presentations to provide the patient perspective to physicians, nurses, medical and nursing students and other hospital staff conducting evidence-based self-help training sessions with patients. (Example of EBPs include Wellness Recovery Action Planning (WRAP) Today we do monthly WRAP classes – we have trained over 20 WRAP facilitators in our community – some on our staff, some staff from community mental health center, some from Mental Health of America of Greater Tarrant County

Process and Outcome Measures

Appropriate Education Goal: Improve percentage of patients / families who are provided with appropriate education upon discharge The appropriate education upon discharge was provided by following our Education Discharge Tools Protocol which consisted of: high risk for readmission receive at least 2 additional tools beyond the standard after visit summary (AVS) moderate risk for readmission receive at least 1 additional tool beyond standard AVS low risk for readmission receive standard AVS and any additional information needed Talk about education packets and PFAC involvement/recommendations

Care plans GOAL: Customized Care Plans - Increase percent of High Risk Patients who are discharged with customized care plans

Follow-up Calls GOAL: Improve percentage of inpatients who have been discharged and have received clinician follow‐up calls to review treatment plans and assess adherence.

7 and 30 day post-discharge Follow-Up Appt GOAL: Improve percentage of patients receiving Follow‐Up After Hospitalization for Mental Illness within 7 and 30 days.

30 day same facility readmission rate

30 day same facility readmissions – risk stratified Data were from the Texas Health Care Information Collection's Inpatient Research Data File (THCIC-IP).

Ipf 30 day all facility readmission rate – cms claims data (FFS) Data were from the Texas Health Care Information Collection's Inpatient Research Data File (THCIC-IP).

Ipf 30 day all facility readmission rate – cms claims data (FFS) Data from TMF – Medicare contracted QIO for Texas

Presentations Research outcomes presented at APHA Annual Conference in 2016 2014 Bill Aston Quality Award Program presented at America’s Essential Hospitals Annual Conference in 2017

Next steps We have already expanded the program to include patients discharged from: “Med-Psych Unit” Psychiatric Emergency Center 23-hour observation patients Trinity Springs North (our new inpatient facilitated opened 01/2016 We anticipate expanding the program to include patients discharged from the acute medical/surgical floors that experienced a psychiatric consult from our service We intend to incorporate this program into a larger care management program to be delivered system wide. Publication

Contact information Alan Podawiltz, DO Chair of Psychiatry, JPS Health Network Chair of Psychiatry, University of North Texas Health Sciences Center 817-702-6695 apodawil@jpshealth.org Wayne Young, MBA, LPC, FACHE Senior Vice President, Behavioral Health 817-702-3639 wyoung@jpshealth.org