THE CENTER FOR SUBSTANCE ABUSE TREATMENT DIVISION OF STATE AND COMMUNITY ASSISTANCE STRATEGIC PLANNING FOR PROGRAMS TO IMPROVE BUSINESS PRACTICES CONFERENCE HYATT REGENCY CRYSTAL CITY ARLINGTON, VIRGINIA OCTOBER 21-23, 2009 USING CLIENT SERVICE DELIVERY DATA FOR SUBSTANCE ABUSE TREATMENT PROGRAM DEVELOPMENT, MONITORING AND ASSESSMENT Richard E. Sherman, Ph.D. Illinois Department of Human Services Division of Alcoholism and Substance Abuse

Three Major Human Service System Planning, Development and Assessment Perspectives Quality - Examples of indicators include: organization licensure/accreditation, use of evidence-based practices, staff qualifications/experience, and physical facility and other logistical resources. Performance - Indicators are generally process in nature and reflect client engagement/access, retention, and care continuity. Outcomes - Indicators focus on changes in client or patient functioning, behavior, and other attributes targeted for impact by the services provided.

Illinois CSAT-Funded Strengthening Treatment Access and Retention – State Initiatives Grant CSAT Cooperative Agreement #: TI17618 Award made to IDHS/DASA in September Fourteen IDHS/DASA-funded providers have participated in the project. The Illinois STAR-SI Project has two major goals. 1. Identification of strategies and process improvements that will increase rates of access and retention in Illinois outpatient substance abuse treatment programs; and, 2. Increase substance abuse outpatient treatment program efficiency in Illinois. The Network for the Improvement of Addiction Treatment (NIATx) serves as the CSAT-funded Technical Assistance Center.

STAR-SI Illinois Outpatient Access and Retention Measures  Client No-show Rate - The percentage of persons who receive an appointment for an admission assessment who fail to show for the appointment.  Average Time from Initial Contact to Admission - The average time between the date on which the client or someone on behalf of the clients first makes contact to request an assessment session, and the date of assessment/admission.  Average Time from Admission to First Outpatient Session - The average time between date of opening/admission and the first outpatient clinical session.

STAR-SI Illinois Outpatient Access and Retention Measures  Average Time from First to Second Outpatient Session - The average time elapsed between the dates of the first and second outpatient sessions.  Early Client Engagement Rate - The percentage of admitted clients who are provided at least four Level I, or twelve Level II group or individual sessions within thirty days of admission.

Identification of Client Service Performance Indicators in Need of Improvement 1. Baseline and Monthly Client Access and Retention Performance Measure Tables and Reports Developed by IDHS/DASA (DARTS Encounter Database). 2. Provider Executive Director Walkthroughs. 3. Individual Provider Data Systems.

Data-Driven Service Improvement Projects Provider Business Case Examples Southeastern Illinois Counseling Centers  AIM:  Increase Admissions by 60% per month in Crawford County.  BASELINE DATA:  Average of 5 admissions per month from October 2008 through January  MEASURE:  # of Admissions/Month during each Change Cycle.  TARGET:  At least 8 Admissions/Month.

Data-Driven Service Improvement Projects Provider Business Case Examples Southeastern Illinois Counseling Centers 1.Streamline the Admission Process:  Increase to 2 Hour Assessment  Reduce to 1 session from 2 or 3 sessions 2.Increase Group Hours:  Increase from 2 to 5 available groups initially  Add Groups as needed 3.Inform Clients and Referral Sources of Changes

Data-Driven Service Improvement Projects Provider Business Case Examples Southeastern Illinois Counseling Centers

Data-Driven Service Improvement Projects Provider Business Case Examples Community Resource Center of Edgar & Clark Counties  AIM:  To reduce by 15% the average time from assessment to first treatment session among Level I clients.  BASELINE DATA:  The baseline average time from assessment and admission to first Level I treatment session was 25 days.  MEASURE:  Average Duration from Admission to First Treatment Session.  TARGET:  An average of no greater than 21 Days.

Data-Driven Service Improvement Projects Provider Business Case Examples Community Resource Center of Edgar & Clark Counties CHANGE  Reduced the clinical substance abuse assessment from 19 pages to 12 pages. RESULTS  In the first 30 days of the change project the average time from assessment to first treatment was reduced from 25 days to 11 days for a 56% reduction.  In the final month of the change project the average time from admission to first treatment sessions was reduced to 7 days for a 72% reduction.

Data-Driven Service Improvement Projects Provider Business Case Examples Community Resource Center of Edgar & Clark Counties

Data-Driven Service Improvement Projects Provider Business Case Examples South Suburban Council on Alcoholism/Substance Abuse  AIM:  Increase Number of Level I Patients who attend at least four TX sessions within 1 st 30 days of admission.  BASELINE DATA:  Baseline data from July to September 2008 showed 44% of patients attended at least four sessions in 1 st 30 days. MEASURE:  % of Clients/At least Four Sessions/1 st 30 Days.  TARGET:  At Least 55% of Clients/At least Four Sessions/1 st 30 Days.

Data-Driven Service Improvement Projects Provider Business Case Examples South Suburban Council on Alcoholism/Substance Abuse 1. Change team Identified Level I DUI clients as significant obstacle to success. 2. Due to attending risk education many did not attend 1 st treatment session until 45 days post admission. 3. Decided to change the order in which these clients received services. 4. All DUI clients would be assessed and placed directly into Level I service and attend risk education after completion.

Data-Driven Service Improvement Projects Provider Business Case Examples South Suburban Council on Alcoholism/Substance Abuse

Data-Driven Service Improvement Projects Provider Business Case Examples Franklin/Williamson Human Services, Inc.  AIM:  Increase client show-rate to four day/week outpatient Parenting Group for women referred from this organization’s residential treatment unit.  BASELINE DATA:  Group initially had a 62.3% no-show rate resulting in an average of $2, in lost DASA revenue/month.  MEASURE:  Cumulative monthly no-show rate for the Parenting Group.  TARGET:  No more than a 50% non-show rate for the Parenting Group.

Data-Driven Service Improvement Projects Provider Business Case Examples Franklin/Williamson Human Services, Inc. 1. First change involved implementation of a contingency management fishbowl strategy that rewarded group attendance. Group attendance increased from an average of four to six clients/group. 2. The second change involved addition of The Real Life Skills Parenting Program (journaling curriculum). This resulted in a further increase in average group show-rate. 3. Following implementation of the second change, clients were under the impression that attendance would not count toward DUI treatment service requirements. This resulted in a drop in attendance. It was determined that sessions would count toward this requirement. 4. As a third change, a client’s residential counselor was contacted in each instance that the client missed a session. A further increase was observed after this change.

Data-Driven Service Improvement Projects Provider Business Case Examples Franklin/Williamson Human Services, Inc.

Data-Driven Service Improvement Projects Lessons Learned – Provider Level 1.Choose a service area of business and/or clinical importance. 2.Identify capabilities and limitations of the data. 3.Collect baseline data. 4.Gather feedback from all stakeholders. 5.Engage and involve all team members. 6.Use concrete definitions in determining the problem and establishing a plan. 7.Set realistic goals and be flexible.

Data-Driven Service Improvement Projects Change Sustainability – Provider Level 1.Establish and Disseminate Program Targets.  Substance Abuse  Mental Health  Co-occurring 2.Monitor productivity, performance indicators, and client caseload indicators of each staff member. 3.Monitor indicators as part of staff supervision. 4.Provide process improvement orientation to new staff. 5.Utilize data in making decisions regarding programs and allocation of agency resources.

Diffusion of STAR-SI Principles Development of a Statewide Provider Performance Management System  Illinois has taken the first steps toward performance-based contracting through development of a baseline provider performance report for each of over 100 IDHS/DASA-funded organizations.  Client service performance measures expanded to Detoxification, Level I (methadone), Level II, and Level III.5.

Diffusion of STAR-SI Principles Development of a Statewide Provider Performance Management System  The first set of Provider Performance Reports reflect an analysis of service data entered in DARTS for clients opened during calendar year  Report Performance Measures Include:  Number of Admissions: (All levels of care.)  Average and Median Duration from Initial Contact to Admission/Opening: (Total clients only.)  Average and Median Duration from Admission to First Outpatient Session: (Levels I and II)

Diffusion of STAR-SI Principles Development of a Statewide Provider Performance Management System  Percentage of Clients who Receive at Least Four Sessions within the First 30 Days: (Level I)  Percentage of Clients who Receive at Least 12 Sessions within the First 30 Days: (Level II)  Percentage of Discharged Clients/Completed Treatment: (All clients and by level of care.)  Percentage of Opened Clients who Remain Open in DARTS: (All clients and separate by level of care.)  Average and Median Length of Stay: (Detox/Level III)  Percentage of Clients Linked to Next Level of Care – Detox/Level III)

Diffusion of STAR-SI Principles Development of a Statewide Provider Performance Management System  Expectations regarding change in individual provider organization status on selected report indicators will be part of the SFY 2010 contracting process.  Year 1 of this first step toward performance contracting will be a “hold harmless” period.  Three indicators were selected to be of statewide importance.  % of opened clients/no clinical service post-opening  Duration between admission and first session  Avg. # of sessions during first 30 days

Diffusion of STAR-SI Principles Development of a Statewide Provider Performance Management System  Process was developed for extraction of a DARTS data file for each DASA-funded provider that contains service billings for all clients opened in calendar year  Procedures were developed for the processing of the raw data files into analysis-ready files.  A format was developed for the provider performance reports  Individual provider performance measure analyses were conducted.

Diffusion of STAR-SI Principles Development of a Statewide Provider Performance Management System  Organization-wide and level of care performance measure databases were developed for 108 providers.  A statewide performance measure report was developed that includes measure levels by DASA service region, level of care, and adult and adolescent client populations.  An individual provider performance report was developed for 108 organizations that includes organization-wide measure levels, and level of care measures by service site location.

Diffusion of STAR-SI Principles Development of a Statewide Provider Performance Management System  There were 71,132 clients opened in DARTS during calendar year  The average duration from initial contact to opening was 8.0 days and the median was 0.0 days. The initial contact and opening dates were the same for 46,246 (67.6%) of the opened clients.  The average duration from opening to first clinical session, for clients who received a first service, was 11.6 days and the median was 5.1 days. Thirty percent (30.0% - 21,311) of the opened clients did not receive a next clinical session after opening.

Diffusion of STAR-SI Principles Development of a Statewide Provider Performance Management System  The average number of service hours provided to the outpatient clients (43,148) was 25.1 hours and the median was 8.25 hours. 31.0% (13,389) of the non- residential clients received no more than 2.0 hours of service, and 40.8% (17,602) of the non-residential clients received no more than 4.0 hours of service.  Of the 48,682 clients opened in calendar year 2007 who were discharged, 44.3% were reported to have completed services. As of September 9, 2008, 31.6% (22,450) of the clients opened during calendar year 2007 were still open in DARTS.

Diffusion of STAR-SI Principles Development of a Statewide Provider Performance Management System – Business Case  Thus far, comments from providers have been generally supportive.  It is expected that the performance contracting process will reduce the need for providers to maintain waiting lists for Level I and Level II services.  The performance contracting process is expected to increase the number of clients who actively engage in treatment, and better enable providers to “spend out” their contracts.  Could result in a decrease in admissions if there is no change in available resources.

Diffusion of STAR-SI Principles Development of a Statewide Provider Performance Management System – Lessons Learned  Need to identify the limitations and capabilities of existing data systems.  There may be an opportunity to make relatively easy revisions to existing data systems.  Important to involve both state staff and provider representatives in system development.  What’s a denominator? – Be available for questions.  Service delivery improvements could result in a decrease in admissions if there is no change in available resources.  Next round of reports will include outcome measures.