 Performance assessments can:  help identify potential problems in the program  help identify areas where streamlining the process could be useful & help make the program run more smoothly  help ensure fidelity to the model  help ensure that the program is following the 10 key components/10 essential elements

 Why should we care if we adhere to the 10 key components:  Courts that bring people into the program within 50 days of arrest have greater impact on reducing recidivism  Courts that drug test at least two times per week (with a true random pattern) are twice as cost effective  Courts that use jail sanctions no longer than 6 days had lower recidivism than courts with jail sanctions of 6+ days  DRUG COURTS THAT EVALUATE THE PROGRAM & MODIFY THE OPERATION BASED ON RESULTS HAD TWICE THE COST SAVINGS OF OTHER COURTS

Online Reports Active Counts Outcomes Performance Measures Admission Data Referral Data (FDC & MHC Only) Referral Data (FDC & MHC Only) Phase Data Discharge Data (Termination, Graduation, etc.)

content/uploads/2009/01/GarbageTruck.jpg Source: content/uploads/2011/03/Packer-truck.jpg

Your Court’s Active Counts Your Court’s Outcomes & Performance Measures & Ultimately, Statewide Data that Affects All Specialty Courts

 Ensuring data quality:  Contractual requirement  Tied to funding  Data matching  Data Review Contracts require data elements for all active, graduated, & terminated participants.  Participants are only counted active for purposes of funding if data records have been updated in at least the last 60 days.  Additionally, contract payments can be withheld for failure to accurately report data. The ODMHSAS holds data sharing agreements with multiple agencies including the Oklahoma Department of Corrections & the Oklahoma Employment Securities Commission. Run program data & review for outliers or data inconsistencies, correct errors.

 Tied to Funding  When a review of the program’s 60 Day Active Count shows a participant or a group of participants that have not been updated in the last 60 days program staff should take steps to ensure the data are updated immediately or by the 2 nd of each month. This ensures programs have current data.

 Data Matching

 Data Review  When a review of outcome data shows a dramatic change, courts should review data to determine if outliers. Once identified, then correct inaccuracies. This ensures programs have accurate data.

 Data Review  1) Run participant-level reports to identify the outliers (Example: Which participants have decreasing income between admission & graduation.)  2)Verify data through file review (Example 1: Pull participant file & review employment verification/pay stub to verify income at graduation.)  3)Correct record to reflect the accurate income.  4)Re-run report to verify correction & view new average for this outcome at the court level (correcting individual cases impacts the overall court results).

 Case Studies  When a review of outcome data shows an outlier, courts can verify & correct data (as seen previously). IF data are correct, then courts can conduct case studies to determine the explanation for why the case was an outlier.

 Case Studies  1)Identify the outlier of focus  2)Case ‘Wwwww’ has no prior felony convictions, no prior arrests, no additional charges; & the current charge is Possession for which they received a 10 year prison sentence. Why would this case be in your court? The reasons are obvious for ‘meth user’, ‘Tt Tt’, & ‘nancy warren’  3)Begin case study gathering information on why this person came into the program. Review: Risk Screen Information (participant has strong association with known criminals, is unemployed, is homeless, & has no family support) ASI (participant has used drugs daily for the past15 years & began at an early age) Mental Health Screen (participant has a co-occurring mental health concern).

 Goal Setting  With the ability to run real-time outcome reports, courts can set goals for improvement of one or more outcome measures.

 Goal Setting  1)Identify which outcome(s) to target  2)Set a measureable, realistic goal for improvement  3)Set a timeline to re-evaluate

 Goal Setting  1)Identify which outcome(s) to target  2)Set a measureable, realistic goal for improvement  3)Set a timeline to re-evaluate  4)Identify a barrier/barriers which has lead to the current issue Many times this is simply, it wasn’t a priority. (Case Studies vs. Systemic Issues)  5)Choose one barrier & identify steps to remove/reduce it.  6)Re-evaluate

 Systemic Issues  Data can reflect a systemic issue that needs to be addressed through policy change(s).  The use of jail as a sanction in MHC is: Ineffective (costly and does not result in positive behaviors) Inappropriate AGAINST best practices Harmful

 Systemic Issues  Data can reflect a systemic issue that needs to be addressed through policy change(s).  NOT getting people into treatment quickly is: AGAINST best practices Harmful to recovery (results in poor outcomes) Delays needed treatment

 Systemic Issues  1)Identify which outcome(s) to target  2)Run participant-level reports which show multiple participants impacting an outcome measure.  3)Meet with the court team to develop plan of action. Multiple participants are impacted. (Example 1: Extended jail days being used as a routine sanction. May need to re-evaluate sanction matrix. Example 2: Excessive time between referral & admission. May need to review the admissions process.)  4)Identify a timeline to re-evaluate the plan from step 3.  5)Re-evaluate

 Goal Setting or Systemic Issues

 1)Run demographic reports which show the make-up of the participants within the court.  2) Compare the court participant demographics to that of arrests within the county and the county demographics as a whole. Does the program mirror these demographics?  3) Meet with the court team to determine if the issue is due to goal setting or if the issue is systemic then develop plan of action to address the issue.  4)Identify a timeline to re-evaluate the plan from step 3.  5)Re-evaluate

 State representative role (Field Representative)  Building a relationship with the programs  Keeping data as a priority  Communicating with the programs on outcome changes  Identifying training needs/trends  Assisting in the assurance of quality data  Providing technical assistance (case studies & systemic concerns)

 Check to see if reaching target population  Ensure accuracy of data used to calculate your court’s priors data  Use to check other performance & outcomes measures  Ensure your court is reaching its target population

 Run all reports regularly  Ensure data are current  Ensure data accuracy  Confirm contract compliance  Monitor improvement  Review case abnormalities  Set goals  Address systemic issues  Serve county needs effectively Risk, MH, SA, Race/Ethnicity, Gender

 David Wright  (405)   Lorrie Byrum  (405)   Nancy Warren  (405) 