state quality management system for treatment improvement understanding and using the information
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STATE QUALITY MANAGEMENT SYSTEM FOR TREATMENT
IMPROVEMENTUnderstanding and Using the
Information
Sanford Starr | Terry Patel | Laura Potts | Kevin Feasel
Spring 2012
John R. Kasich, GovernorOrman Hall, Director
What is Quality Management?*
Quality Management (QM) The processes of establishing measures,
gathering and reporting data and using data to • verify performance; • improve services and/or business practices; and • make data-driven decisions
The term (QM) is used in healthcare where as “Performance Management” has been used in the substance abuse field
* Performance Management for Substance Abuse Treatment Providers. SAMHSA. April 2008.
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Components of QM
“Quality Assurance” is establishing, measuring and identifying and correcting minimal standards of acceptable performance, which is completed by experts and staff
“Quality Improvement” is the process that defines quality according to the needs and preferences of customers and continuously improve services in real time as services are provided ODADAS’ approach focuses on Quality
Improvement
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Research vs. Quality Management
Adds to knowledge and evidence-based practices
Experimental and quasi-experimental designs
Sophisticated techniques and analyses
Led by health/ human services scientists
Takes months to years
Presents evidence of effectiveness and improved services
Internal comparison of data over time
Simple analyses of trends over time
Led by clinical and program staff
Takes a few months
Research Quality Management
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ODADAS’ QM Plan
To use QM on a statewide level; however data are available to providers and boards for their own use
To start with treatment services and incorporate prevention services at a later date
To develop techniques and strategies to increase performance and share key learnings
To encourage peer support and networking To continue training and technical assistance
Quality Management - Webinar Series #1 - Spring 2012
Implementing the System
Start with measures that impact outcomes*
Retention (in treatment)
Disposition at Discharge Invite providers and boards to work with
ODADAS to determine the utility Use NIATx for quality improvement
purposes Develop subgroup reports
* QM is evolving; this is just a starting point
* QM system is evolving; this is the starting point
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Retention Indicators
At least one clinical encounter* within the first 14 days post assessment and two additional encounters within the 30-day period (Washington Circle)
At least four clinical encounters* within the first 30 days post assessment (NIATx)
* Does not include case management
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Case Management Findings*
State retention rates only: Case management only – low retention
rates Clinical services only – improved retention
rates Case management and clinical services –
dramatic increase in retention rates
* For unbundled case management
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Table Figures - Retention
“All Clients” represents the number of clients*
served at a particular provider based on the Unique Provider Identification (UPID) number
“Retained” represents the number of clients who met the retention measure
“Retention Percentages” represent the percent of clients who met the retention measure
*Measures are based on unduplicated clients information with admission and discharge records. Admission dates are used in reporting.
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Interpreting Results
Critical to know: What the UPID represents Percentage of clients served are reported in
Ohio Behavior Health (OHBH) Percentage of clients served have
admission and discharge records When services are billed in MACSIS*
* Multi-Agency Community Services Information System
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How the Results Can be Used
What is the direction of change; how do the numbers increase, decrease or remain the same over time?
What are the differences among levels? Were the figures expected? Are these the desired results? What strategies might be used
to do better? Who needs to be involved in making and sustaining improvements?
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Levels of Measures*
Provider Based on UPID
Board 47 combined (ADAMHS) and 3 separate (ADAS)
Region▪ Appalachian ▪ Rural, Non-Appalachian▪ Metropolitan ▪ Suburban
State* National data will be provided if applicable and available
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Metropolitan Region (12)
Allen Butler Cuyahoga Franklin Hamilton Lorain
Lucas Mahoning Montgomery Richland Stark Summit
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Suburban (17)
Auglaize Clark Delaware Fairfield Fulton Geauga Greene Lake Licking
Madison Medina Miami Pickaway Portage Trumbull Union Wood
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Rural, Non-Appalachian (30)
Ashland Ashtabula Champaign Clinton Crawford Darke Defiance Erie Fayette Hancock Hardin Henry Huron Knox Logan
Marion Mercer Morrow Ottawa Paulding Preble Putnam Sandusky Seneca Shelby Van Wert Warren Wayne Williams Wyandot
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Appalachian (29)
Adams Athens Belmont Brown Carroll Clermont Columbiana Coshocton Gallia Guernsey Harrison Highland Hocking Holmes Jackson
Jefferson Lawrence Meigs Monroe Morgan Muskingum Noble Perry Pike Ross Scioto Tuscarawas Vinton Washington
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MARIONMORROW
KN O X
HENRY
PUTNAM
LAWRENCE
PIKE
ATHENS
COSHOCTON
HOLMES
FAIRFIELD
HOCKING
JACKSON
SCIOTO
HIGHLAND
ROSS
FAYETTEPICKAWAYGREENE
BELMONTMUSKINGUM
MEIGS
VINTON
WASHINGTON
MORGAN
PERRYMONROE
GUERNSEY
P0RTAGE
HARRISON
JEFFERSON
RICHLAND
SENECA
HARDIN
SANDUSKY
LICKING
DELAWARE
MADISON
FRANKLIN
CHAMPAIGN
MAMI
DARKE
PREBLEMONTGOMERY
CARROLL
BROWN
CLER-MONT
HURON
ERIE
ASHLAND
WYANDOT CRAWFORD WAYNE
CUYAHOGALORAIN
SUMMIT
LAKE
ASHTABULA
TRUMBULL
GEAUGA
MAHONING
COLUMBIANASTARK
NOBLE
GALLIA
CLINTONWARREN
SHELBY
WILLIAMS
MERCER
ALLEN
AUGLAIZE
HANCOCK
VAN WERT
FULTONLUCAS
WOOD
OTTAWA
LOGAN
UNION
CLARK
Ohio Regions
BUTLER
ADAMS
MEDINA
TUSCARAWAS
PAULDING
DEFIANCE
HAMILTON
Legend
Appalachian
Rural, Non-Appalachian
Suburban
Metropolitan
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Disposition at Discharge Categories
Assessment and Evaluation Only (2) Successfully Completed no Further Services
Recommended Client Rejected Recommendations
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Disposition at Discharge Categories (continued)
Neutral (8)
Left on Own Against Staff Advice WITH Satisfactory Progress
Incarcerated Due to Old Warrant/Charge from Before Entering Treatment (Satisfactory or Unsatisfactory)
Transferred to Another Facility for Health Reasons Death Client Moved Needed Services Not Available Other
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Disposition at Discharge Categories (continued)
Referral (2) Referred to Another Program or Service (Satisfactory or Unsatisfactory)
Successful (1)
Successful Completion/Graduate
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Disposition at Discharge Categories (continued)
Unsuccessful (5)
Left on Own Against Staff Advice WITHOUT Satisfactory Progress
Involuntarily Discharged Due to Non-Participation
Involuntarily Discharged Due to Violation of Rules
Incarcerated Due to Offense Committed While in Treatment/Recovery (satisfactory or unsatisfactory)
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Table Figures – Disposition at Discharge
Number of Client Episodes Period of time between admission and discharge for
each level of care The number of episodes for all discharge categories
Percent Percentage of episodes for each of the discharge
categories Percentile
The dispersion of measures as related to zero—the 50th percentile equals the median
Positive to Negative Ratio Percentage of positive and negative dispositions that are
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Results Over Time Chart
4/2011 - 3/2012
7/2011 - 6/2012
10/2011-9/2012
1/2012-12/2012
0.00
10.00
20.00
30.00
40.00
50.00
60.00
70.00
Assessment OnlyNeutralReferralSuccessfulUnsuccessful
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Disposition Data for Chart
Assessment Only Neutral Referral Successful Unsuccessful
4/2011 - 3/2012 4.64 3.93 62.62 7.74 21.07
7/2011 - 6/2012 5.85 4.53 57.10 9.25 23.21
10/2011-9/2012 4.22 4.82 61.75 8.30 20.79
1/2012-12/2012 1.00 1.00 64.20 8.02 19.75
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Review - Basis for Reports
Unduplicated client data (at the provider level)
from existing data in OHBH and MACSIS Admission dates are used for reporting; last
admission is used when there are multiple admissions in a quarter
Data only reported for clients with both an admission record and a discharge record
Clinical services are used to determine retention
Any change in a level of care is considered a new Episode of Care (not the case for OHBH)
UPID is used for provider dataQuality Management - Webinar Series #1 - Spring 2012
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Subgroup Reports
Level of Care Outpatient Residential
Drug of Choice Alcohol Marijuana Cocaine/Crack Heroin Other Opiates Other
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Subgroup Reports - Population Groups
Age Adolescents (12-17)
Young adults (18-25)
Adults (18+)
Older adults (60+)
Criminal justice Deaf or hard of
hearing Dually diagnosed
Gender Mental health
history Methamphetamin
e using Opiate using Poly-substance
using Referral
disposition Service member
or veteran
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Why This QM Approach Now? To respond to the Substance Abuse
Treatment and Prevention (SAPT) Block Grant States must demonstrate the capacity and
capability to make data-driven decisions based on performance measures
ODADAS received SAMHSA Technical Assistance Planning and Outcomes Committees Other states’ systems
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Quality Improvements
Programmatic Better serve needs of clients Improve client outcomes Improve program efficiencies
Policy Inconsistent Missing Unclear
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Quality Improvements (continued)
Procedural Clinical Administrative
Human Resource* Caution: Position descriptions, supervision, training
and communication factors need to be explored before aligning results with people
Other Combination of factors such as funding, staffing,
facilities, operations, etc. * It is usually best to target improvements at the organizational level
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Accessing Reports
Login to OHBH - http://prod.ada.ohio.gov Choose “Production” as environment Choose “OHBH” as application Choose “Reports” from main menu Click the link “Quality Management
Reports” at the far right side of the page
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Accessing Reports (continued)
Each PDF file is labeled with the measure, date and subgroup (if applicable)
Files are ordered by ascending UPID numbers
Use (“CTRL-F” or go to “Edit” then “Find”) to locate your report by UPID or provider name
Summary reports are also available Documentation available on site at
“Click Here” or the ODADAS web site– www.odadas.ohio.gov
“Services,” NIATx,” “Quality Management System”
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Next Steps
Complete the webinar series to introduce the system
Organize questions and comments; determine utility Make modifications to reports and
documentation Solicit volunteers to work with ODADAS Test new ideas (as applicable)
Develop subgroup reports Continue webinars series and technical assistance Encourage networking and peer support
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The End
Questions, Comments and Ideas
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