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TRANSCRIPT
3/14/2014
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Data Mining for Cross
System Collaboration Claudia Zundel, M.S.W.
Diane Fox, Ph.D.
Nancy Johnson Nagel, Ph.D.
Colorado Department of Human Services
The Question…
• Who are the children and adolescents
currently utilizing high-cost intensive
behavioral health services that could
benefit from a System of Care approach?
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The Problem….
• How do we understand the array of
intensive services provided to children and
youth when
– Intensive services (residential treatment) are
provided through a variety of agencies and
funding sources
– Data systems are siloed and difficult to
integrate
Finding the Answers… • Step 1:
– How much is being spent by child serving agencies
on residential treatment and hospitalization?
• Step 2:
– How many unique children are served with these
intensive services?
– Are costs equally distributed to the children served?
– What happens to costs when children are involved
with multiple systems?
• Step 3:
– How many children are receiving services from
multiple agencies over the course of their lives?
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Step 1: Method for Compiling
Costs of Residential Treatment
• Contacted all agencies that pay for
residential and inpatient services – Child Welfare
– Office of Behavioral Health
• Non-Medicaid eligible
– Division of Youth Corrections
– Medicaid
• Asked for their total expenditures for a
single FY and the number of clients served
Residential and Inpatient
Expenditures for FY2010-11
Funding Agency Number of Children
Agency Expenditure
Additional Medicaid
Contribution Total
Child Welfare 2063 $51,719,376 $5,922,691 $57,642,068
Medicaid Inpatient 1287 $13,938,398 $13,938,398
DYC 577 $12,960,211 $1,495,839 $14,456,050
Medicaid Residential 462 $3,400,666 $3,400,666
Office of Behavioral Health (non-medicaid) 31 $656,148 $147,845.69 $803,993
Total 4420 $82,674,801 $7,566,376 $90,241,177
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Step 2: Determining How Many Unique
Children Were Served In the FY
• Went back and asked the same agencies
to provide lists of clients that they served
to comprise these costs
Barriers:
Confidentiality of data!
Success: Able to put in place business associates
agreements to obtain all the necessary data!
Children not identified with a universal identifier
Success: Used a constructed unique identifier in
combination with Medicaid ID to merge data sets
Clients in the Top Third of BHO Medicaid
Spending Accounted for 70% of the Total
Spending
33.3
8.0
33.3
22.0
33.3
70.0
0
10
20
30
40
50
60
70
80
90
100
% of Clients % of Total Medicaid Spending
Per
cen
t
Highest 1/3
Middle 1/3
Lowest 1/3
Cost per client:
$23,398.34
Cost per client:
$7,207.73
Cost per client:
$2,611.57
*Clients were grouped into three equal groups (high, medium, and low utilizers) then their % of total
spending and cost per client were calculated
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Unique Clients Served in Residential and
Inpatient Settings in a SINGLE Fiscal Year
• Result: There were 3,888 unduplicated youth
– 488 (12.6%)children/youth were served by multiple systems
87.4
11.5 1.1
0
10
20
30
40
50
60
70
80
90
100
Per
cen
t Three Agencies
Two Agencies
Single Agency
Step 3: Determining how many children are
receiving services in multiple systems
• First looked at a single large urban county
to see the overlap between
– Child Welfare (high utlizers)
– Youth Corrections
– Mental Health Services
– Substance Abuse Services
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How this Data was Used
• Provided justification for the creation of a
Care Management Entity Pilot site in the
county.
– Currently serving high needs youth in the
community
Taking That Analyses Statewide
• The Colorado State Division of Child Welfare (DCW) provided data
for the top 20% of children in Colorado who generated the highest
expenditures in Child Welfare in FY2011-2012. The sample was
comprised of 1881 children.
• Historical data that included any case open on July 1, 2006 or later
were obtained from
– Division of Youth Corrections and
– Office of Behavioral Health (mental health and substance data).
• These data were then merged with the data from Child Welfare to
determine the overlap between child welfare, juvenile justice,
substance abuse, and mental health services for these 1881
children.
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System Overlap for youth
with high CW costs
CW/MH/DYC, n=854, 45%
of CW has DYC & MH
CW/DYC, n=28, 1.5% of
CW has DYC only
CW/SA, n=6, 0.3% of CW has
SA only
CW/MH/SA, n=100, 5.3%
of CW has MH and SA
CW/MH, n=883, 47%
of CW has MH only
CW/DYC/MH/SA, n=266, 14% of
CW has all
CW/DYC/SA, n=10, 0.5%
of CW has DYC and SA
CW Only n=113, 6.3%
Who are the youth being seen?
Age Distributions by System Involvement
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Policy
• IMPLICATIONS
– Need for System Collaboration and Coordinated
Care; System of Care approach
– Streamline systems for efficiency and seamless care
• IMPACTS
– Establishing a Care Management Entity in One
County
– Mental Health Staff housed at Medicaid
– Medicaid Recommendations
Policy
• QUESTIONS!
– Who are the youth served in the various systems and
when is the best time to intervene?
– Is there a common path or trajectory through the
systems ?
– How do changes in one system affect other systems?
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Discuss
• What system of care questions might be
addressed with cross system data?
• What systems would be involved?
• What barriers might exist to obtaining
these data?
• Any ideas that you would like to discuss
with the group?
Great Sand Dunes National Park, Colorado