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Cross-system Utilization using

Three Years of Data

Paul Stiles, J.D., Ph.D. Diane Haynes, M.A.

813) 974-9349 [voice] (813) 974-8209 [voice]

stiles@fmhi.usf.edu haynes@fmhi.usf.edu

Policy & Services Research Data Center

Department of Mental Health Law & Policy

Louis de la Parte Florida Mental Health Institute

University of South Florida

13301 Bruce B. Downs Blvd.

Tampa, FL 33612

Pinellas Data Collaborative

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PDC Background

Established under F.S. 163 Several organizations in county

participating including:– BOCC -- DJJ– DSS -- JWB– Courts/Sheriff -- DCF– EMS --FMHI (repository)

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Data Sets

Criminal Justice [CJIS]

Dept of Social Services [DSS]

DCF/ADM [IDS]

Medicaid [AHCA]

Juvenile Welfare Board [JWB]

Child Welfare [CW]

Emergency Medical Services [EMS]

Baker Act [BA]

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On-going Questions/Analyses Use and cost of Acute Care (Baker Act) services in the county

Use of Acute Care (Baker Act) by children

Overlap of identified population (PEMHS) in JWB that are in Medicaid

Network Analysis on Individuals Dealing with Substance Abuse

Continuity of Care Study (GPW Closing)

How many kids being served by JWB are also involved in the Child Welfare system?

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Cross Systems Utilization:Initial Questions

What is the measure/degree to which adults and children in the 8 systems have caseload overlap for over a three year period (1998-2001)?

What is the measure/degree to which high users in the systems have caseload overlap over a three year period (1998-2001)?

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Overview

The Eight Systems

The Statistical Method used in this study

Findings

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Eight Systems Included in this Study

Criminal Justice [CJIS]

Dept of Social Services [DSS]

DCF/ADM [IDS]

Medicaid [AHCA]

Juvenile Welfare Board [JWB]

Child Welfare [CW]

Emergency Medical Services [EMS]

Baker Act [BA]

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• CJIS 35%

• DSS 34%

• EMS 24%

• IDS 58%

• MMH 77%

• JWB 19%

• CW 24%

• BA 21%

• CJIS35%

• DSS36%

• EMS24%

• IDS51%

• MMH 79%

• JWB15%

• CW15%

• BA15%

Between 1998 and 1999 Between 1999 and 2000 Between 1998 and 2000

• CJIS 25 %

• DSS 21 %

• EMS 19 %

• IDS44%

• MMH 64%

• JWB34%

• CW13%

• BA 13 %

Overlap within each system across years - All

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• CJIS 28%

• DSS 33%

• EMS 18%

• IDS 55%

• MMH 56%

• JWB 8%

• CW 65%

• BA 38%

• CJIS26%

• DSS29%

• EMS19%

• IDS41%

• MMH 57%

• JWB3%

• CW58%

• BA18%

Between 1998 and 1999 Between 1999 and 2000 Between 1998 and 2000

• CJIS14%

• DSS13%

• EMS11%

• IDS21%

• MMH 40%

• JWB0%

• CW53%

• BA13%

Overlap within each system across years - HH

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Statistical Method

Probabilistic Population Estimation (PPE)

Caseload Segregation/Integration Ratio (C-SIR)

This process relies on information in existing databases and the agencies do not have to share unique person identifiers. It avoids the expense of case-by-case matching and sensitive issues of client-patient confidentiality.

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Probabilistic Population Estimation (PPE) A statistical method for determining the number of people

represented in a data set that does not contain a unique identifier. The estimation is based on a comparison of information on the distribution of Date of Birth and Gender in the general population with the distribution of Date of Birth and Gender observed in the data sets.

The number of distinct birthday/gender combinations that occurred in each data subset are counted. The number of people necessary to produce the observed number of birthday/gender combinations are then calculated.

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Caseload Segregation/Integration Ratio (C-SIR)

C-SIR =

C-SIR is a rating between 0 and 100 which indicates the amount of overlap of clients between agencies.

Zero being no overlap at all and 100 being total overlap.

Duplicated Count

Unduplicated Count

- 1

Duplicated Count

Largest Undup. Count- 1 * 100

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One year Overlap/C-Sir (44)

IDS

MMH

7,447

  3,996

3,131

 

 

Unique ID Count PPE Count Population Cross

MMH 7,104 7,127 56.06%

IDS 11,640 11,443 34.92%

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Findings from last year’s analysis There is very little overlap in users between the

systems that were looked at.

The caseload integration/segregation rating in this study varied from 5 to 44 on a scale of 0 to 100. The greatest overlap is between IDS and MMH, the mental health systems

It is the non-high users that are more likely to cross multiple systems, not the high users. If an individual is a high user in one system, they probably are not in the other systems.

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Three Year Overlap/C-Sir-AdultsTotal Population

Rate

# of IndWho

OverlapMMH & IDS 40 6,548

MMH & DSS 28 9,514

MMH & CJIS 26 32,154

IDS & DSS 16 3,317

IDS & CJIS 40 6,563

DSS & CJIS 43 13,973

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Three Year Overlap/C-Sir-KidsTotal Population

Rate# of Ind

Who OverlapMMH & IDS 69 3,062

MMH & DSS 100 626

MMH & CJIS 95 135

IDS & DSS 4 26

IDS & CJIS 67 97

DSS & CJIS 1 2

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Three Year Overlap/C-Sir-Adults“Heavy Hitters”

Rate

# of IndWho

OverlapMMH & IDS 52 517

MMH & DSS 3 97

MMH & CJIS 2 124

IDS & DSS <1 6

IDS & CJIS 7 64

DSS & CJIS 3 86

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Three Year Overlap/C-Sir-Kids“Heavy Hitters”

Rate

# of IndWho

OverlapMMH & IDS 76 349

MMH & DSS * *

MMH & CJIS 3 2

IDS & DSS * *

IDS & CJIS <1 0

DSS & CJIS * *

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Overlap/C-Sir JWB & CW

JWB Child Welfare

48,639 23,720

17,563

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Overlap/C-Sir EMS & IDS/MMH/BA (All Age Groups)

Rate# of IndWho Overlap

EMS & IDS 7 105EMS & MMH 14 29,948EMS & BA 62 5,146

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We need your help!!

Help with what systems to cross Help with predicted pathways (so that

we can look at service use patterns over time)

Help selecting other systems to include (e.g., Education?)

Help with interpretation

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Demographics (ALL-Adults)

0

20

40

60

80

100

CW

BA

DS

SJW

BID

SM

MH

EM

SC

JISFemale

Male

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Demographics (ALL-Kids)

0

20

40

60

80

100

CW

BA

DS

SJW

BID

SM

MH

EM

SC

JIS

Female

Male

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Reference 

Banks, S. & Pandiani, J. (1998). The use of state and general hospitals for inpatient psychiatric care. American Journal of Public Health, 99(3), 448-451.

  

Banks, S., Pandiani, Gauvin, L, Readon, M.E., Schacht, L., & Zovistoski, A. (1998). Practice patterns and hospitalization rates. Administration and Policy in Mental Health, 26(1), 33-44.

 Banks, S, Pandiani, J. & James, B (1999). Caseload segregation/integration: A measure of shared responsibility for children & adolescents. Journal of Emotional & Behavioral Disorders, 7(2), p 66-17.

 Banks, S, Pandiani, J., Bagdon, W., & Schacht, L. (1999). Causes and Consequences of Caseload Segregation/Integration. 12th Annual Research Conference (1999) Proceedings, Research and Training Center for Children’s Mental Health.

 Pandiani, J., Banks, S., & Gauvin, L. (1997). A global measure of access to mental health services for a managed care environment. The Journal of Mental Health Administration, 24(3), 268-277.