Solutions Consulting Group, LLC

Prevalence Rates:  A Working Model and 2 State experiences

Presenters:Karleen Goldhammer-ConsultantMary Ann Discenza (VA) - Part C

CoordinatorLizette Stiehr (AK) - Agency

DirectorFebruary 7, 2005

Why is Prevalence important to know?

Benchmarks and planningSystem designFinancingIdentifying resource and support needsQuality assuranceEquityWell being of childrenLong and short term service gap identification

Virginia’s Plan - ContextRe-design the finance system to reflect the:– Demographic, – Political and – Economic context of the Commonwealth

Implement an integrated data system to assist– Local EI systems in decision-making and

management Renew state interagency agreements and service contracts– Clearly establish the parameters of the service

delivery approachIncrease knowledge of, and access to: – Potential formal funding at the state, local, and

community level– Informal community resources and supports

Virginia - Why a Cost Study?

The purpose and design of the cost study were to understand the total cost of Virginia’s Part C System; andTo answer the question how many children should be served given Virginia’s definition of eligibility.

Information gained through the Cost Study?

Statewide total cost of early intervention in VirginiaAverage hourly cost per direct service personRatio of direct services to administrative and support costsCost difference relating to different personnel types/disciplines.Number of children we should be servingThe cost for serving all potentially eligible children

Alaska-Why did we do it?

Leaders within Alaska’s early intervention system have identified this question as a critical priority area to be addressed within the scope of a strategic work plan and have dedicated resources to address the issue.

Alaska- Project Status

Spent time with a Prevalence Committee pulling a working model together through 2004Presented information to a larger stakeholder group for input and reaction (11/04)Collected stakeholder thought and inputEstablished targets and other recommendationsIdentified recommended use for the informationDraft report currently in review

IDEA Part C Eligibility

CategoriesChildren who have a diagnosed mental or physical condition that has a high probability of resulting in developmental delay. (Required)

Children experiencing developmental delays. (Required)

Children at-risk of having substantial delays (9/ 56=16%). (Optional)

National Early Intervention Longitudinal Study (NEILS) Data Report

64.1

20.415.5

0

10

20

30

40

50

60

70

Reasons for Receipt of EIService

A DevelopmentalDelay

A DiagnosedCondition

At Risk forDevelopmentalDelay

WASHINGTON

OREGON

MONTANA

IDAHO

NEVADA

CALIFORNIA

UTAH

WYOMING

COLORADO

ARIZONANEW MEXICO

NORTH DAKOTA

SOUTH DAKOTA

NEBRASKA

KANSAS

OKLAHOMA

TEXAS

ALASKA

HAWAII

PUERTO RICO

LA

ARKANSAS

MS ALABAMA GEORGIA

FL

SO.CAROLINA

NO.CAROLINATENNESSEE

KENTUCKYMISSOURI VIRGINIA

WV

ILLINOIS INOHIO

IOWA

MINNESOTA

WISCONSIN

MICHIGAN

PENNSYLVANIA

NEW YORK

MAINE

CT

VT

MA

DCNJ

NH

MD

DE

RI

Percent Served

Less than 1%

1% to <1.5%

1.5% to <2%

2% to <3%

Map 1

Percentage (Based on 2000 Census Population) of Infants and Toddlers Ages Birth Through 36 Months Served Under IDEA, Part C

in 2002 (excludes At-Risk)

Note: Data as of August 30, 2003.

Because the criteria for Part C eligibility varies widely across states, differences in identification rates on this map should be interpreted with caution. Please see Data Notes for an explanation of individual state differences on how data are reported.

Source: U.S. Department of Education, Office of Special Education Programs, Data Analysis System (DANS).

3% or higher

IDEA Part CPercentage of children under the age of 3 receiving services as of 12/1/2003 (excludes at-risk)

= 2% level

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Mo

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Data Source: Westat

Hawaii 7.70

Massachusetts 5.92

Indiana 3.62

Wyoming 3.57

Vermont 3.42

Pennsylvania 2.94Delaware 2.90

New Mexico 2.89Maine (ED) 2.77

West Virginia 2.73South Dakota (ED) 2.66

Wisconsin 2.66

New Hampshire 2.61

Maryland (ED) 2.60Arkansas 2.46

Kansas 2.40

Florida 2.28

Michigan (ED) 2.13Iowa (ED) 1.95

Ohio 1.81

Minnesota (ED) 1.78

Louisiana 1.75

North Carolina1.66Colorado (ED) 1.56Washington 1.56

Mississippi 1.53

Virginia 1.40

Alabama 1.20

New York 4.42

Rhode Island 3.48Connecticut 2.96

Idaho 2.44

Illinois 2.42

Kentucky 2.37

New Jersey 2.36

Tennessee (ED) 1.81

Texas 1.81

California 1.76

Nebraska (ED)1.70Utah

1.69Oregon (ED) 1.38

Georgia 1.19

South Carolina 1.04

Oklahoma (ED) 2.24

Alaska 2.17

North Dakota 2.13

Montana 1.95

Missouri (ED) 1.51

Arizona 1.39

DC 1.13

Nevada .94

Virginia’s Part C - Eligibility

“Early intervention services" means services provided through Part C of the Individuals with Disabilities Education Act (20 U.S.C. § 1431 et seq.), as amended, designed to meet the developmental needs of each child and the needs of the family related to enhancing the child's development and provided to children from birth to age three who have (i) a twenty-five percent developmental delay in one or more areas of development, (ii) atypical development, or (iii) a handicapping condition.

Virginia - Children in Service

Year Child Count % of Population

1997 2,393 .9%

1998 2,651 1.0%

1999 3,010 1.1%

2000 3,110 1.1%

2001 3,497 1.2%

2002 4,163 1.4%

2003 4,173 1.4%Note: May not include 2 year olds served by the schools

How Many Children Are Currently in Service?

Virginia has a mandate for 2 year olds to optionally be served within the public school system.

Using DOE combined data for the 2002 and 2003 Child Count, Virginia is currently serving 5,197 children or 1.9% of children 0-3 in the Commonwealth.

Alaska’s Part C Eligibility

Children who experience developmental delays of 50% or greater, or who experience a diagnosed condition (such as Down syndrome, Autism, Fetal Alcohol Syndrome (FAS)), likely to result in a 50% developmental delay, are entitled to services.

Alaska - Children in Service

Year Child Count % of Population

1997 466 1.6%

1998 499 1.7%

1999 585 2.0%

2000 651 2.3%

2001 634 2.2%

2002 646 2.1%

2003 638 2.2%

How do you count the number of children currently served in the system?

– Child Count 12/1 of each year

– Aggregate Count

– Referrals not moving to eligibility

– Eligible children not completing

an Individualized Family Service

Plan

Children Served by the Part C System

Child Count (Point in Time)

Aggregate Count (Over the Year)

Eligible but do notproceed to IFSP

Referred but do notproceed to Eligibility

How many children should we serve?

Establish the population base

Review the eligibility definition

Tally the number of children currently served

Select a projection model

Collect data to build a statewide composite number

Decide how it will play a role in your system

Continue to review, refine and enhance

Model Options

A single statistic, such as low birth weight

Epidemiological Model

Variables Model

Prevalence Concept

The premise of the estimated prevalence model used for Alaska and Virginia is rooted in the notion that all communities within a single Part C system should serve the same percentage of children EXCEPT for accounting (indexing) for community differences in population characteristics that are likely predictors of participation in early intervention.

Variables Model Concept Proposed as an alternative to an epidemiological model

– Limited data exists regarding the prevalence rate of children with developmental delay

– Complexity of identifying which diagnosis are eligible

Establishes the highest credible percentage of children currently in service as the benchmark

– Review for issues of over or under identification – Look for possible weaknesses in the eligibility determination

process– Conduct forums or interviews in targeted communities

Compare community differences to benchmark community– Review county level characteristics that influence early

intervention participation

Project the target prevalence rate given today’s service levels

– Establishes the minimum threshold rather than a maximum

Review and adjust

Model Mechanics

1. 0-3 or 0-4 population numbers by county (FIPS code) 2. Identify desired variables such as Pre Term Births,

Children in Poverty, No Prenatal Care, Maternal Education etc. 

• Sum the variable• Optionally you may weight the variables then sum 

3. Child Count/Aggregate by geography• Establish the county with the highest % of children served

• Validity and credibility are crucial

4. Compute the index • Highest percentage of children in service divided by summary percentage of

variables

5. Establish the percentage of children to be served based• Apply the index to all of the other sums of variables

6. Compare the number of children in service to the projected estimate of eligible children

• Growth will not occur immediately

Geographic Issues to Consider

Cities, towns & villages

Census tracts

Counties, Boroughs

Metropolitan area

Census areas

Federal Information Processing Standards

(FIPS)

Regions

Demographic & Health Risk Factors

Being a member of a minorityBeing in foster careBeing in a low-income household ($25,000 or less annually)Having a primary female caregiver with less than a high school educationHaving a female caregiver who was < 17 years old Living in a household with only one parentLiving in a household with one or more other children with special needsLiving in a household with four or more childrenAdequacy of housing rated as fair or poorAdequacy of transportation rated as fair or poor.Birth WeightGestational AgeMedical Complications

Suggested Characteristics for Variables

Population based rather than participatory counts. The information should be readily available with a long history of collection. Alignment with state demographics. The quantity of information for both the numerator and denominator need to be sufficient enough in size to be statistically reliable.

Alaska-Initial Variables Discussed

– Number of children diagnosed with Fetal Alcohol Syndrome (FAS)

– Number of children diagnosed with Fetal Alcohol Effect (FAE)

– Unduplicated count of substantiated reports of harm

– Number of children whose mother smoked during pregnancy

– Number of children born at or below 32 weeks gestation

– Number of children born to mothers age 17 yrs or less at time of birth

– Number of children in foster care

AK – Variables ModeledSubstantiated Reports of Harm 1999-2003– A data report from PROBER© through the DHSS/OCS was

used that tallies the number of substantiated reports of harm for children under age 3 for five (5) year period from fiscal year 1999 through fiscal year 2003.

Poverty Index 1999– (http://www.ers.usda.gov/Data/PovertyRates) and includes

Related Children under 18 years of age Pre Term Births 1998-2000– Data from the Alaska Department of Health website (

http://www.hss.state.ak.us/dph/bvs/birth_statistics/Profiles_Census/default.htm) was used and represents the number of infants born at less than 37 weeks gestation over the total number of live births for the period.

Late or No PNC 1998-2000– This variable includes the combined percentage of No

Prenatal Care and the percentage where prenatal care began in the third trimester.

< 12 Yrs education 1998-2000 – The percentage of the population with less than 12 years

of education was obtained from the DOH vital statistics website

Virginia- Variable Categories Discussed General

Demographics Race/ethnicity

Information Populations Of Special

Consideration Pregnancy And Birth

Information Health Challenges And

Child Welfare Issues Family Households

Child Count Data Part B/3-5 Preschool

Eligibility Medicaid/SCHIP

Eligible And/or Enrolled

Income Information Eligibility

Information Local Economic

Resources

Virginia - Selected Variables

HS Dropouts-2002Very Low Birth Weight 1998-2001Poverty Rates for Related Children under 18 years 1999(Weighted)

AK & VA Model Results

Statewide ProjectionRange (Hi, Low)

Fitting it All Together

Decide on your approach

Build your model at the appropriate geographic level

Collect your data/identify missing data

Routinely use the information

Review and adjust the estimate

Don’t be afraid to start!

Practical Uses for the DataDiscussion at Local Coordination Meetings with other community members

– Head Start– Local public school– Other health care providers– Other community resources

Grant application planning– Child Find and intake activity– Provide for additional review at the community level – Establish a targeted growth plan using the estimated prevalence number

Evaluation of system resources (people, time & money)– Provider availability– Funding– Allocation systems

Data analysis and verification– Validity of Child Count numbers– Relationship between child count and aggregate count (turnover ratio)

Quality assurance

Population Base by Alaska Census Area (2000)

FIPS Geography (N=27) T. Pop 0-3 % of Total 0-3 T. Pop 0-4 % of Total 0-4

02013 Aleutians East 71 0.3% 91 0.2%

02016 Aleutians West 123 0.4% 180 0.5%

02020 Anchorage 12000 42.9% 15,788 42.2%

02050 Bethel 933 3.3% 1,260 3.4%

02060 Bristol Bay 50 0.2% 73 0.2%

02068 Denali 64 0.2% 78 0.2%

02070 Dillingham 277 1.0% 381 1.0%

02090 Fairbanks North Star 3970 14.2% 5,321 14.2%

02100 Haines 69 0.2% 102 0.3%

02110 Juneau City and Borough 1160 4.1% 1,523 4.1%

02122 Kenai Peninsula 1942 6.9% 2,600 6.9%

02130 Ketchikan Gateway 527 1.9% 763 2.0%

02150 Kodiak Island 793 2.8% 1,068 2.9%

02164 Lake and Peninsula 79 0.3% 97 0.3%

02170 Matanuska-Susitna 2272 8.1% 3,182 8.5%

02180 Nome 451 1.6% 644 1.7%

02185 North Slope 419 1.5% 555 1.5%

02188 Northwest Arctic 441 1.6% 595 1.6%

02201

Prince of Wales-Outer Ketchikan 282 1.0% 359 1.0%

02220 Sitka City and Borough 320 1.1% 384 1.0%

02232 Skagway-Hoonah-Angoon 120 0.4% 155 0.4%

02240 Southeast Fairbanks 234 0.8% 338 0.9%

02261 Valdez-Cordova 374 1.3% 514 1.4%

02270 Wade Hampton 404 1.4% 594 1.6%

02280 Wrangell-Petersburg 282 1.0% 361 1.0%

02282 Yakutat City and Borough 25 0.1% 42 0.1%

02290 Yukon-Koyukuk 279 1.0% 387 1.0%

  State of Alaska 27961   37,435  

Alaska’s Population Base 0-3: 2000

Percentage of Children in Service – Alaska 2.28% Statewide

Within 1 standard deviation of the mean Below 1 standard deviation of the mean

1.36% Northwest Arctic Borough 0.00% Aleutians West

1.41% Aleutians East Borough 0.00% Denali

1.58% Matanuska-Susitna Borough 0.00% Yakutat City and Borough

1.60% Valdez/Cordova 0.31% City & Borough of Sitka

1.67% North Slope Borough 1.01% Kodiak Island Borough

1.71% Southeast Fairbanks

1.79% Yukon-Koyukuk Above 1 standard deviation of the mean

1.99% Fairbanks North Star Borough 3.77% Nome

2.09% Ketchikan Gateway Borough 3.80% Lake & Peninsula Borough

2.27% Kenai Peninsula Borough 4.00% Bristol Bay Borough

2.48% Prince of Wales 4.35% Haines Borough

2.57% Bethel

2.58% Municipality of Anchorage

2.67% City & Borough of Juneau

2.84% Wrangell-Petersburg

2.89% Dillingham

3.22% Wade Hampton

3.33% Skagway-Angoon

Virginia’s Early Intervention System

Number of children served 4,173Eligibility definition (broad) (25% delay in one or more

developmental areas, atypical development or a handicapping condition)

Local autonomy

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40

Children in Service 12/1/2003 as a Percentage of Total 0-3 Year Olds by Local Council Area

Alaska- Community Variables Modeled

1. Substantiated Reports of Harm 1999-2003

2. Pre-Term Births 1998-20003. Late or No PNC 1998-20004. < 12 Years Education 1998-

20005. Poverty Index 1999

Alaska-Community Variables

Census AreaPov. Index

99PreTerm Bir. 98-

00Late or No PNC 98-

00< 12 Yrs Edu.98-

00**Substan. Rpts of Harm

99-03

Aleutians East 6.8% 4.8% 1.6% 6.9% 2.80%

Aleutians West 6.0% 4.3% 6.4% 12.0% 22.80%

Anchorage 8.8% 10.7% 2.5% 12.7% 18.10%

Bethel 24.5% 12.3% 10.6% 20.0% 40.30%

Bristol Bay 10.7% 7.5% 3.8% 8.0% 0.80%

Denali 10.2% 10.5% 3.7% 10.7% 3.10%

Dillingham 26.6% 11.6% 18.6% 16.1% 26.00%

Fairbanks North Star 8.4% 9.6% 5.9% 9.9% 17.30%

Haines 14.6% 7.6% 5.1% 6.9% 2.90%

Juneau City and 6.7% 9.3% 2.1% 10.3% 23.40%

Kenai Peninsula 12.0% 10.1% 4.9% 13.5% 17.20%

Ketchikan Gateway 7.5% 9.7% 6.0% 14.6% 16.70%

Kodiak Island 6.7% 9.4% 5.1% 12.5% 7.10%

Lake and Peninsula 21.0% 12.5% 3.8% 24.4% 13.90%

Matanuska-Susitna 13.2% 9.1% 5.9% 12.8% 12.90%

Nome 20.0% 13.7% 12.0% 22.8% 38.10%

North Slope 9.0% 13.1% 7.8% 30.2% 39.40%

Northwest Arctic 19.7% 14.9% 5.3% 29.2% 23.40%

Prince of Wales-Outer Ketchikan 13.7% 6.9% 3.1% 14.0% 12.10%

Sitka City and 9.2% 8.4% 3.8% 11.5% 14.10%

Skagway-Hoonah-Angoon 15.0% 5.7% 2.6% 18.8% 9.20%

Southeast Fairbanks 20.8% 5.6% 10.6% 13.1% 23.10%

Valdez-Cordova 9.7% 9.0% 4.4% 9.8% 8.80%

Wade Hampton 29.4% 12.7% 11.4% 26.3% 53.50%

Wrangell-Petersburg 9.3% 5.1% 2.4% 12.9% 16.70%

Yakutat City and 22.5% 5.6% 5.6% 6.3% 4.00%

Yukon-Koyukuk 26.7% 11.1% 8.2% 18.9% 43.70%

State of Alaska 11.2% 10.3% 4.7% 13.7% 20.80%

Alaska - ModelsModel 1

Substantiated Reports of Harm 1999-2003Pre-Term Births 1998-2000Late or No PNC 1998-2000< 12 Yrs education 1998-2000

Model 2Pre-Term Births 1998-2000Late or No PNC 1998-2000< 12 Yrs education 1998-2000

Model 3Pre-Term Births 1998-2000Late or No PNC 1998-2000< 12 Yrs education 1998-2000Poverty Index 1999

Alaska - Local Community Stakeholder Meetings

Collaboration w/ other community stakeholders who were helpful to validate the numbers.Concern about the system impact of doubling current service participation numbers.

Virginia - Variables

Stakeholders reviewed models with more than a dozen variables Unanimously agreed to use the following variables:

• High school drop-out rate• Very low birth weight• Poverty indicator

– No one variable should have any more or less of an influence in the final calculations.

• First two variables were weighted to an equivalency of 11.9

• An index was created and universally applied to each geographic designation to estimate the minimum number of children that should be served.

Virginia - Data Sources

Census data plus information traditionally collected by the State agency responsible for the Maternal Child Health Grant was used in this study

Virginia - Demographic Analysis

The Regional Profile is:– Designed to assist local and state

planners in short- and long-term planning;– Identifying the potential prevalence

locally of children eligible; and – Targeting specific regional or local

challenges that serve as barriers to accessing or providing services for the eligible population under Part C.

How Many Children Should Be Served in Virginia’s Part C System?

Virginia’s integrated work plan developed by stakeholders identified this question as a critical priority area to be addressed.

An outcome of the cost study was to identify the cost of serving all eligible children.For the 2002 data, Virginia ranked 24th of 29 of states with a broad eligibility definition.Based on the 12/1/2002 Child Count, Virginia is serving at 1.4% of the 0-2 population.

Virginia-The Process

Virginia attempted to use an epidemiological model to compute the number of children to be served within the early intervention system.Challenges with using this model:

– Not all children having a particular medical condition will be in need of service.

– There is a lack of data regarding very young children with developmental delay.

– The system relies on passive reporting requirements– Children are misdiagnosed– Children could be missed

48

Virginia Cares: Birth Defect Surveillance Data 1989-1998

The report:– Summarizes epidemiological and statistical

information about children born to Virginia residents.

– Spans 20 years.Of the 95,000 children born annually in Virginia, approximately 4,600 children are known to have birth defects.Nationally, between 3 and 5 percent of children born annually have birth defects.Virginia is within the range of 4.9%.

Virginia - Common Characteristics - Communities with Highest Levels of % of Children Served

Small communityWell-known by the physician communityCommunicate back with referral sourcesStable programLongevity of the primary contact person

Alaska - Common Characteristics of Communities with Highest Levels of % of Children Served

Small community The person and/or the organization are well known by the physician communityCommunication back with referral source about the outcome of the referral existsExistence of longstanding inclusive playgroups Stable program Longevity of the primary contact person

In ConclusionThe prevalence data from Virginia’s Cost Study provides a baseline of information that can be used in future system evaluation processes.

Virginia’s Challenges:– Lack of actual delivered service information

collected on a routine basis– Revenue information is substantially different

across the region and this has implications for fund stability

Virginia has a solid foundation to build an improved system for Virginia’s infants and toddlers and their families

What do you think?

How clear is the model?

Does any of this make sense?

What are the strengths?

What are the weaknesses?

How does this relate for you and your community?

Other thoughts?

Discussion Items: Referral

1. Is there a broad array of referral sources?2. What are the referral patterns?3. How aggressive is the child find effort?4. What kind of training occurs for potential

referral sources?5. How do you examine/review that over

identification of children is not playing a part in the number of children being served?

6. What is the rate of children referred to the number of children actually eligible?

Discussion Items: Eligibility Determination1.Describe the process of determining

child eligibility.2.Who is primarily responsible for

determining eligibility?3.Do they use a standardized process for

eligibility determination?4.What kind of training occurs for persons

determining eligibility?5.How often is informed clinical opinion

used?   

Discussion Items: Finance

1.Are there pockets of special considerations?

2.What are the service patterns? 3.Financial considerations? 4.Other community partnerships?

Request for Additional Information - VA

Mary Ann DiscenzaPart C Coordinator

Infant & Toddler Connection of Virginia(804) 371-6592

maryann.discenza@co.dmhmrsas.virginia.gov

Request for Additional Information-AK

Lizette Stiehr-DirectorFamily Outreach Center Under-standing Special

Needs, Inc. (FOCUS)PO Box 671750

Chugiak, AK 99567Tel: 907-688-0282

E-mail: lizette-stiehr@gci.net

Thank you for your participation!

Karleen R. GoldhammerSolutions Consulting Group, LLC

725 Riverside DriveAugusta, ME 04330 Tel: 207-623-8994

E-mail: Kgoldhamm@aol.com