Building Local Capacity for Data Analysis and Use
Sharon Walsh, Data Accountability Center (DAC)Mary Anne White, Infant & Toddler Connection of VAHaidee Bernstein, Data Accountability Center (DAC)Beverly Crouse, Infant & Toddler Connection of VA
Data Accountability CenterGoal
Form partnerships in states that join state and local agencies in the use
of data to drive improved results
PremisesData Use Involves:• Working through a Collaborative
Team approach.• Engaging Team in a Continuous
Improvement Process.• Relating the Data to specific
Problem/Issue.
Using Data is an Iterative Process!
There is a Process for Using Data to
Improve Performance!
Important Points for Helping Local Data teams
Be SuccessfulHow do you maximize data you
already collect and collect what you need?
How do you organize your staff and your agency around ongoing data use?
Its all about continuous improvement Use data to determine priority for
focusIt is important to “drill down” to
understand performance to identify meaningful solutions
1. Identify relevant data
2. Conduct data analysis to generate hypothesis3. Test
Hypothesis to determine root cause
4. Plan for Improvement
5. Evaluate Progress
Data Analytics
Inquiry
Actio
n
DATA ACCOUNTABILITY CENTERDATA ANALYTICS
Historical PerspectiveVirginia’s 2008 Determination
Status
Work with DAC
Leadership Academy (April
2010)
Data Analysis Modules
Historical Perspective
Historical PerspectiveLeadership Academy April 2010
Two Sessions Held: Plenary & BreakoutPlenary:
overview of use of quality of dataBreakout sessions:
Use of actual local dataResults:Positive feedback from meeting evaluationsWanted more time to spend on the activityFirst activity in all CAP or SEP’s developed
requires a data analysis be completed
Historical Perspective
Standards and PrinciplesUse data on
a regular basis
Use data for continuous
improvement
Verify the accuracy of your data
Make sure you have the right team at each
step
Own your data
Use a process to determine how much data is
needed
Haidee’s stuffToday, we are officially showing some of the slides and explaining the process and rationale
From Notes to PowerPoint
From PowerPoint to Lectora
PowerPoint Lectora Final Product
• Why engage in this process• Types of Data
Module 1: Overview
• Identify people to look at the data• Define the problem(s)
Module 2: Preparation
• Identify Relevant Data• Conduct Data Analyses to Generate
Hypotheses• Consider and test Hypotheses
Module 3: Inquiry• Determine Actionable Causes• Develop and Implement Improvement Plans• Evaluate Progress
Module 4: Action
• Case StudyModule 5: Practice
Guide
Infant & Toddler Connection of1 Alexandria 11 Danville-Pittsylvania 21 the Highlands 31 Prince William, Manassas and Manassas Park2 the Alleghany Highlands 12 Dickenson 22 Loudoun 32 Rappahannock-Rapidan3 Arlington 13 Crater District 23 Middle Peninsula-N Neck 33 Rappahannock Area4 the Roanoke Valley 14 the Eastern Shore 24 Mount Rogers 34 the Blue Ridge5 Central Virginia 15 Fairfax-Falls Church 25 the New River Valley 35 Richmond6 Chesapeake 16 Goochland-Powhatan 26 Norfolk 36 the Rockbridge Area7 Chesterfield 17 Hampton-Newport News 27 Shenandoah Valley 37 Southside8 Williamsburg * James City * York * Poquouson 18 Hanover 28 the Piedmont 38 Valley9 Planning District 14 19 Harrisonburg-Rockingham 29 LENOWISCO
39 Virginia Beach10 Cumberland Mountain 20 Henrico-Charles City-New Kent 30 Portsmouth 40 Western Tidewater
Local Lead Agencies
Infant & Toddler Connection of1 Alexandria 11 Danville-Pittsylvania 21 the Highlands 31 Prince William, Manassas and Manassas Park2 the Alleghany Highlands 12 Dickenson 22 Loudoun 32 Rappahannock-Rapidan3 Arlington 13 Crater District 23 Middle Peninsula-N Neck 33 Rappahannock Area4 the Roanoke Valley 14 the Eastern Shore 24 Mount Rogers 34 the Blue Ridge5 Central Virginia 15 Fairfax-Falls Church 25 the New River Valley 35 Richmond6 Chesapeake 16 Goochland-Powhatan 26 Norfolk 36 the Rockbridge Area7 Chesterfield 17 Hampton-Newport News 27 Shenandoah Valley 37 Southside8 Williamsburg * James City * York * Poquouson 18 Hanover 28 the Piedmont 38 Valley9 Planning District 14 19 Harrisonburg-Rockingham 29 LENOWISCO
39 Virginia Beach10 Cumberland Mountain 20 Henrico-Charles City-New Kent 30 Portsmouth 40 Western Tidewater
Local Lead Agencies
Ways to Use DataIdentifying issues
Monitoring
System Planning
Improvement Activities
System oversight/man
agement
Approach to Improvement Planning
Monitorin
g Consultants
TA consultants
Local
System
Planned preparation
Possible ReactionsNegative Reactions
• Potential Roadblocks– I do not have time
for this– I already know this– I know the problems– I have the solutions
Positive Reactions• Potential
Facilitators– In the long run this
will save time– I didn’t know this
was possible – This information will
help me do my job better
– This information will help families
Proactive Versus ReactiveBoth are Positive
Check the data to ensure its accuracy
Determine program effectiveness. Develop a plan using local data
Proactive
Use available data to respond to a problem
Adjust plans that are in place after conducting data analysis
Reactive
What is Your Purpose
Reactive• Example: Responding
to an issue such as monitoring results
• Purpose: To address monitoring results that are below the state target
Proactive• Example: Conduct
quality review or assessment to determine areas of need
• Purpose: To Proactive look at the quality of dataGood Idea Good Idea
How Will Your Team Interact?
Who?Can
decipher the data?
Can bring new ideas?
Can make the
decisions?
Can translate data into policy?
Pre On-Site VisitWith Local System Managers
Discuss purpose of data analysis processDiscuss potential data team members Identify ITOTS reports to be reviewed Identify data from other sources that need to be reviewed
Pull three years worth of data
Desk AuditReview and analyze same data as local systemFormulate questions about data Identify additional data that may need to be collected
First On-Site Visit
Inqu
iryPr
epar
atio
n
3 . Identify Relevant Data
4 . Conduct Data Analysis to Generate Hypotheses
5 . Test Hypotheses to Determine Actionable Causes
1. Define and Articulate the Problem
2. Define the Problem/Issue
Beginning the Journey1. Complete the Preparation Phase and part of Inquiry
Phase2. Review the data reports
“What does the data tell you?” What are the good things the data is telling you? What surprises you about the data? What questions strike you as you look at the data? What data appears to be missing?
What are the good things the data is telling you? What data appears to be missing?
Review Multiple Source of Data
Record Reviews
Part C, Local and State data systems
During Inquiry Phase
Infant & Toddler Connection of Playground CityReferral Outcome by Referral Source
7/1/09 – 7/30/10
Referral Sources Evaluated Not Evaluated
Total Referral Source
Eval-Ineligible
Will Receive Services Total Unable to
ContactDeclined Screening
Declined Eval Total
Health 9 9 3 1 3 7 16
DSS 1 5 6 2 2 5 9 15
Doctor’s 1 10 11 4 5 8 17 28
Parent 3 10 13 1 6 7 20
Other 1 8 1 1 1 3 12
Totals 7 49 56 12 10 28 50 106
Infant and Toddler Connection of Playground CityReferral Outcome by Referral Source (7/01/09-
7/30/10)1. Information Local System
Gathered through this report:53% of all referrals are
evaluated; 47% are not evaluated– 46% of all referrals will
receive services– 6% of all referrals were
evaluated ineligible– 11% of all referrals were lost
to contracts– 9% of all referrals declined
screening26% of all referrals declined an
evaluation2. Physician Referrals: 26% of all
referrals3. Parent Referrals: 19% of all
referrals4. Health: 15% of all referrals5. Dept. of Social Services: 14% of
all referrals
A. Physician Referrals: 39% were evaluated; 69% were not evaluated. Of those not evaluated, 39% declined either screening or evaluation.
B. Family Referrals: 65% were evaluated; 35% were not evaluated. Of those not evaluated, 100% declined screening or evaluation.
C. Health Referrals: 56% were evaluated; 44% were not evaluated. Of those not evaluated, 43% were lost to contact and 57% declined screening or evaluation
D. DSS Referrals: 40% were evaluated; 60% were not evaluated. Of those not evaluated, 22% were lost to contact and 78% declined screening or evaluation
Additional Data Needed
• What is the average age of referrals?• Which physicians are referring?
Specific name versus name of practiceWhat is the average age of the physician referral?
• How do families hear about Part C services?• Why are families declining Part C services?
At what point in the process are families declining Part C services?
Second On-Site VisitIn
quiry
3. Identify Relevant Data
4. Conduct Data Analysis to Generate Hypotheses
5. Test Hypotheses to Determine Actionable Causes
What’s Accomplished?
Summarize discussion from previous visit
Review data collected in-between visits
Formulate hypotheses• H
ypothesis is a proposition or supposition tentatively accepted to explain certain facts or to provide a basis for further investigation.
Identify strategies to test hypotheses
Data Collection (8/1/10 – 11/30/10)
• Average age of referral: 16 months• 10 referrals received from
physicians:– Average age of referral: 14 months
• Dr. Swingset: 0 referrals received < 18 months
• Dr. Sandbox: 0 referrals received < than 24 months
• Dr. Bottle: average age of referral is 9 months; 50% of declined a screening
• No referrals from the NICU at the ABC hospital
Data Collection (8/1/10 – 11/30/10)
• 12 referrals received from family’s:– 7 Families declined services:
• 57% of families felt their child was developing at age level
• 43% of families wanted to receive services through a private agency
• 5 families declined a developmental screening
• 2 families declined Assessment for Service Planning
ITC Playground City Hypotheses
Physicians are not referring children at very young ages
Physicians are not providing families with a complete explanation of early intervention and reason for referral
Hospitals are not referring premature babies
Final On-Site VisitA
ctio
n
6. Develop and Implement Improvement Plan
7. Evaluate Progress
Inqu
iry
3. Identify Relevant Data
4. Conduct Data Analysis to Generate Hypotheses
5. Test Hypotheses to Determine Actionable Causes
Final On-Site VisitMoving from inquiry to action
Review Hypotheses• Were we correct?• Do we need to re-look at data to formulate new or additional hypotheses?
Improvement Planning and Evaluating Progress• Consider priorities• Sphere of Influence• Use data to determine if moving in right direction
ITC Playground City Improvement Plan
Plan to address increase in referrals of premature babies from NICU: Identify Discharge Social Workers, Nurses or
Therapists responsible for referralsMeet with individualsGather data from hospital (# of premature births
residing in their community, where are referrals being made)
Provide information about EI in VirginiaCollaboratively develop mechanism to meet with
family prior to NICU discharge
What’s Next?•Develop mechanism to introduce to local systems
Complete data analysis modules
•Analysis work completed with systems to-date
Fine-tune process work with local
systems
•Competing prioritiesDevelop mechanisms
on how to keep people engaged in
this process
Things to RememberStates can assist local
agencies/programs to remember: It is all about improved quality of services for
children and families Hard to let go of traditional improvement
planning Hard to let go of your own sense of what the
problem/solution is Follow the data where it leads you Ask the difficult questions Create an environment where solutions are
generated
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