data efficiency in effective communication 6 th annual summit vocational rehabilitation program...
TRANSCRIPT
Data efficiency in effective communication
6th Annual Summit Vocational Rehabilitation Program Evaluation and
Quality AssuranceProvidence RI
September 16-17, 2013
Presented by:
• Susan Stoddard, Ph.D., President, InfoUse; RTAC • Scott Sabella, Ph.D., Director, Region 8 TACE • Michael Quinn, Program Evaluation Coordinator,
Alabama Department of Rehabilitation Services• Elizabeth Moody, Strategic Planning Coordinator,
Florida Division of Vocational Rehabilitation
The expanding data challenge
• Expansion of data availability• Better internal data systems• New data analysis and display tools• Advances in data technology• Significant investment in data and systems• How to use data effectively and efficiently?• How to communicate progress and results?
Needed: best data to support…
• Reporting• Evaluating• Planning • Deciding• Auditing• And of course assuring service quality,
outcomes, and continuous improvement• In all of this we rely on our data.
Danger – Information/need mismatch
• Lots of information: 911 and agency MIS; financial transactions ; vendor data; census/ACS and other population information.
• Many internal and external information needs: reporting to RSA and other funding sources; general reporting to the public; internal monitoring and performance assessment, etc.
• Costly, inefficient• How to link these data to agency information needs to
support communication and continuous improvement?
Major data source options (existing)
• Agency data (RSA-911, RSA-2, MIS, case management)
• Public data (census, ACS, disability population, state labor market data, IDEA data)
• Fiscal reports• Case file reviews• Consumer satisfaction surveys• Monitoring reports• State audits
Data Source Options (new)
• Needs assessments (training, client, CRP, stakeholders)
• Surveys (clients, counselors, PWD)• Focus groups• Community hearings• Key informant interviews• Targeted evaluations• Targeted case file reviews
Examples
• Examples of linking the data to agency information needs to support communication and continuous improvement– Alabama– Florida– Utah– CSNAs: Michigan, Iowa, Ohio– Working with SRC
Alabama VRS
Examples of effective data communication using maps
Alabama VRS annual report
Alabama tailored briefing for legislative district
Examples of effective data communication
Florida VR
• External communication method
• Personalized
• VR performance and state population data
• Return on Investment (ROI)
Legislative Profiles
• Available via Sharepoint
• Interactive graphics
• Magic Kingdom themed training
Florida VR Performance Report
• Survey administered every 2 years
• Employee input drives decision-making
• Linkage is evident
Employee Climate Survey + Strategic Plan
Utah State Office of Rehabilitation (USOR)
• Economic Impact Study• Written Benefits Analysis Study
USOR Economic Impact Study
• Relatively simple formula (increase in tax revenue + decrease in public assistance + decrease in Medicaid payments)/state dollars invested
• Multiple uses– Information to agency leadership and staff on impact– State legislature advocacy– State report cards to U.S. Senators and Congressman– National advocacy
USOR Written Benefits Analysis Study
• Are Benefits Planning Assistance and Outreach services associated with improved earnings and employment outcomes• Yes, those who received benefits planning services had
higher wages than the control group• Yes, those who received benefits planning services was
more likely to have a successful closure and more likely to be employed in the quarter after closure
• Utilization• Advocacy for the program• Decision making • Used to support funding benefits planner positions
CSNA examples
• CSNA– Look beyond the “every three year” study…– To what extent is the CSNA integrated into the
continuous feedback and MIS systems? – Ways to make the CSNA investment serve agency
planning and communication needs– What new opportunities need to be created?– CSNA information and formatting… some
possibilities
Michigan CSNA: Outcomes and Attrition
Michigan: Employment rates
Iowa: Outcome rate by impairment, 2007-2010
Iowa: Unique population story
Iowa: Lowest growth rate in US, 1900-2009
5th in % population 65 and over, 2008
Iowa Caseload comparisons
Ohio decreasing referrals, applicants eligibility
Ohio funding context for declines
Ohio: County needs/service gapsTransition
Working with your SRC
• Providing input on outreach to PWD• Providing input on needs for PWD• Indentifying key informants• Developing surveys and communication
strategies• Reviewing and analyzing information• Prioritizing needs• Making recommendations for strategic plan• Making recommendations for the state plan
Parkinson’s Law of Triviality(Bike Shedding)
• “The time spent on any item on an agenda will be in inverse proportion to the sum involved”
• Committee deliberations regarding building an atomic reactor
• Committee deliberations regarding building a bike shed.
Bike Shedding and SRC Example
• Promise grant initiatives ($1,000,000)• Attrition rate ($100,000)• Transportation project ($100,000)• What to serve for lunch at a working lunch
meeting ($600)
• What is the point?
Example: Framing Information for Your SRC?
• Intent: Are you trying to get their input or get items through?
• How much invested in helping them understand complicated issue
• Preservation of language for certain information
• Examples related to daily life
The Important VR Cycles
• State fiscal year• Federal fiscal year• State legislative cycle• CSNA 3 year cycle• State plan submission• Federal reporting (RSA-911, RSA-2)• Federal monitoring
Windows of OpportunityDiscussion
• What are the windows of opportunity for these various cycles?– Preparing for legislative sessions– Federal reporting (program, fiscal)– CSNA– State plan– Federal monitoring
Conclusion: 8 principles to remember
• Know your available data source options and how to use them
• Make use of existing data• Use information for multiple purposes• Data quality: avoid GIGO• Make sure there is a link in process from data to
decision making• Make sure the data gets to the people who can use it,
communicated in a form they understand• Share, borrow and adapt good ideas• Support a continuous improvement system
