1. Feed-back on Belgium Experiments
Brant E. Fries, Ph.D.
University of Michigan, USA
Brussels, Belgium
February 19, 2008

2. New Technology of Assessment
Link assessment directly with clinical care
Turn data into information
Multiple uses of data
Careful design and scientific testing
Cross-sector compatibility
Cross nation comparisons

3. It’s not enough just to measure…..

4. Link assessment directly with clinical care
Primary goal: care of the individual
Use Clinical Assessment Protocols (CAPs)
triggers to target opportunities for better care
content to design interventions
New triggers better identify individuals who can benefit
NOT automated care planning!

5. Turn Data into Information
Assessment data can be used for multiple purposes:
Clinical care
Case-mix measurement and payment
Quality measurement and program evaluation
Eligibility determination or program recommendation
Program monitoring and policy research

6. Multiple Uses of Data Efficient, as only collected once
Focuses attention on proper assessment
Offsetting incentives encourage accuracy

7. Careful Design and Scientific Testing
Design by clinical experts
Cross-fertilization from other long-term care sectors
Extensive testing:
Reliability
Validity
International testing and experience
Development of multiple applications
Careful translation to other languages
Cross-sector integration

8. Cross-Sector Compatibility
Goal of new interRAI “Suite”
Assessment items consistent across instruments
Common structure for all databases
Allows comparisons between sectors
Effective items used across sectors

9. Comparing Persons Served in Two Michigan Settings

10. Cross-National Comparisons
Practical experience from use in multiple nations
Cross-national comparisons provide more accurate standards
Only possible with standardized assessment

11. Lessons Learned Staff training Plan for staff turnover
Develop cadre of “trained trainers”
Invest in computer-directed learning technology
Establish web-based clinical “help desk”
Create “Frequently Asked Questions” (FAQ) list; post and update frequently
Set training requirements in regulation or contracts

12. Lessons Learned - 2 Develop “business intelligence” plan
Analyze desired uses of data
How will stakeholders get timely information?
Design reports for key audiences:
Administrators
Clinicians
Policymakers
Consumers?
Fund adequate, multi-year budget
Future data analysis: make or buy?
All or above: at both government and provider level

13. Lessons Learned - 3 Insure timely data outputs
Include both clinicians and administrators in software design/ purchasing decisions
Negotiate performance contracts with software vendors
Set aside funds to create additional reports as need arises

14. Lessons Learned - 4 Don’t let the assessments become “paperwork”
Field needs strong, persistent message about importance of data quality from top leadership.
Use the data in many ways:
“Continuous Quality Improvement” (CQI) efforts
Encourage users to identify effective “best practices”
Invest in audit process to ensure assessment and data accuracy over time