Feed-back on Belgium Experiments

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