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Barbara M. Fraumeni Muskie School of Public Service, University of Southern Maine & the National Bureau of Economic Research, USA IARIW, Session 3 Joensuu, Finland August 22, 2006 A Framework for Quality Adjustment Across UK Public Services By Jim Ebdon and Ogho Okiti, ONS, UK
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Muskie School of Public Service Ph.D. Program in Public Policy GOALS Establish a consistent framework across all UK public services Differentiate and cover representative service sub-types Quality adjust via degree of success & contribution to outcomes
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Muskie School of Public Service Ph.D. Program in Public Policy Differentiation of Services As detailed and homogeneous as possible Avoids confounding of structural and quality changes Even when costs are predominantly staff costs, assuming cost and quality correspondences may be problematic Switch from marginal cost to value weights
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Muskie School of Public Service Ph.D. Program in Public Policy Degree of Success Atkinson: ‘a quality improvement is equivalent to getting a larger package.” Need to measure output quality changes, not just process quality changes Avoid double-counting Example of timeliness and accuracy for social security benefits processing
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Muskie School of Public Service Ph.D. Program in Public Policy Contribution to Outcome Eurostat handbook backs use of outcome indicators to adjust for quality Attribution and time lag: an education example
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Muskie School of Public Service Ph.D. Program in Public Policy Case Study: Adult Social Care Differentiation of Services 23 categories of services, where data exists, by Type of service Client group Type of home
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Muskie School of Public Service Ph.D. Program in Public Policy Outcome Adjustments Care weeks, intensity of care, and quality of care Methodology from the Personal Social Services Research Unit (PSSRU) of the University of Kent Concentrated on current welfare gains 9 dimensions of outcome, such as personal cleanliness & comfort and control over daily life (see para. 4.6)
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Muskie School of Public Service Ph.D. Program in Public Policy Capacity for Benefit (CfB) Assessments by service clients Level of benefit if the intervention per week was perfect Needs were categorized as high, low, or no needs Could not separate CfB into two types of home care, but could measure CfB by intensity of care Average CfB per week for home care was about 2 (of a max of 7) CfB among admissions to care homes by type grew between 13% and 18% from 1995 to 2004
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Muskie School of Public Service Ph.D. Program in Public Policy Capacity for Benefit PSSRU Background Paper Understanding Tables 4.3 and 4.4 (after para. 4.15) Aggregate CfB’s of subcomponents by Equal weights for the 9 dimensions of outcomes Or by weights for the Older Persons Utility Scale (OPUS) which covered 5 dimensions of outcomes; with equal and low weights for two of the remaining domains
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Muskie School of Public Service Ph.D. Program in Public Policy Output Index = Capacity for Benefit X Quality Adjustment X Weeks of Help
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Muskie School of Public Service Ph.D. Program in Public Policy Adjusting for Degree of Success and Client Experience – Quality Satisfaction surveys focusing on dimensions such as attitudes of care-workers Separate data for client experience and elements of care delivered are not available currently Degree of success and client experience are both on the future work agenda
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Muskie School of Public Service Ph.D. Program in Public Policy Comments Consistent framework, differentiation of services with representation, and quality adjustment goals are commendable Evaluation by service clients can be tricky Authors well aware of outcome pitfalls How about consumer surplus pitfalls? Use of the word “welfare” makes me nervous Keep up the good work
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