THE UNIVERSITY OF
WESTERN AUSTRALIA
Setting the Scene: What are provider payment reforms?
Professor Stephen DuckettAdjunct Professor
ACERH/University of Queensland
Presentation to Regional Health Financing Seminar:Strategic Choices for Better Outcomes
February 4 – 5, 2008Bangkok, Thailand
Key issues in provider payment reform:
What problem trying to solve? How is risk to be distributed? What instruments/policy levers do
you have available?
What problem are you trying to solve?
Health systems have multiple objectives• Access
Distribution of access also important (i.e. equity)
• Quality • Efficiency
Vs Constrain total expenditure
• Maximise patient assessed value Reform to provider payment may attempt to
• Optimise all• Maximise/minimise one, satisfice on others
How is risk (cost broadly defined) to be distributed?
Cost here includes:• Money costs to consumers
including travel costs Out of pocket costs
• Non-monetary costs to consumers including Quality costs Travel time
• Profit/surplus of providers• Total program costs
Service provision offset by consumer copayments
Risk will fall differently on those with different roles in health system
Oversight Funder
• Treasury• Patient in fully privatised system • What is in scope (medical, dental)• Nature of mutualisation pool
Purchaser• May not exist• Meso-level organisation • What is in scope (more refined), under what conditions
Provider Owner
How is risk (cost broadly defined) to be distributed?
Can fall on any or all of:• Funder/Taxpayer/Contributor• Purchaser• Provider• Consumer
Design should reflect• Goals (see previous slide)• Who is best placed to manage the risk• Inevitability of gaming
What policy instruments/levers do you have available (NB: different equity effects) Culture Price Regulation
• Preferably in alignment
• Different instruments can be used for different purposes
Demand Supply
What price-based instruments/policy levers do you have available to distribute risk?
Demand side: Patient contributions
Supply side:• Payment methods
How describe product
• Payment amount
What regulatory instruments/policy levers do you have available to distribute risk?
Constraints on consumer choices (aka demand)• What providers for what services • Gate keeping (absolute, higher co-payment)
Constraints on provider choices (aka supply)• What treatments• What co-payments can be charged (autonomy)• Prioritisation of patients• Services in scope• Protocols etc, • Second opinions
What policy instruments/levers do you have available (NB: different equity effects)
Supply Demand
Price Fee Schedule Co payments
Regulation Licensing rules Gate keeping rules
Instrument – Objective matrix Casemix funding (supply side) example
Efficiency Access Mitigate risks
(gaming, quality)
Price Benchmark payment per separation
Activity cap at full priceBonus/Penalty scheme for elective surgery and emergency access failure
Coding auditAccreditation mandatory
Regulation Coding rules Patient Satisfaction SurveyReporting of quality indicators
Services have to be funded - 1
Less (economically) rational• History, politics aka “need”
Inputs• Salaries + other inputs
Outputs, volume• Casemix, Fee for service• Incentive payments including ‘adjunct
incentives’ Population, Capitation
• Area vs consumer choice Mix for different levels of system
Services have to be funded - 2
Hierarchies• Can use market-like instruments
Increasing tendency to do so
Markets• Demand driven or not
“Soft vs hard caps” vs no cap (within budget cycle)
Incentives on providers– Tapering– ‘Volume performance standards’/ Agreements
‘Professional payment model’ vs ‘business model’ including tenders
Williamson’s Transaction Cost Economics suggests market superiority affected by:
Frequency of transactions Asset specificity Uncertainty (? reduced by
hierarchy) Product description
Ouchi Culture Analysis
Ability to describe product
Knowledge of transformation process
Perfect Imperfect
High
Low
Markets/hierarchies
Hierarchies
Markets
Clan
Services have to be funded - 3 All systems require risk adjustment (or
fee schedule) of some kind• Fee schedules have tended to over compensate
procedural work and correspondingly under compensate cognitive work
Risk adjustment for hospitals is called case mix• Requires ‘grouper’, updating
Risk adjustment for population • Requires population weights etc
Each liable to gaming Requires technically skilled
policy/purchasers
Services have to be funded - 4
Each funding option has strengths and weaknesses• Including moral hazard of providers
Salary Fee-for-service
• Including moral hazard of consumers Most research/experience suggest
mix of methods is required to balance relative strengths and weaknesses
Who is best placed to manage which risk
Risk Assessment and Skill Assignment
Casemixfunding HospitalFunder
Populationfunding HospitalFunder Purchaser
+ Residual (perverse incentive risk)
Populationexpenditure
=
Size of(weighted,
needs adjusted)
population
x Utilisationrate
x Casemix xCost/service
(eg days, tests)
xServices/
separation
Casemix issues Prerequisites Distribution of efficiency risks
• Purchaser vs provider
Gaming moral hazard Casemix policy doesn’t determine
efficiency P4P along side casemix
CASEMIX FUNDING: The prerequisites
Identification of products
Identification of output measuresfor each product
Pay the price for each unit of output measure
$
Same day
Low Boundary
Costs
Payments and costs by length of stay
Length of stay
High Boundary
Payments
Provider at risk of loss
Purchaser risk of over payment
Length of stay
Risk
Theoretical funding risk as a function of length of stay
Payment amount
Provider at risk of loss
Purchaser risk of over payment
Length of stay
Risk
Theoretical funding risk as a function of length of stay
Payment amount
This is all an inexact science because provider costs not necessarily clear (to either providers or purchaser!) so the curves are in fact quite broad zones
Assignment of risks in casemix funding
Type of risk
Assigned to
Caveat Mitigation strategy
Number and costs per unit of service
Hospital Quality I ndicators Patient surveys
Number of patients
Funder Type of patients (adverse selection)
Activity tapering/ cap
Type of patients
Funder Gaming (upcoding)
Waiting lists and by-pass
Allocative efficiency
Coding audit Bonuses ????
Same day separations as proportion of all separations from public hospitals
0
10
20
30
40
50
60
NSW
Vic
INDICATOR POSSIBLE INCENTIVE DESIGN
Clinical indicators e.g. % adherence
to specific treatment for specific
disease Adherence to (any) endorsed care path
Achievement of hospital accreditationComplications of care
Appropriateness of care: Propensity
to admit conditions which exhibit high
geographic variation.
Incremental payment where
evidence of specific
intervention Increment for adherence to
care path Bonus for accreditation Remove from DRG calculation Discounted payment for
admission of high variability
conditions
DOMAIN INDICATOR POSSIBLE INCENTIVE DESIGN
ACCESS Elective surgery waiting times
Hospital emergency service times to treatment (by triage category)
Long stays in hospital emergency service
Discount/penalties for high percent or number of patients waiting in excess of threshold time Penalties for failure to achieve threshold t treatment time goals
Penalties for number of patients staying in excess of threshold times
PREVENTION Avoidable hospital admissions Avoidable mortality
Discounted payment for avoidable admissions Penalty in area funding formula for excess avoidable mortality
CODING QUALITY AND TIMELINESS
Timeliness
Incidence of “error” DRGs
Coding error as measured by audit
Zero payment for submission outside specific timeframes Discounted payment for ‘error’ DRG codes.
Penalty for upcoding (eg. double deduction where overcoding found).
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