payment innovations in healthcare and how they affect ... · estimated spending on computed...
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1 Dr. Christian Wernz
Payment innovations in healthcare – and how they affect hospitals and physicians
Christian Wernz, Ph.D. Assistant Professor
Dept. Industrial and Systems Engineering Virginia Tech
Abridged version of the presentation given at: Work-In-Progress Session
Office for Clinical Practice Innovation, George Washington University December 19, 2014
2 Dr. Christian Wernz
The U.S. healthcare system is expensive
Poland
Portugal
Czech Republic South Korea
Spain
France
UK Iceland
Finland
Germany Canada
Denmark Austria
Australia
United States
R2=0.72
Per capita health care spending, 2011
29%
71%
Data Source: OECD Health Statistics (2013) Per capita GDP, 2011
USD at purchasing power parity (PPP)
3 Dr. Christian Wernz
Despite high expenditures, overall quality is low
Source: The Commonwealth Fund (2014), SelectUSA.commerce.gov (2014)
Ranking 11 10 9 8 7 6 5 4 3 2 1
Overall quality
Technology availability
Quality care
Access
Efficiency
Equity
Healthy lives
US CAN FRA NZ NOR GER NETH AUS SWE SWIZ UK
4 Dr. Christian Wernz
U.S. is No.1 in technology availability
Source: The Commonwealth Fund (2014), SelectUSA.commerce.gov (2014)
Ranking 11 10 9 8 7 6 5 4 3 2 1
Overall quality
Technology availability
Quality care
Access
Efficiency
Equity
Healthy lives
US CAN FRA NZ NOR GER NETH AUS SWE SWIZ UK
5 Dr. Christian Wernz
Treatment of U.S. patients is technology intensive and expensive
Source: OECD iLibrary (2014), the Commonwealth Fund (2013)
Reimbursement price per procedure
Quantity x Price
CT scans
per 1000
population
$566 $183 $125 $124
256.8
17
2.1
12
9.3
12
9.3
Estimated spending on computed tomography (CT) procedures, 2012
United States
France
Canada South Korea
6 Dr. Christian Wernz
Hospitals rank imaging as top spending priority
17%
12%
10%
7%
10%
9%
9%
8%
15%
18%
15%
14%
11%
11%
11%
10%
Imaging
Emergencydepartment
Surgery
Ambulatory care
Cancer center
Interventional suite
Laboratory
Cardiology
Currently under construction Planned in the next three years
Source: HFM/ASHE construction survey (2011)
Year 2011
7 Dr. Christian Wernz
U.S. healthcare spending breakdown, 2010
Hospitals are major cost producers
Hospitals 25%
Direct administrative costs 13%
Retail products/services 4%
Prescription drugs 8%
Long-term care 7%
Source: Deloitte (2012)
Physician and clinical services 16%
Supervisory care 15%
Other services 8%
Dental services 3%
8 Dr. Christian Wernz
Expensive, low quality
Technology intensive
Hospital based
+
Opportunity: Reduce cost and increase quality for technology usage and investments in hospitals
+
Quantity x Price
$566 $183 $125 $124
256.8
17
2.1
12
9.3
12
9.3
United States
France
CanadaSouth Korea
U.S. health care spending breakdown, 2010
Poland
Portugal
Czech RepublicSouth Korea
Spain
France
UKIceland
Finland
Germany Canada
DenmarkAustria
Australia
United States
R2=0.7229%
71%
USD at purchasing power parity (PPP)
9 Dr. Christian Wernz
How?
10 Dr. Christian Wernz
President's Council of Advisors on Science and Technology (PCAST), May 2014: “The predominant fee-for-service payment system is the primary barrier to great use of systems methods and tools in health care, as it serves as a major disincentive to more efficient care…”
“Positively shaped health care incentives increases both efficiency and quality of care.”
The Center for Medicare & Medicaid Services (CMS) is working on payment innovations and is piloting a variety of reimbursement methods that pay for quality, and not quantity.
11 Dr. Christian Wernz
U.S. healthcare is complex, and a better understanding of the system is needed
Environment
Organization
Care Team
Patient
Regulation, policy, market
Infrastructure, resource
Frontline care providers
Regulators Insurance
Companies Medicare, Medicaid
Research Funders
Health Care Purchaser
Hospitals
Outpatient Clinics
Nursing homes
Rehabilitation Centers
Physicians
Nurses
Family Members
Patients
12 Dr. Christian Wernz
I will present two research projects
Patient
Physician
Medicare
D
D D
O
O
O
O
O
D
O
O
O
D
O
D
D
① ② ③
④ ⑤
⑥ ⑦
D
D,O
O
D
Hospital
1. Designing multi-level incentives for healthcare systems
2. Helping hospitals make better technology investment decisions.
13 Dr. Christian Wernz
How to get from reality to math?
1
2
*2
* 1 * 2 *
2 1 20 1
( | ) ( ) ( ) ...R H R R
hMax a C C
3
Hospital
Physicians
CT scan
Buy newCT scanner
CT availability
Status quo
Costs
High
Low
High
Low
Medicare billings Patient health
High High
Low Low
Incentive from CMS
O
D
O
D
Decisions Outcomes
Alternative
Stakeholders
Incentive
Uncertainty
14 Dr. Christian Wernz
1. The agent interdependence diagram captures decisions, outcomes, interactions
15 Dr. Christian Wernz
2. The detailed graphical representation allows for micro-modeling
Hospital
Physicians
CT scan
Buy newCT scanner
CT availability
Status quo
Costs
High
Low
High
Low
Medicare billings Patient health
High High
Low Low
Incentive from CMS
O
D
O
D
Decisions Outcomes
Alternative
Stakeholders
Incentive
Uncertainty
16 Dr. Christian Wernz
3. The mathematic formulation is based on Multiscale Decision Theory (MSDT)
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.40
0.05
0.1
0.15
0.2
0.25
0.3
change coefficient c
sh
are
co
effic
ien
t b
Area 1
Area 2a
Area 4
Area 2b
Area 3
Area 5b
Area 5a
SUP
INF
1
SUPa
2
SUPa
| ,SUP SUP INF SUP
final i j mp s s a
1
INFa
2
INFa
|INF INF INF
j np s a
1
SUPs
2
SUPs
1
INFs
2
INFs
Influence
on transition
probability
Influence
on reward
| , , | | ,INF SUP INF INF INF SUP INF INF INF SUP SUP INF SUP
final m n final j i j n final i j m
i j
E r a a r s s p s a p s s a
| , | | ,SUP SUP INF SUP SUP INF INF INF SUP SUP INF SUP
final m n final i j n final i j m
i j
E r a a r s p s a p s s a
| , | | ,SUP SUP INF SUP SUP SUP SUP SUP INF SUP
final i j m i m i j mp s s a p s a f s s a
,INF INF SUP INF INF SUP SUP
final j i j ir s s r s b r s SUP SUP SUP SUP
final i ir s r s
17 Dr. Christian Wernz
Different inventive programs exist
High
Low
Paye
r Sa
vin
gs
High Low Provider Financial Risk
Fee for Service (FFS)
Pay for Performance (P4P)
Medical home
Shared savings
Bundle payment
18 Dr. Christian Wernz
We modeled the Medicare Shared Saving Program (MSSP)
Hospital and physicians form an Accountable Care Organization (ACO) to coordinate care of Medicare patients
Standard Reimbursement (as before): Physicians/radiologists: Fee for service Hospital: Diagnosis-related groups for inpatients Outpatient prospective payment system
MSSP Incentive: ACO receives 50%-60% of cost savings when achieving quality goals
MSSP
19 Dr. Christian Wernz
Physicians
CT scan
Alternative
Medicare billings Patient health
High
Low
High
Low
Stakeholders Decisions Uncertainty Outcomes
Agent P 0 1Pa PrP sb,c
P | a p
P( ) = ab,c;p
P S P = s1,1
P ,… sb,c
P ,… ,sB,C
P{ }
Physicians’ decision and outcomes related to CT scans
20 Dr. Christian Wernz
Hospital
Buy advancedCT scanner
Status quo
Maintenancecosts
Operatingcosts
High
Low
High
Low
Physicians
CT scan
Alternative
Medicare billings Patient health
High
Low
High
Low
Bundled incentive from CMS
Incentivepassed onto physicians
Stakeholders Decisions Uncertainty Outcomes
Hospitalreputation
High
Low
Hospital and physicians affect each other
Incentive for H Investment decision
Operating &
Maintenance cost
Hospital
reputation payoff
Incentive for P Interdependencies
21 Dr. Christian Wernz
Converting the graph into math
Hospital
| , , ,H H H P CMS H H P H P H P
final total h h hE r E r a a g a a g a a
Payoff before incentive for H:
Final payoff for H:
Reward Probability
Payoff before incentive Bundled incentive Distributed incentive
22 Dr. Christian Wernz
Converting the graph into math
Physician
Payoff before incentive for P:
Final payoff for P:
| , ,P P H P H P H P
final total h hE r E r a a g a a
Payoff before incentive Distributed incentive
Reward Probability
23 Dr. Christian Wernz
Incentives from CMS to ACO
Bundled incentive from CMS to Hospital:
Distributed incentive from Hospital to Physician:
Benchmark set by CMS
, ,H P H P CMS H H P
h hg a a m g a a
Sharing percentage set by Hospital
E gCMS®H a
h
H ,aP( )éë
ùû
= 50% × M - E(rcost
H | ah
H ,aP ) - E(rcost
P | ah
H ,aP )éë
ùû
24 Dr. Christian Wernz
Decision problem is a sequential game
25 Dr. Christian Wernz
Results: Incentives can prevent new equipment purchase and lower CT scan rate
M=35 m=0.5
CT scan rate
a 50-50 split of CMS incentives between H and P
26 Dr. Christian Wernz
Physicians’ optimal CT scan rate depends on incentive and equipment
0.2 0.4 0.6 0.8 1.0Test rate
10
15
20
25
P's payoff
With incentive, investment No incentive, investment
No incentive, status quo
With incentive, status quo
Scan rate
P’s reward
Physician payoff
CT scan rate
27 Dr. Christian Wernz
How should hospitals and physicians split the incentive?
26 28 30 32 34Benchmark M
0.0
0.2
0.4
0.6
0.8
1.0
Optimal sharing percentage mOptimal sharing percentage m*
Benchmark M
all goes to Physician
Hospital keeps all
28 Dr. Christian Wernz
In summary…
Physicians
- Incentives motivate physicians to reduce CT scan rate.
Hospitals
- Incentives can reduce hospital’s propensity to invest in
additional equipment.
- Given challenging cost benchmarks, hospital passes on all
incentives to physicians, which results in largest CT scan
reduction.
29 Dr. Christian Wernz
ACOs
- The incentive distribution mechanism can be designed to
maximize the payoffs of their members.
Policy maker / CMS
- The cost benchmark has to be set just right to induce
desired behavior, or otherwise the incentive is not effective.
In summary…
30 Dr. Christian Wernz
Next steps: YOU can help
1. Revise model and remove assumptions to get closer to clinical practice / reality
2. Calibrate and validate model through data
31 Dr. Christian Wernz
Project 2: Helping hospitals make better technology investment decision
Board of Directors
Departments
Physicians
Patient
Physician
Medicare
D
D D
O
O
O
O
O
D
O
O
O
D
O
D
D
① ② ③
④ ⑤
⑥ ⑦
D
D,O
O
D
Hospital
32 Dr. Christian Wernz
Large number of capital requests compete for small budgets
<
33 Dr. Christian Wernz
Current investment decision-making is informal and unstructured
Ad-hoc, heuristic, political
decisions
Too many variables to
consider
Pressure from physicians,
patients and donors
Limited information,
high uncertainty
Multiple objectives,
some hard to quantify
34 Dr. Christian Wernz
Decision analysis can make this process more transparent and systematic
• All objectives are taken into account
• Analysis of different trade-offs
• Getting stakeholders involved
Objective and balanced decision
making
35 Dr. Christian Wernz
Project objectives:
• Provide hospital executives with a structured decision-making framework
• Apply SMART (Simple Multi-Attribute Rating Technique) in a hospital setting using real investment alternatives
• Prepare for SMART session through student mock panels
36 Dr. Christian Wernz
We identified investment objectives reviewing literature and best practices
Objectives Attributes
Financials Net present value
Quality Quality Adjusted Life Years
Strategic importance Growth in market share
Infrastructure Productivity increase
Increase on patient satisfaction
Ease of implementation Low level of disruption, high usability, short learning curve
37 Dr. Christian Wernz
SMART in action: Session with hospital executives
Scoring of alternatives
Assessment of Weighted
Single Dimensional
Values
Selection of investment alternatives
Sensitivity Analysis
Budget: 2.5 million $
Alternatives: 1. CT scanner dose reduction software, $192K 2. New CT scanner, $732K 3. CT scanner lease buyout, $292K 4. New Mammography unit, $468K 5. Mammography refurb, $160K 6. Da Vinci surgical robot, $2,000K
38 Dr. Christian Wernz
1. Investment alternatives were scored across five objectives
Direct Assessment
Linear relationship between NPV values
Value Scale
Financial impact
Clinical impact
Market share
Routine infrastructure
Staff-physician relationships
100
0
90
40
15
Scoring of alternatives
Assessment of Weighted
Single Dimensional
Values
Selection of investment alternatives
Sensitivity Analysis
39 Dr. Christian Wernz
2. We derived weights for each objective
Financial impact
Clinical impact
Market share
Routine infrastructure
Staff-physician relationships
10
10
10
10
10
Points
20
20
20
20
20
Weights (%)
Scoring of alternatives
Assessment of Weighted
Single Dimensional
Values
Selection of investment alternatives
Sensitivity Analysis
40 Dr. Christian Wernz
3. We calculated weighted values for each alternative on each objective
Scoring of alternatives
Assessment of Weighted
Single Dimensional
Values
Selection of investment alternatives
Sensitivity Analysis
41 Dr. Christian Wernz
4. The alternatives were ranked based on Value/$
Scoring of alternatives
Assessment of Weighted
Single Dimensional
Values
Selection of investment alternatives
Sensitivity Analysis
42 Dr. Christian Wernz
5. Hospital executives chose a portfolio of alternatives that meets the budget
Scoring of alternatives
Assessment of Weighted
Single Dimensional
Values
Selection of investment alternatives
Sensitivity Analysis
43 Dr. Christian Wernz
6. We performed a sensitivity analysis around the objectives’ weights
Scoring of alternatives
Assessment of Weighted
Single Dimensional
Values
Selection of investment alternatives
Sensitivity Analysis
44 Dr. Christian Wernz
Participants confirmed feasibility and value of SMART for hospital’s decision process
Survey scores
Intuitive Can be incorporated into hospital’s decision-
making practice
“…this is the best thing I’ve done all week”
“I need more and better information on proposed investment alternatives”
Feedback from executives
45 Dr. Christian Wernz
In summary…
• We implemented SMART in a hospital using actual investment alternatives
– Hospital executives found the method intuitive
– They believe it can be incorporated into their organization’s practice
• Participants realized information availability and accuracy are critical
46 Dr. Christian Wernz
Thank you!
www.wernz.com