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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

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