health economics: hot topics and research in progress richard e. nelson, phd division of...

Health Economics: Hot Topics and Research in Progress

Richard E. Nelson, PhDDivision of Epidemiology

University of Utah School of MedicineSalt Lake City Veterans Affairs Healthcare System

Presentation Outline

• Brief overview of healthcare costs in the US• Affordable Care Act

– Oregon Health Insurance Experiment• Cost of healthcare-acquired infections

– Methods – Application of these methods to VA data

Economics

• “Economics examines economic events and arrangements through the lens of economic theory”

• The study of how individuals, governments, firms, and nations allocate scarce resources to satisfy their unlimited wants

• The study of choices

Health Economic Evaluation

• Bang for the buck– Inputs (costs)– Outcomes (benefits)

• Cost-effectiveness– Achieving objective at least cost, or– Maximizing benefits from given amount of

resources

Total Healthcare Expenditures per Capita

$0

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

$8,000

$2,729 $2,870 $2,902$3,129

$3,353 $3,470$3,677 $3,696 $3,737

$3,970 $4,063 $4,079

$4,627$5,003

$7,538

OECD. 2010

Total Health Expenditures as a Share of GDP, 2008

OECD. 2010

0%

200%

400%

600%

800%

1000%

1200%

1400%

1600%

1800%

810.0%850.0%850.0%870.0%900.0%

910.0%940.0%990.0%

1040.0%1050.0%1050.0%1070.0%1110.0%1120.0%

1600.0%

Commonwealth Fund 2013

Why Cross-Country Differences in Healthcare Expenditures

• Administrative costs– US = 25% of healthcare expenditures– Other countries = 10-15% of healthcare

expenditures– Duke University

• 900 beds• 1,300 billing clerks

– Typical Canadian hospital• 10 billing clerks

David Cutler, Harvard University

Why Cross-Country Healthcare Expenditure Differences?

IFHP 2012 Comparative Price Report

Why Cross-Country Healthcare Expenditure Differences?

IFHP 2012 Comparative Price Report

Why Cross-Country Healthcare Expenditure Differences?

IFHP 2012 Comparative Price Report

Why Cross-Country Differences in Healthcare Expenditures

• The same patients get more medical care in the US– Ontario, Canada

• 11 hospitals that can do open heart surgery

– Pennsylvania• 60 hospitals that can do open heart surgery

– Life expectancy and one-year mortality following heart attack roughly the same

David Cutler, Harvard University

What do we get for our healthcare dollars?

What do we get for our healthcare dollars?

Geographic variation in health care spending

Institute of Medicine 2013

Lowest and Highest Spending Medicare HRRs

Institute of Medicine 2013

1. Rochester, NY2. Stockton, CA3. Sacramento, CA4. Buffalo, NY5. Bronx, NY6. Santa Cruz, CA7. Santa Rosa, CA8. Medford, OR9. San Francisco, CA10. Salem, OR

1. Miami, FL2. McAllen, TX3. Monroe, LA4. Houston, TX5. Alexandria, LA6. Lafayette, LA7. Shreveport, LA8. Baton Rouge, LA9. Fort Lauderdale, FL10. Metairie, LA

Lowest Highest

Geographic variation in health care spending

Baicker and Chandra (2008) Health Affairs

Geographic variation in healthcare spending

• Potential reasons– Differences in prices paid for similar services– Differences in illness between regions– Differences in volume of health care services

received by similar patients

Geographic variation in healthcare spending

• Why higher volume of care– More effective care?– More preference-sensitive care?– More supply-sensitive care?

Geographic variation in healthcare spending

• Higher volume of care does not produce better outcomes for patients– Worse adherence to evidence-based guidelines1-3

– Worse mortality after heart attack or hip fracture4

– Worse communication among physicians5

– Worse access to care and greater waiting times4

– Worse patient-reported inpatient experience6

1. Fisher et al (2003) Ann Intern Med2. Baicker et al (2004) Health Aff3. Fisher et al (2004) Health Aff4. Fisher et al (2003) Ann Intern Med5. Sivovich et al (2006) Ann Intern

Med6. Wennberg et al (2009) Health Aff

Affordable Care Act

• Signed into law March 23, 2010• Major components

– Individual mandate– Employers must offer insurance coverage– No denying coverage if preexisting condition– Creating health insurance exchanges– Expand Medicaid

Affordable Care Act

• Medicaid expansion– Prior to ACA

• Pregnant women and children < 6 with family incomes < 133% of FPL

• Children age 6-18 with family incomes < 100% of FPL• Parents, caretaker relative meeting certain financial

eligibility requirements• Elderly and disabled individuals who qualify for

Supplementary Security Income

Affordable Care Act

• Medicaid expansion– After ACA

• All non-Medicare eligible individuals < 65 up to 133% FPL

– $14,856 for individual in 2012– $30,657 for family of 4 in 2012

• Federal government pays for expansion

– Supreme Court decision 2012• Medicaid expansion violates Congress’ spending clause

power

Affordable Care Act

Oregon Health Insurance Experiment

• Oregon Medicaid – Did not allow new enrollment from 2004-2008

due to budget constraints– Expanded in 2008– Excess demand– So created a lottery

• Treatment group = 29,834• Control group = 45,088

– Sneak peak at possible impacts of ACA

Oregon Health Insurance ExperimentResults

• Increased hospital admissions

Finkelstein, et al Quarterly Journal of Economics (2012)

Oregon Health Insurance ExperimentResults

• Increased Rx, outpatient encounters

Finkelstein, et al Quarterly Journal of Economics (2012)

Oregon Health Insurance ExperimentResults

• Reduced probability of unpaid medical bill sent to collection agency

Finkelstein, et al Quarterly Journal of Economics (2012)

Oregon Health Insurance ExperimentResults

• Increased self-reported health and probability of not screening positive for depression

Finkelstein, et al Quarterly Journal of Economics (2012)

Oregon Health Insurance ExperimentResults

• Increased ED use

Taubman, et al Science (2014)

Oregon Health Insurance Experiment and ACA

• Summary– Improvements in self-reported health– Decreases in financial hardship– Increases in healthcare utilization

HAI and MRSA

• Healthcare-acquired infections (HAI)– Infections that result from encounters with

healthcare system– About 1 in 20 hospitalized patients in US

• Methicillin-resistant Staphylococcus aureus (MRSA)– Bacteria resistant to many antibiotics– One of the leading causes of invasive infections in

healthcare settings• Bloodstream, pneumonia, and surgical site infections

Accurate cost of HAIs

• Nicholas Graves– The purpose of cost-of-illness studies for HAIs is to

inform decisions about how to reduce HAIs• If we know how much they cost, we will know how

much we will save if they are prevented

– 2 measures of cost appropriate for HAIs1. Excess length of stay

1. Opportunity costs associated with lost bed-days

2. Variable inpatient costs1. Variable vs. fixed costs

Accurate cost of HAIs

1. Excess LOS2. Variable (and total) inpatient costs3. Post-discharge costs

Goal of my current research

• Estimate the cost per healthcare-acquired MRSA infection in the VA using these 3 components:

1. Excess LOS2. Variable (and total) inpatient costs3. Post-discharge costs

• And use that estimate to estimate the budget impact of VA MRSA Prevention Initiative

Veterans Affairs MRSA Prevention Initiative

• Began October 2007• Consisted of a “bundle” of prevention

strategies– Universal nasal surveillance for MRSA– Contact precautions for patients colonized or

infected with MRSA– Hand hygiene– Institutional change

• HAI prevention is everyone’s responsibility

Estimating cost of MRSA HAI in VA

• Need way of identifying healthcare costs– VA DSS data

• Activity-based accounting system in VA• Extracts information from general ledger and VA payroll

system• Specific job categories, supplies or equipment• Costs are allocated to cost centers

– Primary care clinics– Intensive care units– Administration– Environmental services

• Costs are allocated based on employee activities

Estimating cost of MRSA HAI in VA

• Need way of identifying MRSA infections– ICD-9 code (V09) is not good for MRSA HAIs

• V09 = infection with drug-resistant microorganisms

– Microbiology data• Unstructured

Schweizer et al ICHE 2011

VA Microbiology Data

Progress to date

1. Excess LOS– In progress

2. Variable (or total) inpatient costs– Preliminary results

3. Post-discharge costs– Preliminary results

1. Impact of HAI on Excess LOS

• Important because each extra bed-day taken up by a patient with HAI represents opportunity cost for hospital

• Many studies compare total LOS between patients with HAI and those without

• But not all of the days are attributable to the HAI• This leads to “time-dependent bias”

Patient 1

Patient 2

HAI

Admission Discharge

DischargeAdmission

Barnett et al AJE (2009)Barnett et al Value in Health (2011)

1. Impact of HAI on Excess LOS• Multi-state models (Beyersmann method)

HAI (1)

Admission (0) Discharge/death(2)

1. Impact of HAI on Excess LOS

• Using VA data to estimate this– In progress

2. Impact of HAI on Inpatient Costs

• Many studies compare total inpatient costs between patients with HAI and those without

• But not all of the costs are attributable to the HAI• This leads to “time-dependent bias”

Patient 1

Patient 2

HAI

Admission Discharge

DischargeAdmission

2. Impact of HAI on Inpatient Costs• Can we identify costs before and after HAI

with VA data?– Separate observations for each patient-treating

specialty-calendar month admitday txspsdt txspedt txsp fy fp TotFD TotFI TotVD TotCost

2009-10-29 2009-10-29 2009-10-31 63 2010 1 $1270.52 $17,767.53 $38,508.67 $57,546.72

2009-10-29 2009-10-31 2009-10-31 52 2010 1 $13.83 $195.31 $282.38 $491.52

2009-10-29 2009-11-01 2009-11-04 52 2010 2 $63.47 $1560.92 $1966.30 $3590.69

2009-10-29 2009-11-04 2009-11-05 63 2010 2 $225.60 $1882.73 $2480.43 $4588.76

2009-10-29 2009-11-05 2009-11-12 52 2010 2 $401.53 $7290.23 $9183.70 $16,875.45

2009-10-29 2009-11-12 2009-11-21 22 2010 2 $1089.92 $12,469.61 $15,273.73 $28,833.26

txsp 63

2009-11-01 2009-12-01

txsp 52 txsp 63 txsp 52 txsp 22

txsp 63 txsp 52 txsp 63 txsp 52 txsp 22

5 treating specialties

6 observations

2. Impact of HAI on Inpatient Costs

• Options to separate pre-HAI costs from post-HAI costs1. Hope that patients with HAI had a new treating

specialty2. Try to get daily costs for all admitted patients3. Exploit the quirk that generates a new

observation each month

Option 2

Admitdt

Day 1 Patient 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Day 9 Day 10 Day 11

Admitdt

Day 1 Patient 2 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 Day 9 Day 10 Day 11 Day 12

Admitdt

Day 1 Patient 3 Day 2 Day 3 Day 4 Day 5 Day 6

• GEE model on patient-day data– Gamma distribution

• DSS Daily Cost Resource (DCR)– Daily inpatient costs

• DSS Production-Level DataHAI

HAI

No HAI

Dischdt

Dischdt

Dischdt

Day 5

Admitdt Dischdt

Patient 1 X

Month 1 costs Month 2 costs

Admitdt Dischdt

Patient 2 X

Month 1 costs Month 2 costs

Admitdt Dischdt

Patient 3 X

Month 1 costs Month 2 costs

Admitdt Dischdt

Patient 4

Month 1

HAI on 1st day of month

HAI in 1st month

Month 1 costs Month 2 costs

HAI in 2nd month

No HAI

Option 3X = HAI

Month 2

Admitdt Dischdt

Patient 1 X

Month 1 costs Month 2 costs

Admitdt Dischdt

Patient 2 X

Month 1 costs Month 2 costs

Admitdt Dischdt

Patient 3 X

Month 1 costs Month 2 costs

Admitdt Dischdt

Patient 4

Month 1

HAI on 1st day of month

HAI in 1st month

Month 1 costs Month 2 costs

HAI in 2nd month

No HAI

X = HAI

Month 2

Admitdt Dischdt

Patient 5

Month 1 costsHAI, 1 month

Admitdt Dischdt

Patient 6

Month 1 costs

No HAI, 1 month

X

Option 3

• Methods– Identify cohort of inpatients at VA hospitals

• Identify those with MRSA HAIs• Identify those MRSA HAIs that occur on 1st day of

calendar month

– Create longitudinal dataset • Observation = patient-month• Treat MRSA HAI as time-varying exposure

2. Impact of HAI on Inpatient Costs

• Patient selection– Inclusion criteria

• Patients admitted to 1 of 114 VA hospitals nationwide– 1st hospitalization

• Between Oct 1, 2007 – Sept 30, 2010• 365 days prior to admission

– Exclusion criteria• Patients with inpatient stays < 48 hours• Patients with MRSA positive culture in 365 days prior to

admission • Patients with MRSA positive surveillance test on index

admission

2. Impact of HAI on Inpatient Costs

Patients meeting inclusion/exclusion criteriaN = 432,874

No MRSA HAIN = 426,421

MRSA HAIN = 6,453

Middle of monthN = 6245

1st day of monthN = 208

Results – Multivariable Cost Regressions

MRSA HAI as time-varying exposure

MRSA HAI as non-time varying exposure

Effect 95% CI Effect 95% CI

Variable inpatient $13,893 $10,823 $16,964 $32,513 $28,251 $36,775

Total inpatient $24,975 $19,530 $30,421 $59,223 $51,697 $66,748

Note: Regression controlled for the following variables: demographic characteristics, comorbid conditions, LOS during index hospitalization, primary ICD-9 code for index hospitalization

• Model = GEE• Dependent variable = inpatient cost• Key independent variable = time-varying MRSA HAI

N = 622,386

3. Impact of MRSA HAI on post-discharge costs

• Patient selection– Inclusion criteria

• Patients admitted to 1 of 114 VA hospitals nationwide– 1st hospitalization

• Between Oct 1, 2007 – Sept 30, 2010• 365 days prior to admission

– Exclusion criteria• Patients with inpatient stays < 48 hours• Patients with MRSA positive culture in 365 days prior to

admission • Patients with MRSA positive surveillance test on index

admission

3. Impact of MRSA HAI on post-discharge costs

• Exposure– MRSA HAI

• MRSA positive clinical culture between 48 hours after admission and 48 hours after discharge

Admission Discharge

48 hours 48 hoursInpatient length of stay

MRSA HAI time window

3. Impact of MRSA HAI on post-discharge costs

• Post-discharge outcomes – Inpatient costs

• Variable costs• Total costs

– Outpatient costs– Pharmacy costs

AdmissionInpatient LOS

Post-discharge outcomes time window

365 days post-discharge

Discharge

3. Impact of MRSA HAI on post-discharge costs

Patients meeting inclusion/exclusion criteriaN = 432,874

No MRSA HAIN = 426,421

MRSA HAIN = 6,453

Results – Multivariable Cost Regressions

Full cohort Propensity score matched subgroup

Effect 95% CI Effect 95% CIOutpatient $466 $86 $845 -$13 -$629 $604Pharmacy $958 $514 $1,403 $1,110 $849 $1,371Total inpatient $10,917 $9,742 $12,092 $15,194 $12,966 $17,422Variable inpatient $5,673 $5,065 $6,282 $7,850 $6,686 $9,013

Note: Regression controlled for the following variables: demographic characteristics, comorbid conditions, LOS during index hospitalization, primary ICD-9 code for index hospitalization

• Model = GLM, gamma distribution, log link• Dependent variable = cost in 365 days post-discharge• Key independent variable = MRSA HAI

N = 432,874

Conclusions

• We pay considerably more for healthcare in the US than other countries do

• Expansion of health insurance coverage under ACA likely to increase utilization of healthcare services

• VA is a great environment to study cost of HAI– Big data

• Cost of MRSA HAIs in VA– $22,853 using variable inpatient costs– $41,279 using total inpatient costs– $59,223 using conventional methods

Thank you

Total Healthcare Expenditures per Capita 1970, 1980, 1990, 2000, 2008

$-

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

$8,000

19701980199020002008

OECD. 2010

Total Healthcare Expenditures per Capita1970, 1980, 1990, 2000, 2008

OECD. 2010

$0

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

$8,000

United States

Switzerland

Canada

OECD Average

Sweden

United Kingdom

Total Health Expenditures as a Share of GDP1970, 1980, 1990, 2000, 2008

OECD. 2010

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

19701980199020002008

Health Expenditures and GDP per Capita 2008

OECD. 2010

$25,000 $35,000 $45,000 $55,000 $65,000$0

$1,000

$2,000

$3,000

$4,000

$5,000

$6,000

$7,000

$8,000

Australia

Austria

BelgiumCanada

France

Germany

Italy

Japan

Netherlands

Norway

SpainSweden

Switzerland

U.K.

USA

GDP Per Capita

Health Economics

• Uncertainty• Asymmetric information• Externalities• Government involvement

Geographic variation in healthcare spending

• Variation in Healthcare Spending– Institute of Medicine report, August 2013– Biggest contributors to variation in Medicare

spending per beneficiary• Post-acute care services

– Home health agencies– Skilled nursing facilities– Rehabilitation facilities– Long-term care hospitals– Hospices

• Inpatient services

Geographic variation in healthcare spending

• Variation in Healthcare Spending– Smallest contributors to variation in Medicare

spending per beneficiary• Outpatient procedures• Outpatient visits• Diagnostic testing

Geographic variation in healthcare spending

• Variation in Healthcare Spending– Recommendations

• Not adjust Medicare payments geographically• Continue to focus on value-based payment reforms

– Patient-centered medical homes– Bundled payments– Accountable care organizations

Mean unadjusted outpatient costs

1 month 3 months 6 months 12 months$0

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

$14,000

$16,000

$1,773

$4,225

$7,111

$12,272

$1,710

$4,366

$7,570

$13,427

No MRSA HAIMRSA HAI

Mean unadjusted total inpatient costs

1 month 3 months 6 months 12 months$0

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

$35,000

$40,000

$2,519

$7,078

$11,705

$18,823

$4,413

$13,737

$22,672

$36,030

No MRSA HAIMRSA HAI

Mean unadjusted variable inpatient costs

1 month 3 months 6 months 12 months$0

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

$14,000

$16,000

$18,000

$20,000

$1,329

$3,730

$6,143

$9,842

$2,314

$7,215

$9,842

$18,815

No MRSA HAIMRSA HAI

Mean unadjusted pharmacy costs

1 month 3 months 6 months 12 months$0

$500

$1,000

$1,500

$2,000

$2,500

$3,000

$3,500

$4,000

$4,500

$360

$947

$1,638

$2,850

$672

$1,554

$2,469

$4,146

No MRSA HAIMRSA HAI

1. Impact of HAI on Excess LOS• Multi-state models (Beyersmann method)

HAI (1)

Admission (0) Discharge/death(2)

Extra LOS for pt with HAI

Extra LOS for pt without HAI

Extra LOS in state 0

Extra LOS in state 1

Probability of infection

Extra LOS (days) =