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