session 35 lecture: medicare payment is different than commercial!
TRANSCRIPT
Session 35 L, Medicare Payment is Different than Commercial!
Moderator: Rebecca Owen, FSA, MAAA
Presenters:
Zack Cooper, Ph.D. James Patrick Hazelrigs, ASA, MAAA
The Price Ain’t Right? Hospital Prices and Health Spending on the Privately Insured*
Zack Cooper, Yale UniversityStuart Craig, University of PennsylvaniaMartin Gaynor, Carnegie MellonJohn Van Reenen, London School of Economics
www.healthcarepricingproject.org
Introduction
• The average premium for employer-sponsored family health coverage was $17,545 in 2015; 20% of those under 65 with full insurance report problems paying medical bills
[Kaiser Family Foundation, 2015; Kaiser Family Foundation, 2016]
• Wide ranging analysis of variation in health care spending via Medicare suggests quantity of care given drives spending variation
[Dartmouth Atlas work: i.e. Fisher et al., 2009; Wennberg et al., 2002]
• However, results may not generalize to private markets where prices are not set administratively
[Philipson et al. 2010;Chernew et al., 2010; IOM, 2013; Franzini et al. 2010]
• The challenge: almost no nation-wide hospital-specific price data and scant data on spending for privately insured
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This Paper
• Analyzes employer sponsored insurance claims from Aetna, UnitedHealth, and Humana that includes negotiated transaction prices
• Studies the variation in private health care spending, analyze the contribution of prices to spending variation, and examine providers’ price variation
Key Findings – Price Plays Crucial Role in Spending by Privately Insured
1. Low correlation (0.140) between Medicare and private spending per person;
2. Price explains large portion of national variation in inpatient private spending;
3. Substantial variation in prices, both within and across markets;
4. Higher hospital market concentration is associated with higher hospital prices;
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This Paper
• Analyzes employer sponsored insurance claims from Aetna, UnitedHealth, and Humana that includes negotiated transaction prices
• Studies the variation in private health care spending, analyze the contribution of prices to spending variation, and examine providers’ price variation
Key Findings – Price Plays Crucial Role in Spending by Privately Insured
1. Low correlation (0.140) between Medicare and private spending per person;
2. Price explains large portion of national variation in inpatient private spending;
3. Substantial variation in prices, both within and across markets;
4. Higher hospital market concentration is associated with higher hospital prices;
3
Outline
I. Overview of the HCCI Data and Price Calculations
II. Public/Private Spending and Price/Volume Decomposition;
III. Variation in Hospital Prices Across Markets;
IV.Variation in Hospital Prices Within Markets;
V. Predictors of Provider Prices;
VI. Implications
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The Data and Our Price Measures
Overview of the HCCI Data
• Claims level data from the Health Care Cost Institute
• Includes ESI claims from Aetna, UnitedHealth Group, and Humana for individuals with coverage from from 2007 – 2011;
• 88.7 million unique individuals;• Covers approximately 27.6% of Americans with ESI• 1% of GDP, 5% of health spending• Coverage in all 306 hospital referral regions in the US
• Data includes the price providers charged, the negotiated contribution of the payers, and the contribution of patients via co-payments and co-insurance;
• Able to link to a wide array of external data6
National Coverage of Data
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•High Shares: Texas, Arizona, Colorado, Florida, Georgia, Kentucky, Ohio, Wisconsin, New Jersey, DC, and Rhode Island have a high share of HCCI data.
•Low Shares: Vermont, Michigan, Alabama, Wyoming, Montana, South Dakota, and Hawaii
WA16.4
OR16.0
CA15.6
AK15.2
HI.1.9
MT8.8
NM16.7
WY9.4
NV13.7 UT
19.1
AZ39.8
CO33.6
ID13.3
TX42.9
ND12.9
S.D.7.8
NE20.0
KS21.7
OK26.3
MN22.7
IA14.9
MO30.0
AR16.6
LA27.9
WI34.5
IL26.8
KY44.2
IN18.0
OH34.3
WV11.5
TN.22.0
MS15.9
AL8.4
GA44.6
FL39.8
SC15.8
NC20.2
VA23.8
PA20.0
NY19.0
ME25.4
MI9.9
VT6.6
NH13.7
MA12.7RI
31.0
CT28.0
NJ39.2
MD28.8
DE29.2
DC37.2
HI1.9
Note: Coverage rates were calculated using HCCI enrollment data. Statewide insurance coverage totals were derived from the American Community Survey for 2011.
Data Sample
• Limit to those age 18-64 with ESI coverage and at least 6 months of coverage;
• Three Samples
• Spending Sample: All physician, outpatient, and inpatient claims (no Rx)
• Inpatient Sample: All inpatient facilities claims
• Procedure Samples: Hip and knee replacements, vaginal and cesarean delivery, PTCA, colonoscopy, and lower limb MRI;
• Limit observations to those with 1st percentile < price <99th percentile; exclude those with length of stay in top 1% by DRG/Condition, require match to AHA;
• Limit to providers doing 50 episodes per year for inpatient analysis per year; 10 conditions for conditions per year.
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Definition of Price
• Price captures the amount a facility was paid (including by insurer and patient);
• Identify risk-adjusted hospital prices for seven procedures identified using very narrow coding (i.e. no complications, no revisions), exclude LOS in top 1%, single ICD-9CM/DRG combo, ICD-9 Diag. code for colonoscopy; CPT-4 code for MRI*;
• Create a hospital inpatient price index that is conditional on who a hospital treats and what mix of DRGs it delivers;
9* For Medicare comparisons we use DRGs to define cohorts
How Medicare Sets Prices
Operating base
payment rate
Hospital Wage Index Adjustment
Base Rate Adjusted for Geographic
Factors
MS-DRG Weight
Adjusted Payment
Rate
Indirect Medical Education Payment
Disprop. Share (DSH)
Payment
Payment for MS-DRG
=
x =+
Hospital Adjusters
=
Wage Index > 1.0
Non-labor related portion
Wage Index ≤ 1.0
68.8% adjusted for area wages
62.% adjusted for area wages
+
Calculating Medicare PPS Payments
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Charge/Negotiated Price/Medicare Fee Ratio
12Notes: Prices are averaged from 2008 – 2011, put in 2011 dollars. Note that we only include hospital-based prices – so we exclude, for example, colonoscopies performed in surgical centers and MRIs that are not carried out in hospitals.
Knee Replacement Negotiated Prices and Charges ‘08 – ‘11
13Notes: Regression-adjusted prices presented in 2011 dollars
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Spending Analysis and Decomposition
Medicare and ESI Overall Spending Per Beneficiary
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Correlation of Public and Private Total Spending Per Beneficiary: 0.140
Note: Data on Medicare is for 2011 and from the Dartmouth Atlas. Spending for Medicare beneficiaries includes Part A & B and is risk adjusted by age, race, and sex. Spending on private enrollees is adjusted by age and sex and includes all inpatient, outpatient, and physician claims
Scatter Plot of Ranking of Medicare Spending Per Beneficiary and Private Spending Per Beneficiary
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Notes: Data on Medicare spending was downloaded from the Dartmouth Atlas http://www.dartmouthatlas.org/. An HRRwith a rank of 1 has the lowest spending per beneficiary of all HRRs. An HRR with a rank of 306 has the highest spendingper beneficiary of all HRRs. Overall spending does not include pharmaceutical spending.
Scatter Plot of Ranking of Medicare Spending Per Beneficiary and Private Spending Per Beneficiary
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Notes: Data on Medicare spending was downloaded from the Dartmouth Atlas http://www.dartmouthatlas.org/. An HRRwith a rank of 1 has the lowest spending per beneficiary of all HRRs. An HRR with a rank of 306 has the highest spendingper beneficiary of all HRRs. Overall spending does not include pharmaceutical spending.
Scatter Plot of Ranking of Medicare Spending Per Beneficiary and Private Spending Per Beneficiary
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Notes: Data on Medicare spending was downloaded from the Dartmouth Atlas http://www.dartmouthatlas.org/. An HRRwith a rank of 1 has the lowest spending per beneficiary of all HRRs. An HRR with a rank of 306 has the highest spendingper beneficiary of all HRRs. Overall spending does not include pharmaceutical spending.
Scatter Plot of Ranking of Medicare Spending Per Beneficiary and Private Spending Per Beneficiary
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Notes: Data on Medicare spending was downloaded from the Dartmouth Atlas http://www.dartmouthatlas.org/. An HRRwith a rank of 1 has the lowest spending per beneficiary of all HRRs. An HRR with a rank of 306 has the highest spendingper beneficiary of all HRRs. Overall spending does not include pharmaceutical spending.
Formal Decompositions of Variance
The variance of spending per DRG d may be decomposed into three components:
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𝑣𝑣𝑣𝑣𝑣𝑣(ln(𝑝𝑝𝑑𝑑𝑞𝑞𝑑𝑑)) = 𝑣𝑣𝑣𝑣𝑣𝑣(ln(𝑝𝑝𝑑𝑑)) + 𝑣𝑣𝑣𝑣𝑣𝑣(ln(𝑞𝑞𝑑𝑑) + 2𝑐𝑐𝑐𝑐𝑣𝑣(ln(𝑝𝑝𝑑𝑑) , ln(𝑞𝑞𝑑𝑑))
Captures share of variance in spending attributable to variation in prices across HRRs
Captures share of variance in spending attributable to variation in the quantity of care across HRRs
The covariance term captures the share of variance attributable to the covariance of price and quantity.
Come up with price/quantity contribution by averaging DRG results by spending per DRG
Decomposition Results
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Private Medicare
Share PriceShare
QuantityShare
Covariance Share PriceShare
QuantityShare
Covariance
Cardiac valve & oth maj cardiothoracic proc w/o card cath w CC 51.2% 17.8% 31.0% 11.7% 48.1% 40.3%Cardiac valve & oth maj cardiothoracic proc w/o card cath w MCC 50.4% 13.4% 36.2% 11.3% 46.8% 41.8%Cellulitis w/o MCC 39.2% 97.4% -36.6% 7.3% 96.8% -4.1%Circulatory disorders except AMI, w card cath w/o MCC 43.6% 60.2% -3.8% 6.6% 101.1% -7.7%Coronary bypass w cardiac cath w/o MCC 56.1% 14.2% 29.8% 6.1% 72.2% 21.7%Craniotomy & endovascular intracranial procedures w MCC 40.8% 19.0% 40.2% 7.8% 54.5% 37.8%Esophagitis, gastroent & misc digest disorders w/o MCC 57.7% 80.3% -38.0% 10.7% 104.3% -15.0%Infectious & parasitic diseases w O.R. procedure w MCC 67.2% 5.0% 27.8% 9.0% 62.4% 28.6%Kidney & urinary tract infections w/o MCC 53.8% 87.2% -41.0% 9.9% 107.2% -17.0%Major cardiovasc procedures w MCC or thoracic aortic anuerysm repair 59.7% 9.6% 30.7% 11.7% 52.1% 36.3%Major cardiovascular procedures w/o MCC 52.1% 26.5% 21.3% 10.9% 69.6% 19.5%Major joint replacement or reattachment of lower extremity w/o MCC 55.4% 73.6% -28.9% 12.3% 101.7% -14.0%
Average Shares (weighted by spending) 45.9% 36.2% 17.9% 9.4% 76.6% 14.0%
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National Variation in Prices
Inpatient Prices
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Inpatient Prices—normalized using the wage index
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The Price of a Knee Replacement is Higher in Grand Junction than it is in Boston
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Private Knee Replacement Prices
National Variation in Prices and Medicare Fees: Knee Replacement
Note: Each column is a hospital; Medicare prices are calculated using Medicare Impact Files
Medicare Knee Replacement PricesMean 12,986Min - Max 10,254 - 24,021p10-p90 11,213 - 15,441IQR 11,734 - 13,605p90/10 ratio 1.38IQR ratio 1.16Coefficient of Variation 0.15Gini Coefficient 0.07
Mean 23,102Min - Max 3,298 - 55,825p10-p90 14,338 - 33,236IQR 17,365 - 27,151p90/10 ratio 2.32IQR ratio 1.56Coefficient of Variation 0.33Gini Coefficient 0.18
Private Knee MRI Prices
National Variation in Prices and Medicare Fees: Knee MRI
Note: Each column is a hospital; Medicare prices are calculated using Medicare Impact Files
Medicare Knee MRI PricesMean 353Min - Max 293 - 546p10-p90 325 - 389IQR 335 - 366p90/10 ratio 1.2IQR ratio 1.09Coefficient of Variation 0.08Gini Coefficient 0.04
Mean 1,331Min - Max 260 - 3,174p10-p90 745 - 2,036IQR 960 - 1,629p90/10 ratio 2.73IQR ratio 1.70Coefficient of Variation 0.38Gini Coefficient 0.21
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Within Market Variation in Prices
Knee Replacement Facility Prices Within Markets
Denver, CO Atlanta, GA Manhattan, NY
Columbus, OH Philadelphia, PA Houston, TX
Note: Each column is a hospital. Prices are regression-adjusted, measured from 2008 – 2011, and presented in 2011 dollars.
Colonoscopy Facility Prices Within Markets
Denver, CO Atlanta, GA Manhattan, NY
Columbus, OH Philadelphia, PA Houston, TX
Note: Each column is a hospital. Prices are regression-adjusted, measured from 2008 – 2011, and presented in 2011 dollars.
Lower Limb MRI Facility Prices Within Markets
Denver, CO Atlanta, GA Manhattan, NY
Columbus, OH Philadelphia, PA Houston, TX
Note: Each column is a hospital. Prices are regression-adjusted, measured from 2008 – 2011, and presented in 2011 dollars.
Lower Limb MRI Facility Prices Within Markets
Denver, CO Atlanta, GA Manhattan, NY
Columbus, OH Philadelphia, PA Houston, TX
Note: Each column is a hospital. Prices are regression-adjusted, measured from 2008 – 2011, and presented in 2011 dollars.
Private Price Medicare Reimbursement
33
Drivers of Price Variation
Correlates of Hospital Prices
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Providers’ Negotiated Prices
Quality of the Provider?
• Clinical quality
• Hotel-related services
• Perceived quality
What is associated with high hospital prices?
Hospital & Local Area Characteristics?
• Teaching status
• Ownership
• Hospital size
• Local costs
• Local wage rates
Medicare/Medicaid Penetration?
• Hospitals’ share of patients funded by Medicare or Medicaid
• Medicare payment rates
• Share of uninsured
Market Structure?
• Provider market structure
• Payer market structure
Bivariate Correlations: Price and Local and Hospital Characteristics
35Notes: The x-axis captures the correlations between key variables featured in our regression and our hospitals’ inpatient prices averaged from 2008 – 2011 and inflation adjusted into 2011 dollars. The bars capture the 95% confidence intervals surrounding the correlations.
Bivariate Correlations: Price and Local and Hospital Characteristics
36Notes: The x-axis captures the correlations between key variables featured in our regression and our hospitals’ inpatient prices averaged from 2008 – 2011 and inflation adjusted into 2011 dollars. The bars capture the 95% confidence intervals surrounding the correlations.
Bivariate Correlations: Price and Local and Hospital Characteristics
37Notes: The x-axis captures the correlations between key variables featured in our regression and our hospitals’ inpatient prices averaged from 2008 – 2011 and inflation adjusted into 2011 dollars. The bars capture the 95% confidence intervals surrounding the correlations.
Bivariate Correlations: Price and Local and Hospital Characteristics
38Notes: The x-axis captures the correlations between key variables featured in our regression and our hospitals’ inpatient prices averaged from 2008 – 2011 and inflation adjusted into 2011 dollars. The bars capture the 95% confidence intervals surrounding the correlations.
Bivariate Correlations: Price and Local and Hospital Characteristics
39Notes: The x-axis captures the correlations between key variables featured in our regression and our hospitals’ inpatient prices averaged from 2008 – 2011 and inflation adjusted into 2011 dollars. The bars capture the 95% confidence intervals surrounding the correlations.
Hospital Market Power Raises Hospital Prices
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Note: An asterisk indicates significance at the 5% level. This figure is based on OLS estimates for 8,176 hospital-year observationswith standard errors clustered at the HRR-level in parentheses. The controls include insurance market structure, HCCI insurer share bycounty, hospitals use of technology, U.S. News & World Report Ranking, hospital beds, indicators for teaching hospitals, government-owned hospitals, and not for profit hospitals, the Medicare base payment rate, the share of hospitals’ patients that are funded byMedicare, and the share funded by Medicaid. The regressions also include HRR fixed effects and year fixed effects.
15.3%*
6.4%*
4.8%*
Hospital Market Power and Hospital Price
Greater Insurance Market Power Lowers Hospital Prices
41
Note: An asterisk indicates significance at the 5% level. This figure is based on OLS estimates for 8,176 hospital-year observationswith standard errors clustered at the HRR-level in parentheses. The controls include hospital market structure, HCCI insurer share bycounty, hospitals use of technology, U.S. News & World Report Ranking, hospital beds, indicators for teaching hospitals, government-owned hospitals, and not for profit hospitals, the Medicare base payment rate, the share of hospitals’ patients that are funded byMedicare, and the share funded by Medicaid. The regressions also include HRR fixed effects and year fixed effects.
- 4.2%*
- 9.0%*
- 15.2%*
Insurer Market Power and Hospital Price
Bigger, High Tech Hospitals Have Higher Prices
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Note: An asterisk indicates significance at the 5% level. This figure is based on OLS estimates for 8,176 hospital-year observationswith standard errors clustered at the HRR-level in parentheses. The controls include hospital market structure, insurance marketstructure, HCCI insurer share by county, hospitals use of technology, U.S. News & World Report Ranking, hospital beds, indicators forteaching hospitals, government-owned hospitals, and not for profit hospitals, the Medicare base payment rate, the share of hospitals’patients that are funded by Medicare, and the share funded by Medicaid. The regressions also include HRR fixed effects and yearfixed effects.
5.1%*2.0%*
1.9%-10%* -1.0%*
5.1%*4.1%*
1.9%-9.9%* -1.0% -8.7% 0.3%
Quality is Weakly Related to Price
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Note: An asterisk indicates significance at the 5% level. This figure is based on OLS estimates for 8,176 hospital-year observationswith standard errors clustered at the HRR-level in parentheses. The controls include hospital market structure, insurance marketstructure, HCCI insurer share by county, hospitals use of technology, U.S. News & World Report Ranking, hospital beds, indicators forteaching hospitals, government-owned hospitals, and not for profit hospitals, the Medicare base payment rate, the share of hospitals’patients that are funded by Medicare, and the share funded by Medicaid. The regressions also include HRR fixed effects and yearfixed effects.
1%
3.7%*2.0%*
3.1%*
13.3%*
Policy Changes to Address Price
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Fundamental Tension:
• Bigger hospitals often have better quality; integration has virtues; in a push towards pay-for performance, size gives stability;
• Bigger Hospitals also clearly have market power, which allows them to raise prices and it stymies incentives for quality;
Policy Options
1. More vigorous antitrust enforcement (including vertical integration)
1. Regulating prices (particularly out-of-network billing and trauma charges)
2. Make patients more price sensitive (leveraged by price transparency where the devil is in the details)