A Burden or Merely a Load: New Empirical Estimates of Health Insurance Loading Fees by Group Size

A Burden or Merely a Load: New Empirical Estimates of Health Insurance Loading Fees by Group Size Pinar Karaca-Mandic, University of Minnesota Jean M. Abraham, University of Minnesota Charles E. Phelps, University of Rochester 1

What is a Load? 2

In the context of health insurance Expected Insurance Benefits + Loading Fee = Premium Portion of the premium that is above and beyond the expected amount of medical expenditures to be paid by the insurance company 3

What does the loading fee cover? Loading Fee Administrative Costs Insurer Profits Taxes Costs associated with Selling insurance Collecting premiums Processing claims 4

In summary, loading fee is the relevant price of insurance Expected Insurance Benefits ($1) + Loading Fee ($0.25) = Premiu m ($1.25) 5

What do we know about loads? Non group policies: 60-80%, sometimes up to 100% Group policies: on average 15-20% varies by group size By how much? We know very little. No published academic research Some historical estimates cited from 1980s era: can be as high as 40% for small firms 6

Why do we care about loading fees? They represent the price of health insurance, and we care about price They tell us about the extent of administrative costs and profits Their magnitude has implications for Both for the demand and supply of health insurance Affordability of health insurance 7

Why care how loads vary with group size? For small businesses, high loads may be a serious issue. Too small to self insure Small firms repeatedly report barriers to afford health insurance. Only 45% offer health insurance If loads contribute a lot, could policy and reform proposals address this issue? National or regional insurance exchange proposals How to attract small businesses Whether/how to subsidize small businesses Assessing cost savings from reductions in loads Implications for employer sponsored insurance 8

Our objective To provide new estimates on the size and nature of loading fees and how they differ between small and larger groups 9

Summary findings Small firms pay a lot more in administrative costs relative to large employer groups. Relative to firms with less than 100 employees, loading fees are smaller by 20% for firms with 101-5000 employees 60% for firms with 5000 or more employees At this point, we estimate the following lower and upper bounds for loading fees 100 or fewer employees : 27% - 47% 1000 or fewer employees: 24% - 43% Across all firm sizes : 13% - 30% 10

Data Source Medical Expenditure Panel Survey (MEPS), the Household Component Insurance Component Linked File for the years 1997, 1998, 1999, 2001 Access at the AHRQ data center Household Component (HC) Demographic, health and expenditure data on all individuals in the household Insurance Component (IC) Information on employers, health insurance offerings, benefit designs, premiums for a subset of the HC individuals 11

Data Extraction Used the Person-Round-Plan files 1997-2001 Identified individuals covered by ESI either as the policy holder or dependent during the first round of their MEPS interview (IC collects data on the employer reported in the first round) Require that individuals stay with the same employer throughout the whole year and do not change insurance plans Exclude individuals with multiple private plans 22,663 individuals 12

Merge the sample to employers and plan Merge individuals to the employer and held plan in MEPS-IC MEPS-IC linkage is available only for a subset Focus on individuals for whom there was an exact match between the health plan reported by the individual and the employer. 7,875 individuals Exclude those with missing key info (firm size, premiums etc). 6,116 individuals Supplement with additional data Small group regulations by business state/year InterStudy data on HMO penetration rate in MSA/year Area Resource File data on relevant market conditions in county/year 13

Econometric framework individual firm size fixed component, varies by firm size, captured with firm size indicators Expected Insurance Payment Firm attributes other than firm size State group regulations Other market 14

Estimating Expected Insurance Payment Two Part Model Part I: Probability of Positive Private Insurance Payment Predict probability of any private pay Part II: Amount of Private Insurance Payment Conditional on Positive Private Pay Predict conditional private pay In both parts, controls include individual demographics, health insurance benefit design and scope of policy Expected Insurance Payment = probability of any spending x conditional private payment 15

Caution: Expenditures in MEPS are biased down Private insurer payments are 21% greater in National Health Expenditure Accounts than in MEPS (Sing et al, 2006) Selden and Sing (2008) construct NHEA aligned private insurance payments by adjusting them up 24.4% Zuvekas et al, 2005 compare mean health expenditures in MEPS to those in MarketScan data for large self insured employers. Again 21%-29% lower private health insurance payments in MEPS. Zuvekas and Olin (2009) compare MEPS expenditures and claims of the Medicare beneficiaries 50% of the discrepancy due to missing data for people with more than $100,000 in annual total expenditures 50% due to underreporting The bias is uniform across population 16

Our approach for adjusting MEPS Want to make sure MEPS is aligned to other employer sponsored insurance Inflate MEPS private payments to match those in MarketScan by age and gender (provided by Zuvekas and colleagues) Female Male Age Age MEPS MarketScan Adjustment Factor 0-17 486 1114 2.29 18-34 2228 2426 1.09 35-49 2200 2898 1.32 50-64 2976 4075 1.37 0-17 602 1253 2.08 18-34 1288 1429 1.11 35-49 1827 2257 1.24 50-64 3031 3976 1.31 17

Select Summary Statistics of Individuals Individual characteristics Mean Std % msa 81 % age 0-17 32 % age 18-34 22 % age 35-49 30 % age 50-64 16 % female 50 % white 83 % black 12 % hispanic 18 % married 46 total household income ($1000), 2007 dollars 104 76 num kids 1.87 1.96 fam size 3.62 1.56 num years of education 10.81 4.72 Health Conditions % cancer 1.26 % diabetes 2.39 % high cholesterol 1.95 % heart disease 1.68 % hypertension 5.8 % asthma 3.34 % depression, anxiety disorder 5.12 18

Select Summary Statistics of Employers/Plans Employer's workforce composition Mean Std % female workers 43.07 25.14 % workers over age 50 21.8 14.62 % union representation 13.19 27.11 % workers earning $15 per hour or more 37.49 29.34 % Government owned 9 % Nonprofit 20 % in business 0-5 years 3 % in business 6-10 years 3 % in business 11-50 years 18 % in business more than 50 years 20 Benefit Design Features % Exclusive provider organization 44 Individual deductible 147 331 % zero individual deductible 70 Ind. deductible among positive deductible plans 486 445 % with OOP maximum 63 Total premium for single coverage 3405 1366 Employee contribution to single coverage 585 662 % Plan includes: Outpatient prescription 70 Dental 19 Inpatient mental illness coverage 79 Outpatient mental illness coverage 67 Alcohol/substance abuse 60 19

Firm size distribution, raw data MarketScan Adjusted Private Ratio of Mean Premiums to Mean Adjusted Prv. Ins. Pay Firm Size Number Any Spending Unadjusted Private Insurance Pay Insurance Pay Single Premiums (%) mean st dev mean st dev mean st dev 1-10 214 79 1587 3500 2192 4690 3633 1840 1.66 11-25 380 81 1385 3305 1986 4801 3469 1440 1.75 26-50 271 79 1457 3168 2073 4736 3558 1256 1.72 51-100 412 81 1251 3098 1849 4794 3200 1172 1.73 101-500 899 83 1883 5666 2701 8023 3451 1432 1.28 500-5000 1040 79 1658 6752 2413 9146 3299 1387 1.37 5000-10000 444 84 1710 3529 2489 5459 3379 1208 1.36 >10000 2456 84 1927 7783 2767 11273 3425 1334 1.24 Mean across all size categories 82 1747 6318 2516 9037 3405 1366 1.35 20

Two-part model for predicting insurance payments Part I Part II Coef. Est Std. Err. stat. sig. Coef. Est Std. Err. stat. sig. Demographic/Socio-Economic age between 0-17 0.12 0.22 * -0.14 0.15 ** age between 18-34 0.004 0.15-0.75 0.09 *** age between 35-49 -0.02 0.14-0.35 0.08 *** female 0.46 0.08 *** 0.17 0.06 *** number of children 0.12 0.06 ** -0.15 0.05 *** number of children squared -0.01 0.01 *** 0.01 0 *** family size -0.39 0.11 *** -0.07 0.09 ** family size squared 0.02 0.01 ** 0.01 0.01 ** # years of schooling -0.02 0.03 * 0.13 0.02 *** # years of schooling squared 0.001 0.002 * -0.01 0 *** Total household income ($1000) 9.58 1.47 *** -1.55 0.93 ** Total household income ($1000) squared -0.013 0.003 *** 0.003 0.002 ** work less than 20 hours 0.66 0.32 *** 0.3 0.15 ** work between 20-29 hours 0.26 0.25 ** 0.04 0.14 * work between 30-39 hours 0.25 0.19 ** 0.17 0.12 ** job tenure under 1 year -0.32 0.23 ** -0.04 0.14 * job tenure 1-5 years -0.16 0.13 ** 0.16 0.08 ** job tenure 6-10 years -0.12 0.15 ** 0.2 0.1 *** Health cancer 2.65 1.08 *** 0.85 0.19 *** chol/diabetes/heart 2.97 0.37 *** 0.6 0.08 *** asthma 1.33 0.31 *** 0.78 0.15 *** pregnant/delivered 2.97 1.01 *** 1.72 0.16 *** depression/anxiety 1.6 0.32 *** 0.62 0.1 *** muscle disorders 1.01 0.29 *** 0.48 0.14 *** oth_chronic 0.6 0.71 ** 0.57 0.24 *** Benefit Features family coverage 0.54 0.12 *** 0.12 0.08 ** exclusive provider org 0.39 0.09 *** 0.07 0.06 ** individual deductible 0-$300 0.24 0.14 ** 0.12 0.11 ** individual deductible $300-$500 0.17 0.12 ** 0.13 0.09 ** 21

Premium Equation (1) Coef. Est Std. Err. stat. sig. Firm Size cat 1:1-10 reference cat 2:11_25 73 156 cat 3:26_50-34 155 cat 4: 51_100-268 146 * cat 5:101_500-121 148 cat 6:500_5000-304 144 ** cat 7:5000_10000-392 154 ** cat 8:>10000-275 143 ** Expected Insurer Payment and Firms Size Interactions Expected Ins. Pay 0.08 0.033 ** Expected Ins. Pay x cat 2-0.108 0.037 *** Expected Ins. Pay x cat 3-0.083 0.035 ** Expected Ins. Pay x cat 4-0.045 0.038 Expected Ins. Pay x cat 5-0.079 0.041 * Expected Ins. Pay x cat 6-0.077 0.034 ** Expected Ins. Pay x cat 7-0.06 0.036 * Expected Ins. Pay x cat 8-0.085 0.033 ** 22

Premium Equation (2) Coef. Est Std. Err. stat. sig. Workforce Composition Less than 25% female -139 60 ** Between 26%-50% female -34 59 Less than 25% over age 50-218 54 *** More than 50% unionized 487 69 *** More than 50% earning $15/hour or more 226 56 *** Industry of the Business Retail 323 198 * Personnel Services 1082 299 *** Business Services 557 214 ** Other Services 498 188 ** Manufacturing 324 189 * Wholesale Trade 363 198 * Finance/Insurance 562 196 *** Transportation 557 207 ** Construction 166 244 Agriculture -466 327 Mining 532 318 * Other Business Characteristics Government owned 254 171 Nonprofit 178 68 ** In business 0-5 years 73 134 In business 6-10 years 23 127 In business 11-50 years 81 57 Market Conditions MSA Indicator -16 76 mean nurse wage rate 46 16 *** average malpractice payment in state ($1000) -1.23 0.54 ** percapita hospitals 620537 915989 * % over age 65 1487 822 * HMO penetration rate x MSA indicator -203 184 23

Predicted Insurer Payments and Premiums $ (in 2007) 3800 3600 3400 3200 3000 2800 2600 2400 2200 2000 1-10 11-25 26-50 51-100 101-500 500-5000 5000- >10000 Predicted 10000 Insurer Payments Number of employees Predicted Premiums Predicted Loading Fees 0.55 0.5 0.45 0.4 0.35 0.3 0.25 0.2 0.15 0.1 1-10 11-25 26-50 51-100 101-500 500-5000 5000-10000 >10000 Number of employees 24

These estimates differ from other reports We find that loading fees are similar for firms under 100 employees Previous reports indicate a downward gradient 30-40% up to 10 employee, 20% 11-100 employees Our estimates are higher for all firm size categories Even for the largest, we estimate loads around 17%, other reports indicate 10% or lower 25

Aggregate implications from MEPS (1) Extract the nationally representative number of enrollees by group size from MEPS-IC summary tables Information available for various firm size categories Number of employees % employees in firms that offer coverage % employees that enroll in ESI fin forms that offer coverage Estimate primary vs. dependent population from HC-IC linked data by firm size Estimate total # enrollees in ESI by firm size 26

Aggregate implications from MEPS (2): overall loading fee of 30% Inferred Number of Employees and Dependents Covered by ESI Expected Insurer Payments Premiums for Single Coverage Ratio of Premiums to Expected Insurer Payments Total Premiums Paid Total Insurer Payments Firm Size 1-10 8,689,296 2617 3646 1.39 3.168E+10 2.274E+10 11-25 8,684,860 2347 3445 1.47 2.992E+10 2.0383E+10 26-100 15,272,021 2238 3387 1.51 5.173E+10 3.4179E+10 101-1000 24,657,216 2489 3447 1.38 8.499E+10 6.1372E+10 >1000 78,663,082 2762 3378 1.22 2.657E+11 2.1727E+11 Ratio Total 135,966,475 4.64E+11 3.5594E+11 1.3 These figures are for 2001, with 2007 dollars 27

NHEA Estimates of Private Insurance Costs Table 1: Private Health Insurance Premiums Paid and Benefits Received 2000 2001 2002 2003 2004 2005 2006 2007 Private Health Insurance Premiums 454.7 497.6 551.1 603.7 645.9 690 731.3 775 Private Health Insurance Benefits 402.8 441 482.3 521.5 560.6 598.9 637.9 680.3 Net Cost 51.9 56.6 68.8 82.2 85.3 91.1 93.4 94.7 Net Cost as Percent of Benefits 12.88 12.83 14.26 15.76 15.22 15.21 14.64 13.92 Source: http://www.cms.hhs.gov/nationalhealthexpenddata/downloads/tables.pdf (Table 12) NHEA estimates suggest an overall loading fee of 13-15%, much lower than our 30% 28

Why are our estimates higher? Although we inflated the MEPS private payments to match other ESI, maybe it is still not sufficient, and we need to inflate more - coming up next NHEA estimates include many other components besides ESI. We need to sort out and understand the portion of NHEA figures attributable to ESI work in progress We are working with single coverage premiums and expected payments for individuals Our estimates may well be lower when we distinguish single coverage and family coverage work in progress 29

Estimates Comparable to NHEA Further inflate insurance benefits paid out by 10%: Obtain an overall loading fee of 19% by 15%: Obtain an overall loading fee of 13% (the magic number) 0.6 0.5 status quo 10% adjustment 15% adjustment 0.4 0.3 0.2 0.1 0 1-10 11-25 26-50 51-100 101-500 500-5000 5000-10000 Number of employees >10000 30

Range of Estimates (lower bound: status quo, upper bound: 15% inflation of private payment) Across all firms, average loading fee (total premiums/total insurer payments) ranges between 13% to 30% 100 or fewer employees : 27% - 47% 1000 or fewer employees: 24% - 43% Assuming 136 million covered under ESI, loading costs are between $55 - $108 billion (in 2007 dollars 100 or fewer employees : $24 - $36 billion 1000 or fewer employees: $39 - $60 billion 31

Implications 15% reduction in loading costs would save (assuming no other changes) $4-5 billion annually for firms with 100 or fewer employees $6-9 billion annually for firms with 1000 or fewer employees If loading fees were reduced to 15%, annual savings would be (assuming no other changes) $11-24 billion annually for firms with 100 or fewer employees $15-$39 billion annually for firms with 1000 or fewer employees. 32

Next Steps More refined aligning MEPS private payments to match NHEA Take into account different points in expenditure distribution Take into account adjustments by sevrice categories Estimate separate models for those in single coverage and family coverage 33