What is the Impact of the Internet on Medical Care Use and Cost?

Implications of Value Based Benefit Design from a Consumer Driven Health PlanStephen T. Parente, Ph.D., University of Minnesota

Funded by the Robert Wood Johnson Foundation Health Care Financing and Organization Initiative.

March, 2007

Presentation Overview A Conceptual Model for Effect of Internet

Use on Medical Care Demand within a Consumer Driven Health Plan for Value Based Purchasing

Descriptive Statistics from one Large CDHP Empirical Study Results Implications SOTU 2007 Bush Proposal Simulation –

NEW!

A Conceptual Model of the Impact of CDHP Internet Search on Medical Care Demand

Health plan-related Internet

Search

Don’t get CDHP Knowledge

Get CDHP Knowledge

Medical Care Demand

No Demand

Medical Care Demand

No Demand

1st Stage 2nd Stage 3rd Stage

How Has the Internet Been Used in a CDHP? Descriptive Statistics from a CDHP

1. How many CDHP members go online?

2. Who uses the health plan web site?

3. What are members looking at the web site?

What is the Impact of the CDHP Web Portal Use on Total Expenditure?

Do members use their health plan website for health information?

2003 2004

# Members 64,437 125,418

% Logged on 51.8 44.7

Who uses the health plan web site?

Total Number of Log-ons

2003 0 1 2-5 6-10 11+

Mean Family Size 2.1 2.45 2.61 2.72 2.79

Illness Burden 91.36 99.17

111.91 130.15

168.12

2004

Mean Family Size 2.06 2.39 2.56 2.68 2.76

Illness Burden 91 94.88

105.78 132.06

170.04

Family is the unit of analysis

What are members looking at?

N=56,073 Percent Accessed

No Yes

My Account 24.98 75.02

Doctors & Hospitals 32.83 67.17

My Benefit 35.76 64.24

Healthcare Costs 64.50 35.50

Health Resources 73.19 26.81

Pharmacy 68.01 31.99

2004 data; Family is the unit of analysis

Research Questions

1. What is the Impact of the CDHP Web Portal Use on Total Expenditure?

2. What is the Impact of Pharmacy Web Information on Rx Expenditure?

3. What is the Impact of Active Monitoring of Personal Care Account (PCA) on Spending?

What is the Impact of the CDHP Web Portal Use on Total Expenditure?

2003 1st Stage 2nd Stage 2nd Stage 2nd StageVariables Mean Internet Use Knowledge Demand/Cost Demand/Cost

Survey Case-mix Survey Case-mix Survey Case-mix Claims Case-mixDependent Variable(s)

Total Expenditure (Logged in regression) $7,464 7.698 7.698Health Plan Portal Use for Plan Choice (1=Yes, 0=No) 0.640 0.640CDHP Benefit Knowledge (1=Yes, 0=No) 0.522 0.522

Information Variables

Health Plan Portal Use for Plan Choice (1=Yes, 0=No) 0.640 - -0.123 -1.552 -0.196CDHP Benefit Knowledge (1=Yes, 0=No) 0.522 - - 4.492 0.899

InstrumentsGeneral Consumer Benefit Knowledge (1=Yes, 0=No) 0.586 0.036 0.134 - -Consumer does not like out of pocket risk (1=Yes, 0=No) 0.511 -0.213 -0.116 - -Consumer likes Internet plan tools (1=Yes, 0=No) 0.327 0.113 - - -Consumer has a regular physician (1=Yes, 0=No) 0.594 0.061 0.141 - -

Control VariablesOverall health of consumer (1=Excellent, 5=Poor) 1.896 0.053 -0.040 0.606 -Chronic illness of consumer's contract (1=Yes, 0=No) 0.351 0.061 0.031 0.865 -Consumer Income (1/1,000) $64.0 -0.001 -0.020 0.005 0.0004Condition Counts (from Claims using Johns Hopkins ADGs) 5.408 - - - 0.191

R-square 0.091 0.040 0.094 0.474Notes:

Regressions also adjusted by prior heath plan choice, age, age squared, gender, and number of dependents

BOLD Coefficients significant at p<.05

Regression Models by Outcome Variables

More Internet Users Have Higher Costs, Controlling for Illness!

What is the Impact of Pharmacy Web Information on Rx Expenditure?

What is the Impact of Pharmacy Web Information on Rx Expenditure?

2003 1st Stage 2nd StageVariables Mean Rx Internet Use Rx Demand/Cost

Survey Case-mix Survey Case-mixDependent Variable(s)

Rx Expenditure (Logged in regression) $1,514 5.408Rx Health Plan Internet Portal Use (1=Yes, 0=No) 0.863 0.863

Information Variables

Rx Health Plan Internet Portal Use (1=Yes, 0=No) 0.863 - -6.381

InstrumentsCDHP Benefit Knowledge (1=Yes, 0=No) 0.586 -0.021 -CDHP Portal Use for Plan Choice (1=Yes, 0=No) 0.511 -0.137 -

Control VariablesOverall health of consumer (1=Excellent, 5=Poor) 1.896 -0.030 0.041Chronic illness of consumer's contract (1=Yes, 0=No) 0.351 0.027 1.921Consumer Income (1/1,000) $64.0 0.0002 0.002

R-square 0.037 0.138Notes:

Regressions also adjusted by prior heath plan choice, age, age squared, gender, and number of dependents

BOLD Coefficients significant at p<.05

Regression Models by Outcome Variables

More Internet Users Have Lower Rx Costs, Controlling for Illness!

What is the Impact of Active Monitoring of PCA on Spending?

What is the Impact of Active Monitoring of PCA on Spending?

2003 1st Stage 2nd Stage 2nd StageVariables Mean Account Monitoring Spent within Account Spent over Deductible

Survey Case-mix Survey Case-mix Survey Case-mixDependent Variable(s)

Consumer finished year with $$ in account (1=Yes,0=No) 0.304 - 0.304 -Consumer finished year spending thru deductibe (1=Yes,0=No) 0.545 - - 0.545Used web site to monitor PCA Balance (1=Yes, 0=No) 0.464 0.464 - -

Information Variables

Used web site to monitor PCA Balance (1=Yes, 0=No) 0.464 - -0.322 0.320

InstrumentsCDHP Benefit Knowledge (1=Yes, 0=No) 0.586 0.060 - -CDHP Portal Use for Plan Choice (1=Yes, 0=No) 0.511 0.572 - -

Control VariablesOverall health of consumer (1=Excellent, 5=Poor) 1.896 -0.003 -0.168 0.198Chronic illness of consumer's contract (1=Yes, 0=No) 0.351 0.053 -0.045 0.156Consumer Income (1/1,000) $64.0 -0.0008 -0.001 0.001

R-square 0.352 0.121 0.161Notes:

Regressions also adjusted by prior heath plan choice, age, age squared, gender, and number of dependents

BOLD Coefficients significant at p<.05

Regression Models by Outcome Variables

$$ Activation MAY lead to Higher Costs, Controlling for Illness!

Implications Use of the Internet by CDHP subscribers

may be associated with moral hazard in all cases examined, except pharmacy.

The value of the Internet transparency as the enabler of a lower-cost ‘Consumer-driven’ health plan is not clear.

Value-based benefit design could have significant unintended consequences.

Incentives need to developed better before there is unmitigated transparency.

“But what do you have that is really current?”

To be presented:President Bush’s 2007 State of the Union Health Insurance Proposal Impact from ARCOLA model

2004 State of the Union Estimates

2007 State of the Union Estimates

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SOTU 2007

A tax deduction of $7,500/$15,000 – but you have to have health insurance to get the deduction

Health insurance premiums will be taxable (equal tax treatment of individual and ESI (employer sponsored, a.k.a. group, premiums)

Complicated incentives created by SOTU cannot be modeled by existing economics studies

Simulations Using a micro-simulation model, we

predicted the effect of 2007 SOTU on health insurance take-up and costs Background: Our model predicted the take-up of

HSA plans in the individual market quite accurately (Parente, Feldman et al, 2005)

Population: adults aged 19-64 who are not students, not covered by public insurance, and not eligible for coverage under someone else’s ESI policy

Baseline uninsurance: 27.3 million people Hold onto your hats…

Results

Uninsurance is reduced from 27.3 million to 7.1 million (a reduction of 20.2 million)

Annual cost of $204 billion: $104 billion subsidy to the individual

market $265 billion subsidy to the ESI market

with offsetting tax recovery of $165 billionSource: Steve Parente and Roger Feldman, ‘ARCOLA’

simulation model, SParente@csom.umn.edu and feldm002@umn.edu

Impact of Current ProposalBaseline MMA HSA take-up compared to 2007 SOTU Policy Estimate2009 Dollar Estimates

New MMA SOTU 2007 SOTU 2007 SOTU 2007 SOTU 2007 SOTU-MMAIndividual Market Population Population Subsidy Tax Recovery Total Impact DeltaHSA 3,156,133 10,035,204 $31,921,204,277 $0 $31,921,204,277 6,879,072PPO High 37,591 13,071 $59,770,496 $0 $59,770,496 -24,521PPO Low 6,046,777 19,360,294 $70,490,159,305 $0 $70,490,159,305 13,313,517PPO Medium 232,105 264,798 $1,284,375,645 $0 $1,284,375,645 32,693Uninsured 27,305,770 7,066,031 $0 $0 $0 -20,239,740

0Group Market 0HMO 19,667,935 15,696,972 $32,300,880,404 $28,189,232,288 $4,111,648,116 -3,970,964HRA 2,745,496 6,403,930 $22,877,835,972 $9,343,514,698 $13,534,321,274 3,658,434Employer-sponsored HSA 77,465 527,314 $2,772,799,510 $627,675,741 $2,145,123,769 449,849Opt-out HSA 38,923 1,782,713 $4,356,536,882 $1,158,935,717 $3,197,601,166 1,743,789PPO High 7,761,708 1,077,170 $2,350,558,189 $4,266,288,379 -$1,915,730,190 -6,684,538PPO Low 1,117,420 8,597,612 $38,418,477,384 $10,518,928,016 $27,899,549,369 7,480,193PPO Medium 40,877,293 50,365,946 $161,828,437,104 $110,655,985,001 $51,172,452,103 9,488,654Turned Down 12,471,072 267,927 $0 $0 $0 -12,203,144

Total Subsidy: $368,661,035,170 $164,760,559,838 $203,900,475,332

Why? Tax subsidy is quite large, even for low-

income workers Individuals are sensitive to the prices of

different types of health insurance: Individual HSA policies will increase from 3.1 to

10 million and low-option PPOs from 6 to 19.4 million

The subsidy covers the full cost of these policies for many people

The ESI market is not hollowed out, but expensive PPO plans will disappear

Summary of 2007 SOTU Effect

Could be the most comprehensive US health insurance market proposal ever on both the tax treatment of insurance AND reducing the uninsured by 82% to less than 10 million.

For more information on our research

Please visit:

www.ehealthplan.org

Thank You!