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

New Findings from a Consumer Driven Health Plan Stephen T. Parente

Roger FeldmanJon B. Christianson

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

June, 2005

Presentation Overview 1999 Dreaming: The Internet and “eHealth

Plans” 2005 Reality: Health Plan Web Portals A Conceptual Model for Effect of Internet Use on

Medical Care Demand within a Consumer Driven Health Plan

Research Questions Study Setting & Data Statistical Modeling Using Instrumental

Variables Results Implications

1999 Vision of E-Commerce in 2005 $250 billion of the New Health Economy

would be e-commerce (e.g., mostly e-prescribing).

Ubiquitous electronic health records Providers access/enter data on web Patients access/enter data on web Information access as seamless as credit card

transactions Informed health care shoppers (patients) pick

hospitals and physicians based on quality. Internet-enabled medical savings accounts.

$250 billion of the New Health Economy would be e-commerce (e.g., mostly e-prescribing).

Ubiquitous electronic health records Providers access/enter data on web Patients access/enter data on web Information access as seamless as credit card

transactions Informed health care shoppers (patients) pick

hospitals and physicians based on quality. Internet-enabled medical savings accounts.

Reality of 2005

Consumer Driven Health Plan (CDHP)Storyline to Date Version 1.0 – Dot-com ehealth insurance (1998-2004)

Definity Health Vivius Lumenos Healthmarket Destiny Health

Version 1.5 – ‘Me-too’ HRA responses (2003-2005) Aetna Cigna Humana Blue Cross Blue Shield

Version 2.0 - Health Savings Accounts drive up demand (2003-on) 2003 MMA Dot-com venture capitalists get return on their investment “Ownership society” proposals United Health’s Golden Rule/Exante/UHC Trifecta “The Health Partners HSA” Fidelity, Vanguard, Merrill Lynch looking to jump in

What is the Relationship Between the Internet and CDHPs? Early CDHP developers made new and innovative use

of the Internet a key part of their business plan. Primary selling point #1: Better informed

consumers/patients will be more knowledgeable purchasers of medical care.

Primary selling point #2: Giving consumers an incentive to evaluate the price of medical care goods will make them even more engaged.

Proposed outcome: e-health plans will lead to more cost-effective health care consumption.

Previous research by Baker, Bundorf & Wagner (2003) suggests consumers actively seek information on the web. The key question is whether information-seeking affects demand.

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?

Study Setting University of Minnesota’s CDHP Plan: Definity Health Years Studied: 2002 and 2003 Data – Unique combination of:

Two telephone surveys (Spring, 2003 & Spring, 2004) Claims data from 2002 and 2003 for CDHP enrollees Human resources records for all employees

Study size: 565 continuously employed workers in 2002 and 2003.

Take-up of CDHP approximately 4% in 2002 and 7% in 2003. Other plan choices were: (HMO: 51%, PPO: 13%, Tiered:

29%) General caveat: ONE Employer’s experience can be quite

different due to: Alternatives offered Plan design Communications with employees Sponsor’s objectives for the plan

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

Econometric Approach Objective: Estimate impact of CDHP web portal use and

CDHP benefit knowledge on medical care demand. Issue: Internet use and benefit knowledge are likely to be

endogenous to medical care demand. Approach: Use an instrumental variables approach similar to

work by Parente, Salkever and DaVanzo (2005) where benefit knowledge for one type of medical service (e.g., flu shot) was instrumented by benefit knowledge of another service (e.g., mammography) and general benefit knowledge.

Instrument candidates used in this analysis: Overall university health plan benefit knowledge Have a usual source of medical care Like to have a plan with online tools Are concerned with out of pocket expenses

Instruments must be correlated with Internet use or benefit knowledge, but must not affect medical care demand.

Used two-stage lease squares with tests for over-identification.

Econometric Model of Three Stages

1. Internet usei = f(agei, genderi, incomei, health statusi, prior health plani,t-1, information preferencesi, ii)

2. Knowledgei = f(Ineti, agei, genderi, incomei, health statusi, prior health plani,t-1, other knowledgei,,,21)

3. Medical Care Demandi = f(Ineti, Knowledgei, agei, genderi, incomei, health statusi, prior health plani,t-1,,,31)

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

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

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

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

Summary of Results

No statistically significant impact of general CDHP web site use on medical care demand.

CDHP subscribers with higher benefit knowledge may consume more medical resources. Results differ depending on case-mix method used (survey-based methods show results and claim-based methods do not).

Consumer use of CDHP pharmacy Internet tools is associated with a substantial reduction in pharmacy expenditure.

Consumers who have money left in their PCA are less likely to examine their accounts.

Consumers who actively monitor their PCA balances are much more likely to exceed their deductible.

Implications Use of the Internet by CDHP subscribers

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

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

May need long-term data to see if what seems like moral hazard may be cost-savings in the long run (e.g., 5 years out).

Next Steps Work with the CDHP to get actual consumer

web site behavior as substitutes and possible complements to the survey data.

Identify more opportunities to apply 3-stage conceptual model: I-net info knowledge demand.

Refine econometric model to identify other relationships between the CDHP web site use and demand for medical care as recorded in claims data.

Extend this work to more specific study populations in larger employers, particularly to subscribers with chronic illnesses and special medical needs.

For more information on our research

Please visit:

www.ehealthplan.org

Thank You!