patient cost-sharing and healthcare utilization in early childhood: evidence from a regression...

Patient Cost-Sharing and Healthcare Utilization in Early

Childhood: Evidence from a Regression Discontinuity Design

Department of Public Finance, NCCU

Hsien-Ming Lien

Motivations

Investment in health in early childhood is widely believed to have a substantial impact in adulthood (Currie, 2009 ; Currie, 2000; Case and Paxson, 2005; Currie and Madrian, 1999)

In light of that, some countries have subsidized medical care for young children by reducing cost-sharing US: providing children (under 14) the health overage

through Children Health Insurance Program Japan: reducing the copayment for young children (aged

less than 6) by 50%. Taiwan: waived the copayment of national health

insurance for young children (aged less than 3)

Motivations

While these programs are generally well received, it remains unclear to what extent young children can benefit from the subsidy on cost-sharing. Do young children obtain more health care in face

of a lower demand price? If yes, is there evidence showing their health

improves after the increase of medical use?

Understanding the magnitude of price elasticity for young children is essential to evaluate these subsidy programs

Previous Literature

Estimates on the price elasticity of health use still relies on results from the Rand Health Insurance Experiment (HIE), a social experiment conducted between 1977 and 1982 that randomly assigned enrollees to insurances of different levels of cost-sharing (from free care (0%) to full cost (95%)) to mitigate the concern of endogenous patient cost-sharing.

HIE findings The health expenditure increases about 50% from the full

cost to the free care coverage The demand elasticity for adults is about -0.2, and -0.1 for

children (under 14). No precise estimates is provided for young children given

the small sample size.

Previous Literature

Davidoff (2005) used the SCHIP program expansion to estimate the use of health care for children (under 14). Results indicate that children of chronic conditions increased their use after obtaining the public coverage, though none of estimates are statistically significant

Several recent studies have used the quasi-experimental design to examine the effect of cost-sharing on the health care for adults and the elderly (Chandra, 2010a; Chandra, 2010b; Chandra, 2012; Hitoshi, 2013), but none of them focused on the young children.

But even the estimates of price elasticity for young children is available, these numbers might not be applicable to other Asian countries The average number of outpatient visits per year

in Asian countries is generally much larger than that in the states.

Taiwan (16, 2004), Japan (17.3, 2003), Korea (11, 2002) U. S. (8.9, 2003)

Research Question

How does a lower cost-sharing affect health use of young children?

Moreover, does the health use of young children respond differently to cost-sharing with respect to Income groups Types of services (e.g. outpatient vs inpatient) Types of diseases (e.g. acute care vs mental

illnesses)

Identifications

We exploit a sharp change in cost-sharing at age 3 in Taiwan, due to Taiwan Children Medical Subsidy Program (TWCMS).

TWCMS covers all the co-payments of medical use for children under 3, but the subsidy stops once a child reaches his 3rd birthday.

The price variation around the 3rd birthday allows us to use a regression discontinuity design (RDD) to examine the causal effect of cost sharing by comparing the spending and use of health care for young children right before and after the 3rd birthday

Change in Cost Sharing at the 3rd Birthday (Outpatient)

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-180 -150 -120 -90 -60 -30 0 30 60 90 120 150 180Age at visits (days from 3rd birthday)

Change in # of Visits at the 3rd Birthday (Outpatient)

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Change in Expenditure at the 3rd Birthday (Outpatient)

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Background: Patient Cost Sharing (I)

Major Teaching Minor Teaching Community ClinicHospital Hospital Hospital

Table 1:

Patient Cost-SharingPatient Cost-Sharing in Taiwan NHI

Panel A:Outpatient service: copayment (NT$)NHI Copay 360 240 80 50Register Fee 150 100 100 50Panel B:Emergency room service: copayment (NT$)NHI Copay 450 300 150 150Register Fee 300 150 100 80

Panel C:Inpatient service: coinsruance1-30 days31-60 daysafter 61 days

10%20%30%

Background: Patient Cost Sharing (II)

Outpatient care Fixed co-payment and registration fee Its amount varies with respect to types of providers. In

general, a better provider charge a higher copayment and registration fee

Inpatient care Fixed coinsurance rate The coinsurance rate depends on the length of stay, but

not the types of health providers. NHI has a annual maximum out-of-pocket expense

(stop-loss) for inpatient admissions (NT52000 in 2012) No deductibles for NHI

Background: Taiwan Children Medical Subsidy Program

In March 2002, the TWCMS was implemented for the following purpose: Reduce the economic burdens of parents Increase the health care use of children Improve the children’s health

TWCMS each year spent NT1.8 billons for children aged below three on cost sharing Co-payment for outpatient and emergency care

(but not the registration fee) Co-insurance rate for inpatient care

A child is no longer eligible for this subsidy program once reaching his/her 3rd birthday

Data

We use claims data from Taiwan's National Health Insurance Database (NHID) NHI is compulsory so NHID covers all individuals in

Taiwan Claim records of inpatient, outpatient and emergency

care use Detailed information about cost-sharing, health care

use and medical expenditure More importantly, our data record the exact date of

outpatient visits, inpatient admissions, and children’s birthdays. Therefore, we can precisely measure when the children are eligible (in days) for subsidy program, essential for RD design

Data

Our sample restricts to children born between 2003 and 2004. We track their health care use from the first day after 2nd birthday to the first day of 4th birthday (2*365 days). Thus, we use NHID data between 2005 and 2008. TWCMS was implemented in 2002. There is a change in the reimbursement rate in 2009

for young children. We exclude

Dental services and Chinese medicine, focusing on Western Medicine

Health checks provided free by NHI Children who enrolled into NHI for only one year Already waived from cost-sharing (e.g. indigenous

families)

Children Characteristics After Sample Selection

(1) (2) (3)Original Sample Continuous enrollment Eliminating

at age two and three cost-sharing waiver

Male Birith year: 2003 Birith year: 2004 1st birth 2nd birth 3rd birth (above) Number of siblings

Number of children

Selected characteristics at age three before and after sample selectionTable2:

0.5250.5100.4900.5190.3680.1131.761(0.671)435,206

0.5250.5090.4910.5200.3700.1121.760(0.671)426,587

0.5240.5090.4910.5200.3700.1101.759(0.669)410,517

Sample Statistics of Health Care Use

Before After Before After3rd birthday 3rd birthday 3rd birthday 3rd birthday

UtilizationAverage annual visits Average out-of-pocket cost per visit (NT$)Average medical expenditure per visit (NT$)Choice of providersMajor Teaching Hospital Minor Teaching Hospital Community Hosptial Clinic Number of children (visits > 0)Number of children-visit

Outpatient care Inpatient careDescriptive Statistics

Table3:

19.8 1958.9 123.1443.5 438.7

4.1% 2.3%5.6% 3.7%3.8% 4.6%86.5% 89.4%

375,493 364,0752,003,097 1,954,591

0.14 0.130 1289.7

12980.6 13013.9

28.7% 29.8%58.6% 58.2%12.8% 11.9%

0% 0%13,252 12,66619,356 18,163

Empirical Specification

We estimate the following RD regression:

is the outcome of interest for the child i outpatient visits or inpatient admissions total spending on outpatient or inpatient care

is an indicator equaling to one if i is age 3 or older is smooth function of age with parameter vector

that accommodate the age profile of outcome variables is an error term that reflects all other factors

affecting outcome variables represents the causal effect of cost sharing on

children‘s health care spending and use

Empirical Specification Problems (I)

A large portion of children do not have health care use with a short period of time Many zeros result in a huge problem in the

estimation (e.g. cannot take log) In the health literature, two-part model is

proposed to deal with the problem of many zeros. Here, we collapse the health care use of all

children in the sample together so that we can measure the health care use by days

Empirical Specification Problems (II)

Children might visit doctors more in face of the ending of subsidy program Check if our estimates are robust when dropping

points very close to the 3rd birthday

Change in # of Visits at the 3rd Birthday (Outpatient)

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520

540

560

580

600

Out

patie

nt v

isits

per

10,

000

per

son

yea

rs


Empirical Specification Problems (III)

Separate the sharp jump from non-linear functional forms

Lee and Lemieux (2010) suggests two ways to estimate parameters of interest in RD design polynomial regression: estimating age profile using all of

available data and a parametric function (e.g., 3th order polynomial)

local linear regression: estimating the age profile over a narrower range of data (choosing specific bandwidth) by using linear regression

We will use local linear regression as the main specification, and global polynomial regression as the robustness check

Results: Outpatient Visits and Spending

(1) (2) (3) (4)Specication Nonparametric Parametric Nonparametric Parametric

Local linear Cubic spline Local linear Cubic spline

Visits rate at age 2(per 10,000 person-years)Bandwidth (days)

Panel A:Log( outpatient expense)After 3rd birthday (X100) Panel B:Log(number of visits)After 3rd birthday (X100) Panel C:Log(outpatient expense per visit)After 3rd birthday (X100)

2005-2008 1997-2001Change at 3rd birthday in Outpatient Visits and Spending: before and after reform

Table4:

542 90 365

-6.63*** -6.79*** [0.44] [0.40]

-4.54*** -4.67*** [0.32] [0.29]

-2.12*** -2.12*** [0.26] [0.27]

568 90 365

0.17 0.36 [0.24] [0.21]

0.26 0.24 [0.17] [0.17]

-0.04 0.11 [0.11] [0.13]

Change in Outpatient Expenditure for Young Children

Change in the Number of Visits for Young Children

Average Expenditure Per Visit for Young Children

(1) (2) (3) (4)Specication Baseline Different Different Donut

Bandwidth Kernel RDBandwidth (days) 90 180 90 90Kernel function triangular triangular unifrom triangularPanel A:Log( outpatient expenditure)After 3rd birthday (X100) -6.63*** -5.97*** -6.61*** -6.26*** [0.44] [0.31] [0.38] [0.82]Panel B:Log(number of visits)After 3rd birthday (X100) -4.54*** -3.78*** -4.52*** -4.90*** [0.32] [0.22] [0.28] [0.45]Panel C:Log(outpatient expense per visit)After 3rd birthday (X100) -2.12*** -2.19*** -2.09*** -1.36**

[0.26] [0.21] [0.27] [0.60]

Robustness Check for Outpatient Expenditure and VisitsTable 12:

Robustness Checks

Summarized Results

The estimated arc-elasticity for outpatient care Health spending: -0.10 Health visits: -0.06

Average expenditure per visit also dropped for 2%, after the end of subsidy. But why? The subsidy program encourages the children to

go to teaching hospitals for ordinary diseases.

(1) (2) (3) (4) (5)All Major teachingMinor teaching Community Clinic

hospital hospital hospitalPanel A: Outpatient visitVisits rate at age 2 542 22 30 21 469(per 10,000 person-years)Log(number of visits)After 3rd birthday (X100) -4.54*** -57.64*** -44.03*** 18.97*** -1.61***

[0.32] [2.40] [1.47] [1.48] [0.26]Log(outpatient expense per visit)After 3rd birthday (X100) -2.12*** 19.07*** 7.13*** -0.75 -0.18**

[0.26] [2.34] [1.75] [1.56] [0.09]Panel B:Emergency room visitVisits rate at age 2(per 10,000 person-years)Log(number of visits)After 3rd birthday (X100)

Log(outpatient expense per visit)After 3rd birthday (X100)

Providers

Change at 3rd birthday in Outpatient Visits and Spending: By choice of providersTable5:

16 6 8 2 0

-5.31*** -9.48*** -12.57*** 32.09*** [1.49] [2.46] [1.58] [3.97]

0.52 0.95 2.24* -3.13 [0.66] [1.64] [1.33] [2.40]

Change in # of Visits for Young Children by Providers

Table7:

(1) (2) (3) (4)Specication Nonparametric Parametric Nonparametric Parametric

Local linear Cubic spline Local linear Cubic spline

Visits rate at age 2(per 10,000 person-years)Bandwidth (days)

Panel A:Log(inpatient expense)After 3rd birthday (X100) Panel B:Log(number of admission)After 3rd birthday (X100) Panel C:Log(inpatient expense per admission)After 3rd birthday (X100)

2005-2008 1997-2001Change at 3rd birthday in Inpatient Expenditure and Admissions: before and after reform

3.9

90 365

-0.11 -1.20 [2.78] [2.41]

-0.10 0.74 [5.15] [4.00]

0.01 0.19 [3.45] [3.03]

2.5

90 365

1.14 3.21 [2.38] [2.20]

1.36 2.72 [2.89] [3.13]

0.04 -0.04 [2.36] [2.48]

Summarized Results

The estimated arc-elasticity is insignificant for inpatient care Admissions: -0.0005 Expenditure: -0.0005

In other words, the demand of inpatient care for young children barely responds to the change of cost sharing

Heterogeneous Treatment Effect

The treatment effect could vary with respect to Gender Birth order Household incomes Diseases

and gender(1) (2)

Visits rate at age 2 Log of visits

(per 10,000 person-years)

Panel B: By birth order1st birth 2nd birth (above) Panel C: By genderMale Female Panel D: By household incomeLow High

Change at 3rd birthday in Outpatient Visits : By diagnoses, household income, birth order,Table6:

535 -4.15*** [0.37]

549 -4.95*** [0.40]

570 -4.68*** [0.35]

511 -4.29*** [0.51]

525 -5.23*** [0.38]

562 -3.77*** [0.43]

(1) (2)Visits rate at age 2 Log of visits

(per 10,000 person-years)Panel A: By visit diagnosesURI 119 -1.89*** [0.53]Skin diseases 20 -11.82***

[1.18]Mental disorder 4 -23.61*** [2.80]Preventive care 2 -33.28*** [5.47]

come, birth order, and genderChange at 3rd birthday in Outpatient Visits and Spending: By diagnoses, in-

Table6:

Conclusion

Our study is the first one to identify the demand elasticity of health care for young children.

Our results show The price elasticity for outpatient expenditure is

about -0.1. The price elasticity for outpatient visit is about -0.06. The price elasticity for inpatient service is very small,

almost zero The price elasticity for preventive care or mental

illness is quite large while that for URI is small. Further work

The long term health effects