THE IMPACT OF GLOBAL BUDGETING ON TREATMENT OUTCOMES

1

THE IMPACT OF GLOBAL BUDGETING ON TREATMENT OUTCOMES

Kanhom KanShu-Fen Li Wei-Der Tsai

2

Objective of this studyInvestigate the impact of global budgeting on

treatment outcome.

Motivation:1. The rapid increase in health care expenditure

since the 1960s has become a great concern to policy makers in most developed countries.

2. Global Budgeting is effective in controlling medical expenditures and it was adopted in OECD countries (see Docteur and Oxley, 2004, and Wolfe and Moran, 1993).

3

Figure 1 Comparison of per capita NHE between OECD Countries and Taiwan

0

500

1,000

1,500

2,000

2,500

3,000

3,500

4,000

4,500

5,000

5,500

6,000

6,500

7,000

7,500

8,000

0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 90,000

NHE( )平均每人美元

GDP( )平均每人美元

Taiwan

Norway

Japan2006

IcelandDenmark

Sweden Ireland

FinlandUnited Kingdom

AustriaCanada

Belgium

Australia2006

ItalyGreece

France

New Zealand

Spain

KoreaCzech Republic

HungarySlovak Republic

Portugal2006

Turkey2005

Poland

Germany

Mexico

Netherlands

Data Source： OECD Health Data 2009

4資料來源：中央健保局

Figure 2 The Growth of NHI Revenues and Expenditures

5

Literature Review Most relative research focus on the provider’s

behavior responses (quantity and quality) to global budgeting:

A. Theoretical Prediction:1. Phelps (1997) and Fan, et al. (1998) show that

medical service providers will increase the quantity of services supplied.

2. Benstetter and Wambach’s (2006) suggest that there is likely to be a coordination failure such that medical service providers will supply a high quantity of services in order to achieve a target income and prevent bankruptcy (the so-called “treadmill effect”).

6

Literature Review (Cont)A. Theoretical Predictions:3. Based on the assumption of monopolist and Cournot

competitive market, Mougeot and Naegelen (2005) suggest that compared with FFS, an expenditure cap results in a lower level of service quantity and quality.

4. Feldman and Lobo’s (1997) assume that medical service providers’ utility is a function of services quantity and quality. Their model indicates that the excess demand which is prevalence under global budget systems is due to the high level of resource intensity chosen by service providers.

7

Literature Review (Cont)B. Empirical Evidence: 1. Rochaix (1993) show in response to an expenditure

cap, physicians in Québec increase their activity levels, and provide more complex and high-priced procedures.

2. Similar results found by Hurley et al. (1997) [cases

of Alberta and Scotia Nova in Canada] and Lee and Jones (2004) [case of Taiwan’s dentists].

3. Chen et al. (2007) and Cheng, et al. (2009) show that hospitals in Taiwan are more likely to hospitalize patients under global budgeting.

8

The literature is silent on the issue that whether the implement of global budgeting has an impact on quality or treatment outcome.

Using the data of Taiwan’s National Health Insurance claim records in 1998-2007, we examine the effect of global budgeting on treatment outcomes of AMI (acute myocardial infraction), ischemic stroke and hemorrhagic stroke patients.

The treatment outcome is measured by inpatient readmission within 30 days, and the rate of 7, 14, 30, 60 and 90 days post-discharge mortality.

9

Background of Taiwan’s NHINational Health Insurance (NHI) was

implemented in March of 1995.NHI provides patients with comprehensive care,

but only requests low out of pocket expenditures. Payment system started from FFS in 1995, but

changed to global budget system sector by sector. 1998/7 Dental services2000/7 Chinese Medicine2001/7 Community clinics in 20012002/7 Hospital services 2010/1 DRG for hospital inpatient services.

10

Background of Taiwan’s NHI (cont)Under FFS, a providers is credited a certain

point for each treatment procedure offered and each point is worth NT$ 1.

Under global budgeting system, there is a regional level expenditure cap. Taiwan was divided into six medical regions. The point value for a given region is determined as follows

11

Figure 3 Medical Region in Taiwan

12

13

Figure 4 Health Care Expenditures Funded by NHI

14

Figure 5 Point Value

15

Figure 6 Treatment Intensity by Average Number of Points per in-patients

16

Figure 7 Treatment of AMI Patients

17

Data DescriptionClaim record form the 1998-2007 Claim File

of Taiwan’s NHI.

The claim record contain information both on hospitalized patients’ and hospitals’ characteristics.

We use the claim data to construct three samples, including AMI (acute myocardial infraction, ICD 410), ischemic stroke ( ICD 434) and hemorrhagic stroke (ICD 430 & 431)patients.

18

Data DescriptionSome criteria are imposed to exclude observations.

(a) admitted to hospitals due to same ICD code in

previous year;(b) hospitalized for more than 30 days;(c) admitted to a hospital, which treated less than

300 cases in the past 10 year;(d) younger than 30 or older than 80. (e) hospitalized during June, July and August of 2002. There are total 63,142, 238,810 and 99,907 patients,

respectively, for AMI, Ischemic stroke and hemorrhagic stroke in 1998-2007.

19

Year Readmission

Within 30 days

discharge

Sample size

Mortality within 7

days after discharge

Mortality within 14 days after discharge




Sample Size

1998 .093 4,779 .186 .197 .210 .222 .230 6,054

1999 .091 5,500 .188 .199 .209 .221 .233 6,950

2000 .092 6,045 .169 .177 .189 .202 .212 7,455

2001 .092 6,582 .177 .184 .194 .207 .217 8,171

2002 .073 7,167 .160 .167 .178 .192 .202 8,723

2003 .065 7,496 .158 .166 .177 .190 .200 9,105

2004 .071 8,319 .158 .163 .173 .187 .197 10,057

2005 .063 8,749 .150 .155 .166 .176 .186 10,487

2006 .054 9,120 .143 .149 .158 .171 .179 10,827

2007 .048 9,904 .122 .127 .134 .144 .151 11,431

Mean value of treatment outcome for AMI patients

20

Year ReadmissionWithin 30

days discharge

Sample size

Mortality within 7






Sample Size

1998 .069 20,325 .054 .061 .070 .084 .094 21,907

1999 .069 22,008 .054 .059 .069 .081 .091 23,684

2000 .068 23,916 .048 .054 .062 .075 .085 25,581

2001 .069 26,019 .047 .051 .060 .072 .081 27,779

2002 .067 27,352 .043 .048 .056 .067 .077 29,069

2003 .056 26,550 .043 .048 .056 .068 .077 28,247

2004 .065 27,947 .041 .045 .052 .064 .073 29,700

2005 .058 28,513 .042 .046 .054 .064 .073 30,349

2006 .059 30,235 .040 .043 .051 .061 .068 32,054

2007 .057 28,814 .036 .039 .044 .050 .057 30,352

Mean value of treatment outcome for Ischemic Stroke patients

21

Year ReadmissionWithin 30

days discharge

Sample size

Mortality within 7






Sample Size

1998 .116 4,729 .276 .290 .306 .317 .324 6,857

1999 .129 5,040 .286 .298 .310 .321 .326 7,340

2000 .131 5,593 .280 .290 .300 .311 .317 8,044

2001 .133 5,749 .279 .289 .299 .309 .316 8,258

2002 .135 5,769 .276 .285 .293 .304 .310 8,225

2003 .109 5,813 .276 .284 .293 .302 .308 8,280

2004 .127 6,141 .277 .283 .291 .300 .305 8,781

2005 .116 6,294 .278 .282 .289 .296 .302 8,979

2006 .113 6,104 .270 .275 .281 .288 .293 8,627

2007 .108 5,884 .248 .253 .259 .265 .267 8,044

Mean value of treatment outcome for hemorrhagic stroke patients

22

Empirical Strategy Linear probability model:

Where subscribe d index calendar dates, h and i index, respectively, the hospital and the patient; yhid an outcome of interest; GBd global budgeting indicator; trendd year trend, Xhid a vector of patient characteristics (i.e., CCI score, age, gender); ηh hospital fixed effect; εhid residuals.

23

Empirical Strategy (cont) To have a preliminary examination of the effect of GB on patient

outcome, we first estimate a fixed effects model without GBd :

We employ a nonparametric smoothing method, call local polynomial

(Fan and Gijbels, 1996), to display the predicted residual

Where g = 0, 1 indicating the pre- and post-global budgeting periods.

24

25

26

27

Empirical Strategy (cont)The graphs indicate that the pattern of the

time trend is the residuals before and after the implementation of GB are different.

To incorporate the effect of time on the readmission and mortality of AMI and stroke patients, we estimate the following specification model

28

Empirical Results

29

Empirical Results (cont)

30

Empirical Results (cont)

31

Conclusion Our estimation results suggest that global

budgeting has some effects on post-discharge readmission and mortality for for-profit hospitals.

Our empirical results suggest that global budgeting leads to an improvement in treatment outcomes for for-profit hospitals. For AMI patients, GB reduces post-discharge readmission by 1.67%, and 7 and 14 days post-discharge mortality by approximately 2%. For hemorrhagic stroke patients, GB reduces the 14, 30 and 60 days post-discharge mortality by 0.0195-0.0233.

Documents

THE IMPACT OF GLOBAL BUDGETING ON TREATMENT OUTCOMES