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THE COLLATERAL HEALTH IMPACT OF SARS IN TAIWAN Daniel Bennett (University of Chicago) Chun-Fang Chiang (National Taiwan University) David Meltzer (University.

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Presentation on theme: "THE COLLATERAL HEALTH IMPACT OF SARS IN TAIWAN Daniel Bennett (University of Chicago) Chun-Fang Chiang (National Taiwan University) David Meltzer (University."— Presentation transcript:

1 THE COLLATERAL HEALTH IMPACT OF SARS IN TAIWAN Daniel Bennett (University of Chicago) Chun-Fang Chiang (National Taiwan University) David Meltzer (University of Chicago) June 29, 2012

2 Introduction  The SARS epidemic in 2003 lasted for 3 months and led to 312 confirmed cases and 82 deaths in Taiwan.  However, the health impact of the SARS epidemic is not limited to people infected with SARS.  Huge decline in both outpatient visits and inpatient visits. Any consequences of these missing visits?

3 Introduction  How many non-SARS deaths did SARS cause?  Which groups experienced greater mortality?  Any long run health impact due to missing hospital visits?

4 Context  National Health Insurance in Taiwan -- high coverage rate (96%) -- low copayments -- frequent hospital visits  SARS 2003 in Taiwan -- first case : 3/15 -- first big event: 4/23 -- first death case: 5/1 -- removed on WHO list : 7/ 3

5 Implications  Health impact due to panic/fear caused by infectious disease  Welfare analysis of health care system. ( If fewer visits do not worsen health, then health care services may be wasteful: shopping and and unnecessary visits )

6 Literature— Medical Care Utilization and Mortality  Less utilization  higher mortality -- Card, Dobkin and Maestas (2009) Medicare eligibility (65 years old); Sample: around age 65, admitted to hospitals through emergency departments nearly 1-percentage-point drop in 7-day mortality for patients -- Ken Chay (2012) Canada data --  Some studies find no effect: -- Finkelstein and McKnight(2008). Medicare in Generous insurance coverage : no effect  Most studies find some effects. Freeman (2008)

7 Literature— Changes during/after the SARS epidemic  Decline in outpatient and inpatient hospital visits  Admission rates for most chronic ambulatory-care sensitive conditions (ACS), except for diabetes, did not change after the SARS epidemic. (Huang, Lee and Hsiao)  Shifting childbirth services from advanced hospitals to local community hospitals during SARS epidemic did not increase neonatal mortality

8 Data  Population death records -- month of death, age, cause of death, township  BNHI panel of one million people -- outpatient and inpatient records ICD9 code, expenditure -- birthday, sex -- linked with death records (month of death) -- use the date out of the insurance in the same month to identify the date of death

9 The 2003 SARS Epidemic in Taiwan

10 Outpatient Visits: Ratio of 2003 to Other Years by Month

11 Inpatient Visits: Ratio of 2003 to Other Years by Month

12 Mortality: 2003 and

13 Mortality (age>=65)

14 Mortality (age<65)

15 Alternative Explanations  Economic Shocks -- unemployment rate didn’t increase -- less activity  less mortality (Evans and Moore 2009)  Psychological shocks -- compare the pattern and changes in mortality after SARS with these after 921 earthquake

16 Psychological shocks  921 Earthquake happened on Sep, 21 in  Number of deaths: 2415  Mortality from diseases, however, did not increase

17 Mortality for all causes of death 2003 v.s avg v.s. 1999

18 Mortality (disease or natural death)

19 Analysis using Population Death Data  Sample: Monthly mortality from 1999 to 2008  Specification: Include month fixed effects & year fixed effects to estimate the changes in mortality

20 Table 1: Changes in Mortality during 2003 SARS period Dependent variable:Non-SARS Mortality ( by thousand) Category:AllOLDYoung (1) (2)(3) March (0.0187)(0.1401)(0.0089) April (0.0187) (0.1401)(0.0089) May **0.4053*** (0.0187)(0.1401)(0.0089) June (0.0187)(0.1401)(0.0089) July (0.0187)(0.1401) (0.0089) Month fixed effectsYes Year fixed effectsYes R-squared

21 Analysis using Population Death Data From column (1), 1042 non-SARS extra deaths in May 2003 (Population 2003: 22,604,548; 129,878 dead) From column (2), 842 non-SARS extra deaths among old people in May 2003 (Pop: 2,087,718, 85,778 dead ) SARS death cases: 82

22 Analysis using NHI one million panel  If missing inpatient hospital visits were responsible for more deaths, we should observe that more deaths from people with higher medical demand.  Time series analysis by group (first look)  Survival analysis using individual data

23 Analysis I  Group 1: High Medical Demand: # Hospital visits > 11 or hospital stay > 7 days in 2002  Group 2: Low Medical Demand:  Sample: Mortality by week and group starting from 2003

24 Table 2: Mortality by history of hospital visits Dependent variable:Mortality ( t ) Category:OldYoungGroup H Group L (1)(2)(3) (4) Week9* Week10* Week11* Week12* * * 0.01 Week13* * ** Week14* * Week15* Week16* * Week17* Week18* Week19* ** ** Week20* Week21* ** * Week22* Week23* Week24* Week25* Week26* Sample size R-squared

25

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27 Change in mortality by disease  Cancer v.s. Diabetes

28 Findings regarding short run effects  While 82 people died of SARS in Taiwan, we find that the epidemic is associated with around 1000 additional non-SARS deaths.  The health impact is larger among the elderly and those with higher medical demand than others.  Differential effects by disease

29 Did missing visits cause any long term impacts?  Conditional on being alive after SARS, we would like to estimate the long term impacts of missing visits.  Empirical difficulty: One’s hospital visiting frequency is related with one’s health condition. Those who has decreasing visits could be getting healthier.

30 Did missing visits cause any long term impacts?  Empirical Strategy: Using instrument variable: Changes in hospital visits of the patient’s hospital  Sample: one million panel Those who had at least one hospital visit from 2003/ /3 & survived the Sars epidemic

31 Specification I

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34 Specification II

35 Effects by disease  Some preliminary findings: -- The long run pattern is different from the pattern of short run effects -- larger impacts on cancer patients, and smaller impacts on diabetes patients. -- The impacts was smaller in later years

36 Conclusions  We find that SARS epidemic causes more non-SARS deaths than SARS deaths during the SARS epidemic.  We also find that missing hospital visits had long term impacts on those who avoid hospital visits.


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