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 1965-1975 -- 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 2000-2002

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 1999.  Number of deaths: 2415  Mortality from diseases, however, did not increase

17. Mortality for all causes of death 2003 v.s. 2000-2002avg 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 2003 -0.00510.0020-0.0054 (0.0187)(0.1401)(0.0089) April 2003 0.0061 0.02740.0037 (0.0187) (0.1401)(0.0089) May 2003 0.0455**0.4053***0.0088 (0.0187)(0.1401)(0.0089) June 2003 0.00960.02750.0074 (0.0187)(0.1401)(0.0089) July2003 0.00590.01090.0056 (0.0187)(0.1401) (0.0089) Month fixed effectsYes Year fixed effectsYes R-squared0.81 0.820.37

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*20030.049-0.0040.027 -0.0181 Week10*2003-0.021-0.0080.012 -0.041 Week11*20030.135-0.0060.048 -0.001 Week12*20030.154*0.0250.061* 0.01 Week13*20030.162*-0.0000.077** -0.017 Week14*20030.160*-0.0110.010 0.026 Week15*20030.008-0.0090.038 -0.049 Week16*20030.0080.01870.056* 0.039 Week17*20030.053-0.0060.050 -0.004 Week18*20030.0320.0010.018 0.01 Week19*20030.183**0.0080.098** 0.011 Week20*20030.0490.0090.017 -0.001 Week21*20030.191**-0.0070.055* 0.043 Week22*20030.1080.0110.046 0.011 Week23*20030.011-0.0010.005 0.012 Week24*20030.021-0.002-0.003 -0.008 Week25*20030.034-0.0020.034 -0.017 Week26*2003-0.0510.0090.025 -0.015 Sample size360 240 R-squared

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 2003/1 -2003/3 & survived the Sars epidemic

31. Specification I

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.