Has Pharmaceutical Innovation Reduced Social Security Disability Growth?

Abstract

This paper analyzes longitudinal state-level data during the period 1995–2004 to investigate whether use of newer prescription drugs has reduced the ratio of the number of workers receiving Social Security Disability Insurance benefits to the working-age population (the “DI recipiency rate”). All of the estimates indicate that there is a significant inverse relationship between disability recipiency and a good indicator of pharmaceutical innovation use: the mean vintage (FDA approval year) of Medicaid prescriptions. From 1995 to 2004, the actual disability rate increased 30%, from 2.62% to 3.42%. The estimates imply that in the absence of any post-1995 increase in drug vintage, the increase in the disability rate would have been 30% larger: the disability rate would have increased 39%, from 2.62% to 3.65%. This means that in the absence of any post-1995 increase in drug vintage, about 418,000 more working-age Americans would have been DI recipients.

Key Words:

• Pharmaceutical
• Innovation
• Disability Social Security

JEL classifications:

• I1
• H5
• O3
• L65

Notes

1. Benitez-Silva et al. (2000) tested and were unable to reject the hypothesis that self-reported disability is similar to the information used by the Social Security Administration in making its award decisions. Their results indicate that disability applicants do not exaggerate their disability status at least in anonymous surveys such as the Health and Retirement Survey. Labriola and Lund (2007) found that information on self-reported days of sickness absence can be used to effectively identify “at risk” groups for disability pension.

2. Previous studies have used longitudinal, regional-level (state-or country-level) data to examine the impact of medical innovation and other factors on longevity and hospitalization rates; see Lichtenberg (2006a), Lichtenberg (2009), Lichtenberg (2010).

3. We will refer to this ratio as the DI recipiency rate.

4. There are two important aspects of program generosity: the probability that a person of given health status qualifies for benefits, and the benefits replacement rate.

5. The DI program provides benefits to disabled workers, their spouses, and children (whether or not disabled). In 2003, 86% of disabled beneficiaries were workers. Our measure of the DI recipiency rate excludes spouses and children.

6. Since N_DISAB_st / POP_st is bounded between zero and one, a linear model would not be appropriate.

7. The average price of Medicaid prescriptions ($69.40) was 8% higher than the average price of non-Medicaid prescriptions ($64.36).

8. There are currently about 46,000 products.

9. http://www.micromedex.com/products/redbook/ Therapeutic Group is an aggregation of Therapeutic Class values.

10. http://ssa.gov/policy/docs/statcomps/di_asr/2006/table 21.xls

11. Lichtenberg and Sun (2007) used data on all (Medicaid and non-Medicaid) prescriptions dispensed by a large retail pharmacy chain, but these data were only available for the period September 2004–December 2006.

12. The six therapeutic classes of drugs were: antidepressants, antihypertensives, cholesterol-lowering drugs, diabetic drugs, osteoporosis/menopause drugs, and pain management medications.

13. Data on FDA approval dates of new molecular entities (NMEs) from 1939 to 1998 were obtained via a Freedom of Information Act request to the FDA. Data on more recent NMEs and (beginning in 2004) new biologics were obtained from CDER Drug and Biologic Approval Reports (http://www.fda.gov/Cder/rdmt/default.htm). FDA approval dates of ingredients contained in about 15% of Medicaid prescriptions could not be determined.

14. For combination (multi-ingredient) products, we use the mean of the FDA approval years of the active ingredients.

15. http://www.fda.gov/Cder/rdmt/InternetNME08.htm

16. The measure of non-pharmaceutical cardiovascular disease innovation he used was the fraction of Medicare major cardiovascular surgical procedures with procedure codes established by the American Medical Association after 1990 or 1995.

17. Lichtenberg (2010) found that controlling for a measure of non-medical innovation – the fraction of state residents who used a computer at home – did not affect estimates of the effect of drug vintage on life expectancy.

18. Drug vintage is an indicator of the nature and perhaps quality of pharmaceutical treatment. Evaluation of the factors that affect (the probability of) treatment is often necessary to obtain unbiased estimates of treatment effects. See Dehejia and Wahba (2002).

19. When we estimate a linear model (in which the dependent variable is (N_DISAB / POP20_64)) rather than a probit model, the coefficient on ln(EMP_INDEX) is negative and highly significant.

20. Lichtenberg (2010) found that all three of these variables had significant negative effects on life expectancy.

21. In column 4, STD% is replaced by STD%_WITHIN.

22. We also estimated models that included measures of the vintage of drugs paid for by Medicare. These are primarily drugs administered by providers (e.g. chemotherapy) to elderly patients. Lichtenberg (2010) found that both Medicaid and Medicare drug vintage has a positive effect on life expectancy (at birth and at age 65). But the effect of Medicare drug vintage on disability in the working-age population is not statistically significant.

23. Estimates of the increase in the number of disabled workers in 2004 from each of the four drug vintage measures are as follows:

24. http://ssa.gov/policy/docs/statcomps/di_asr/2004/sect01c.html#table 20