1. Are Women’s Health Concerns Prioritized at the NIH and the FDA? Nicole C. Quon, Ph.D. Assistant Professor Indiana University

2. Scientific Agencies Scientific agencies use scientists and scientific evidence to make science policy Scientific agencies use scientists and scientific evidence to make science policy Likely to seek bureaucratic autonomy Likely to seek bureaucratic autonomy May respond to external pressure under certain conditions May respond to external pressure under certain conditions

3. Women’s Health Movement Relied on frames of gender inequity Relied on frames of gender inequity Concerns about medical research Concerns about medical research –Increasing attention to women’s health –Participation of women in clinical trials –Research funding for women’s health issues, especially breast cancer

4. Mobilizing Resources MeanRange General women’s health groups 7.5 2 – 14 Disease-specific women’s health groups 1.1 0 – 9 Other disease-specific groups 5.0 0 – 56 National Women’s Health Network budget ($1000) 401.8 0 – 743 Scientific agencies may consider the demands of resource-rich groups Scientific agencies may consider the demands of resource-rich groups

5. Raising Awareness MeanRange Congressional oversight index (alpha=0.62) 17.8 0 – 42 Media coverage index (alpha=0.91) 21.40-277 Scientific journal articles 331.1 0 – 3467 Scientific agencies may respond to signals of issue importance Scientific agencies may respond to signals of issue importance Political/social influence vs. scientific influence Political/social influence vs. scientific influence

6. Reducing Monitoring Costs MeanRange Women in senior NIH positions 3.6 0 – 9 Women in NIH study sections (% change) 0.8 -1.8 – 5.2 Administrative procedures Administrative procedures –Introduce decision makers who share the same values

7. Gender Politics MeanRange Women in Congressional committees (%) 6.5 1.0 – 16.7 Positive gender gap in Presidential election (%) 1.7 0 – 11 Negative gender gap in Presidential election (%) -4.9 -10 – 0 Partisanship in Congress 1.1 0.9 – 1.4 Issues related to gender may become more salient under certain conditions Issues related to gender may become more salient under certain conditions

8. Disease Burden MeanRange Hospital admission rate for women 1427.8 1153 – 1960 Overall death rate for men 94.5 85 – 109 Prevalence rate for women 982.0 0 – 7660 Disease-specific death rate for men 3.0 0 – 42 Agency missions reflect public health goals Agency missions reflect public health goals Rate for women or men could influence priority setting Rate for women or men could influence priority setting

9. NIH Dependent Measures Related to decisions in the NIH grants program Related to decisions in the NIH grants program –Grants for “women or female” studies  Extramural program (n=556)  Intramural program (n=418) –Grants for studies on 23 diseases on the women’s health agenda  Extramural program (n=749)  Intramural program (n=660) Collected from the CRISP database of funded grants from 1972 to 2004 Collected from the CRISP database of funded grants from 1972 to 2004 Keyword searches of grant titles and abstracts Keyword searches of grant titles and abstracts

10. NIH Independent Variables Mobilization of resources Mobilization of resources Raising awareness Raising awareness Reducing monitoring costs Reducing monitoring costs Gender politics Gender politics Disease burden Disease burden Other variables Other variables –Female medical school faculty, year trend, presidential dummies

11. NIH Model Specification Count data Count data –Data was overdispersed –Data was a panel design  32 years  23 institutes or 23 diseases Random effects negative binomial models Random effects negative binomial models Offset to account for varying institute sizes Offset to account for varying institute sizes Lagged independent variables Lagged independent variables

12. NIH Extramural Priorities Models Studies on Women or Females Studies on 23 Disease Priorities Coeff.S.E.Coeff.S.E. Mobilizing Resources General women’s health groups -0.00130.0108-0.0811*0.0470 Disease-specific women’s health groups ---0.1457***0.0213 Other disease-specific groups --0.0471***0.0041 National Women’s Health Network budget 0.00030.0003-0.00030.0003 Raising Awareness Congressional oversight On women’s health On women’s health0.00170.00180.0075***0.0018 On specific disease On specific disease0.0132**0.0060 Media coverage -0.00030.00030.0040***0.0008 Scientific journal articles -0.00020.0002-0.0003***0.0001 * p<0.10, ** p<0.05, *** p<0.01

13. NIH Extramural Priorities Models Studies on Women or Females Studies on 23 Disease Priorities Coeff.S.E.Coeff.S.E. Reducing Monitoring Costs Women in senior NIH positions 0.0319*0.01680.02700.0174 Women in NIH study sections 0.00630.0172-0.01630.0117 Political Salience Women in Congressional committees 0.02150.02240.0389**0.0189 Positive gender gap in Presidential election 0.0252*0.01500.0325***0.0096 Negative gender gap in Presidential election 0.00200.0150-0.0159*0.0093 Partisanship in Congress -0.04490.25350.21020.1823 * p<0.10, ** p<0.05, *** p<0.01

14. NIH Extramural Priorities Models Studies on Women or Females Studies on 23 Disease Priorities Coeff.S.E.Coeff.S.E. Disease Burden Hospital admission rate for women -0.00010.0001 Hospital admission rate for men 0.00030.0002 Overall death rate for women 0.01850.0246 Overall death rate for men -0.05010.0358 Prevalence rate for women 0.0001***0.0000 Prevalence rate for men -0.00010.0001 Disease-specific death rate for women -0.1570***0.0151 Disease-specific death rate for men 0.1497***0.0126 * p<0.10, ** p<0.05, *** p<0.01

15. NIH Intramural Priorities Models Fewer influences seem to matter compared to extramural program decisions Fewer influences seem to matter compared to extramural program decisions Studies on women or females Studies on women or females –Gender politics: negative gender gap Studies on 23 disease priorities Studies on 23 disease priorities –Mobilizing resources: other disease-specific groups –Raising awareness: congressional oversight on specific diseases –Disease burden: death rate for men

16. FDA Dependent Measures Related to decisions for new drug approval Related to decisions for new drug approval –Assignment of “priority” review –Speed of new drug review in months Approval dates from 1970 to 2004 Approval dates from 1970 to 2004 Focused on drugs approved for diseases on the women’s health agenda (n=131) Focused on drugs approved for diseases on the women’s health agenda (n=131)

17. FDA Independent Measures Mobilizing of resources Mobilizing of resources –Interest groups Raising awareness Raising awareness –Congressional oversight, media coverage, scientific articles Disease burden Disease burden Other variables Other variables –FDA workload, previous firm success, PDUFA

18. FDA Model Specification Logistic regression to examine assignment of priority review Logistic regression to examine assignment of priority review Proportional hazards regression to examine the speed of drug review Proportional hazards regression to examine the speed of drug review

19. FDA Priorities Models Priority Review Drug Review Times Coeff.S.E.Coeff.S.E. Mobilizing Resources Disease-specific women’s health groups 0.19630.2049-0.08170.0734 Other disease-specific groups 0.01910.09280.02590.0178 Raising Awareness Congressional oversight on specific diseases -0.73530.64610.02130.0906 Media coverage 0.09690.5312-0.03250.1793 Scientific journal articles 0.10760.06570.0229***0.0081 * p<0.10, ** p<0.05, *** p<0.01

20. FDA Priorities Models Priority Review Drug Review Times Coeff.S.E.Coeff.S.E. Disease Burden Prevalence rate for women -0.00070.00100.00020.0003 Prevalence rate for men -0.00390.00370.00000.0002 Disease-specific death rate for women -0.54681.21300.13100.1259 Disease-specific death rate for men -2.4601*1.4444-0.10570.1128 Priority rating ----1.4061***0.3556 Other Variables FDA workload -0.02702.0056-0.57280.6231 Previous firm success 0.27180.77080.31450.3401 PDUFA trend -0.02080.11900.08710.0456 * p<0.10, ** p<0.05, *** p<0.01

21. Summary of Main Results The FDA was responsive to the women’s health movement The FDA was responsive to the women’s health movement But not in priority setting for new drug approval But not in priority setting for new drug approval Female leadership (scientific and political) are associated with increased priority setting at the NIH Female leadership (scientific and political) are associated with increased priority setting at the NIH Congressional oversight and some signals from health advocates are also important Congressional oversight and some signals from health advocates are also important

22. Study Limitations NIH dependent measures collected using keywords NIH dependent measures collected using keywords Data on grant applications unavailable Data on grant applications unavailable Women’s health advocacy measure is crude Women’s health advocacy measure is crude Few drugs for diseases on the women’s health agenda Few drugs for diseases on the women’s health agenda

23. Policy Implications Scientific agencies are not insulated from gender politics Scientific agencies are not insulated from gender politics Influence depends on the type of decision and agency culture Influence depends on the type of decision and agency culture Some pathways of influence seem more effective Some pathways of influence seem more effective –Collaborations between interest groups and Congress –Increasing the role of women leaders

25. Pathways of External Influence “External signals” theory “External signals” theory –Josckow, Olson –Mobilizing resources –Raising awareness “Political control” theory “Political control” theory –Weingast and Moran, McNollGast, McCubbins and Schwartz –Reducing monitoring costs Political salience Political salience

26. Agency Mandates and Culture Research scientific agencies Research scientific agencies –NIH intramural grants program Distributive scientific agencies Distributive scientific agencies –NIH extramural grants program Regulatory scientific agencies Regulatory scientific agencies –FDA Center for Drug Evaluation and Research

27. NIH Independent Variable Lags Agencies respond to most recently available information Agencies respond to most recently available information 1 year lag: Congressional oversight, media, and scientific journal coverage 1 year lag: Congressional oversight, media, and scientific journal coverage 2 year lag: interest groups 2 year lag: interest groups 3 year lag: disease burden 3 year lag: disease burden

28. Grants for Women's Health Agenda Diseases Percent of Total NIH Grants Year

29. Studies on Women or Females (%) 1972-1974 1 % 1-5 % 5-10 % >10%

30. Studies on Women or Females (%) 1972-19741982-1984 1992-19942002-2004 1 % 1-5 % 5-10 % >10%

31. NIH Results Summary Priority setting in the NIH extramural and intramural programs for women’s health is not insulated from politics Priority setting in the NIH extramural and intramural programs for women’s health is not insulated from politics All four pathways of external influence seem to matter All four pathways of external influence seem to matter Extramural decisions are associated with more external influences Extramural decisions are associated with more external influences

32. Priority Review of New Drugs

33. Mean Drug Review Times (in months)

34. FDA Independent Measures I MeanRange Mobilizing Resources Disease-specific women’s health groups 1.4 0 – 10 Other disease-specific groups 7.6 0 – 46 Raising Awareness Congressional oversight index 2.1 0 – 16 Media coverage index 136.88 0 – 923 Scientific journal articles 3004.4 0 – 12097

35. FDA Independent Measures II MeanRange Disease burden per 10,000 population Prevalence rate for women 606.6 0 – 4498 Prevalence rate for men 403.1 0 – 5590 Death rate for women 4.4 0 – 30 Death rate for men 5.5 0 – 40 Other Variables FDA workload 1.10.7-1.8 % of firms with previous success 73%

36. Directions for Future Research Examine impact of women’s and women’s health movement on other scientific agencies Examine impact of women’s and women’s health movement on other scientific agencies Study whether other disease groups that do not have historical gender inequities have influenced scientific agencies decisions Study whether other disease groups that do not have historical gender inequities have influenced scientific agencies decisions