Are Women ’ s Health Concerns Prioritized at the
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Scientific Agencies Are Women’s Health Concerns Prioritized at the NIH and the FDA? Scientific agencies use scientists and scientific evidence to make science policy Likely to Nicole C. Quon, Quon, Ph.D. Assistant Professor Indiana University seek bureaucratic autonomy May respond to external pressure under certain conditions Women’ Women’s Health Movement Relied on frames of gender inequity Mobilizing Resources Scientific agencies may consider the demands of resourceresource-rich groups Concerns about medical research – Increasing attention to women’ women’s health – Participation of women in clinical trials – Research funding for women’ women’s health issues, especially breast cancer Raising Awareness Range General women’ women’s health groups 7.5 2 – 14 DiseaseDisease-specific women’ women’s health groups 1.1 0–9 Other diseasedisease-specific groups 5.0 0 – 56 401.8 0 – 743 National Women’ Women’s Health Network budget ($1000) Reducing Monitoring Costs Scientific agencies may respond to signals of issue importance Political/social influence vs. scientific influence Congressional oversight index (alpha=0.62) Mean Administrative procedures – Introduce decision makers who share the same values Mean Range Mean Range Women in senior NIH positions 3.6 0–9 17.8 0 – 42 Women in NIH study sections (% change) 0.8 -1.8 – 5.2 Media coverage index (alpha=0.91) 21.4 0-277 Scientific journal articles 331.1 0 – 3467 1 Gender Politics Disease Burden Issues related to gender may become Agency missions reflect public health more salient under certain conditions goals Rate for Mean Range 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 women or men could influence priority setting Mean Range 1427.8 1153 – 1960 Overall death rate for men 94.5 85 – 109 Prevalence rate for women 982.0 0 – 7660 3.0 0 – 42 Hospital admission rate for women DiseaseDisease-specific death rate for men NIH Dependent Measures Related to decisions in the NIH grants program – Grants for “women or female” female” studies Extramural program (n=556) Intramural program (n=418) – Grants for studies on 23 diseases on the women’ women’s health agenda Extramural program (n=749) Intramural program (n=660) Collected from the CRISP database of funded grants from 1972 to 2004 NIH Independent Variables Mobilization of resources Raising awareness Reducing monitoring costs Gender politics Disease burden Other variables Keyword searches of grant titles and abstracts – Female medical school faculty, year trend, presidential dummies NIH Model Specification NIH Extramural Priorities Models Studies on Women or Females Count data – Data was overdispersed – Data was a panel design 32 years 23 institutes or 23 diseases Coeff. Coeff. S.E. Studies on 23 Disease Priorities Coeff. Coeff. S.E. Mobilizing Resources General women’ women’s health groups -0.0013 0.0108 -0.0811 * 0.0470 DiseaseDisease-specific women’ women’s health groups -- -0.1457 *** 0.0213 Other diseasedisease-specific groups -- 0.0471 *** 0.0041 National Women’ Women’s Health Network budget 0.0003 0.0003 Random effects negative binomial models Offset to account for varying institute sizes Congressional oversight 0.0017 0.0018 Lagged independent variables Media coverage -0.0003 0.0003 Scientific journal articles -0.0002 0.0002 -0.0003 0.0003 Raising Awareness On women’ women’s health On specific disease 0.0075 *** 0.0018 0.0132 ** 0.0060 0.0040 *** 0.0008 -0.0003 *** 0.0001 * p<0.10, ** p<0.05, *** p<0.01 2 NIH Extramural Priorities Models Studies on Women or Females Coeff. Coeff. S.E. NIH Extramural Priorities Models Studies on 23 Disease Priorities Coeff. Coeff. S.E. Studies on Women or Females Studies on 23 Disease Priorities Coeff. Coeff. S.E. Coeff. Coeff. -0.0001 0.0001 0.0003 0.0002 0.0185 0.0246 -0.0501 0.0358 S.E. Disease Burden Reducing Monitoring Costs Women in senior NIH positions 0.0319 * 0.0168 0.0270 0.0174 Hospital admission rate for women Women in NIH study sections 0.0063 0.0172 -0.0163 0.0117 Hospital admission rate for men Overall death rate for women Political Salience Overall death rate for men Women in Congressional committees 0.0215 0.0224 0.0389 ** Positive gender gap in Presidential election 0.0252 * 0.0150 0.0325 *** 0.0096 Negative gender gap in Presidential election 0.0020 0.0150 -0.0449 0.2535 Partisanship in Congress -0.0159 * 0.2102 0.0189 Prevalence rate for women 0.0001 *** 0.0000 Prevalence rate for men -0.0001 0.0093 DiseaseDisease-specific death rate for women -0.1570 *** 0.0151 0.1823 DiseaseDisease-specific death rate for men * p<0.10, ** p<0.05, *** p<0.01 0.0001 0.1497 *** 0.0126 * p<0.10, ** p<0.05, *** p<0.01 NIH Intramural Priorities Models FDA Dependent Measures Fewer influences seem to matter compared to extramural program decisions Related to decisions for new drug approval Studies on women or females – Assignment of “priority” priority” review – Speed of new drug review in months – Gender politics: negative gender gap Studies on 23 disease priorities – Mobilizing resources: other diseasedisease-specific groups – Raising awareness: congressional oversight on specific diseases – Disease burden: death rate for men FDA Independent Measures Mobilizing of resources – Interest groups Raising Approval dates from 1970 to 2004 Focused on drugs approved for diseases on the women’ women’s health agenda (n=131) FDA Model Specification Logistic regression to examine assignment of priority review awareness – Congressional oversight, media coverage, scientific articles Disease burden Other variables Proportional hazards regression to examine the speed of drug review – FDA workload, previous firm success, PDUFA 3 FDA Priorities Models FDA Priorities Models Priority Review Priority Review Coeff. Coeff. Drug Review Times S.E. Coeff. Coeff. S.E. Mobilizing Resources Drug Review Times Coeff. Coeff. S.E. Coeff. Coeff. S.E. Prevalence rate for women -0.0007 0.0010 0.0002 0.0003 Disease Burden DiseaseDisease-specific women’ women’s health groups 0.1963 0.2049 -0.0817 0.0734 Prevalence rate for men -0.0039 0.0037 0.0000 0.0002 Other diseasedisease-specific groups 0.0191 0.0928 0.0259 0.0178 DiseaseDisease-specific death rate for women -0.5468 1.2130 0.1310 0.1259 DiseaseDisease-specific death rate for men -2.4601 * 1.4444 -0.1057 0.1128 Raising Awareness Priority rating Congressional oversight on specific diseases -0.7353 0.6461 0.0213 0.0906 Media coverage 0.0969 0.5312 -0.0325 0.1793 Scientific journal articles 0.1076 0.0657 0.0229 *** 0.0081 -- FDA workload PDUFA trend Summary of Main Results The FDA was responsive to the women’ women’s health movement But not in priority setting for new drug approval 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 1.4061 *** 0.3556 Other Variables Previous firm success * p<0.10, ** p<0.05, *** p<0.01 -- -0.0270 2.0056 -0.5728 0.6231 0.2718 0.7708 0.3145 0.3401 -0.0208 0.1190 0.0871 0.0456 * p<0.10, ** p<0.05, *** p<0.01 Study Limitations NIH dependent measures collected using keywords Data on grant applications unavailable Women’ Women’s health advocacy measure is crude Few drugs for diseases on the women’ women’s health agenda Policy Implications Scientific agencies are not insulated from gender politics Influence depends on the type of decision and agency culture Some pathways of influence seem more effective – Collaborations between interest groups and Congress – Increasing the role of women leaders 4 Pathways of External Influence Research “External signals” signals” theory – Josckow, Josckow, Olson – Mobilizing resources – Raising awareness scientific agencies – NIH intramural grants program Distributive “Political control” control” theory – Weingast and Moran, McNollGast, McNollGast, McCubbins and Schwartz – Reducing monitoring costs Agency Mandates and Culture scientific agencies – NIH extramural grants program Regulatory scientific agencies – FDA Center for Drug Evaluation and Research Political salience NIH Independent Variable Lags Grants for Women's Health Agenda Diseases Agencies respond to most recently 50 Percent of Total NIH Grants available information 1 year lag: Congressional oversight, media, and scientific journal coverage 2 year lag: interest groups 40 30 20 1970 1975 1980 1985 1990 1995 2000 2005 Year W o m e n ’ s H e a l t h A g e Year nda 3 year lag: disease burden Studies on Women or Females (%) Studies on Women or Females (%) 1972-1974 1972-1974 1982-1984 1% 1% 1-5 % 1-5 % 5-10 % >10% 1992-1994 2002-2004 5-10 % >10% 5 NIH Results Summary Priority Review of New Drugs Priority setting in the NIH extramural and intramural programs for women’ women’s health is not insulated from politics 40% 34% 30% 30% 20% All four pathways of external influence seem to matter 10% Extramural decisions are associated with more external influences 0% All drugs (n=653) Mean Drug Review Times (in months) Women's health drugs (n=131) FDA Independent Measures I 30 24.2 23.6 Mean Range DiseaseDisease-specific women’ women’s health groups 1.4 0 – 10 Other diseasedisease-specific groups 7.6 0 – 46 Mobilizing Resources 20 Raising Awareness 10 Congressional oversight index 0 All drugs (n=653) Mean Range Prevalence rate for women 606.6 0 – 4498 Prevalence rate for men 403.1 0 – 5590 Disease burden per 10,000 population Death rate for women 4.4 0 – 30 Death rate for men 5.5 0 – 40 Other Variables FDA workload 0 – 16 136.88 0 – 923 Scientific journal articles 3004.4 0 – 12097 Women's health drugs (n=131) FDA Independent Measures II % of firms with previous success 2.1 Media coverage index 1.1 73% 0.70.7-1.8 Directions for Future Research Examine impact of women’ women’s and women’ 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 6
