1. Gender and Access to Medicines in 15 Low- and Middle-Income Countries: Does Physician Prescribing for Men and Women Differ? Stephens, Peter (1); Ross-Degnan, Dennis (2); Wagner, Anita (2) 1: IMS HEALTH, United Kingdom & WHO Collaborating Centre for Pharmacoepidemiology and Pharmaceutical Policy Analysis, Utrecht University, Utrecht, the Netherlands 2: Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA WHO Collaborating Center in Pharmaceutical Policy

2. What do we know already? Gender inequity confirmed by many different outcome indicators – e.g. World Economic Forum Global Gender Gap Index Gender inequity studies have tended to report that women are less favoured than men – Though not always Little information on impact of gender on access to medicines – And little outside of hospital

3. Study aims Does gender affect prescribing in low and middle income countries? If gender does affect prescribing, are men more favoured than women? Are the prescribing data used in this study an effective and appropriate indicator of gender inequity?

4. Data sources Treated consultation records – 3 conditions (1 acute, 2 chronic) Acute Respiratory Infection Diabetes Depression – 3 age groups (0-14,15-59, 60+ years) – 15 countries between 2007-10 – 487,841 consultations 217,004 male, 270,837 female – 855,476 prescriptions 391,913 male, 463,563 female

5. Study countries Visualization from Gapminder World, powered by Trendalyzer from www.gapminder.orgwww.gapminder.org

6. Method ObservedVsExpected Treated consultations by age and sex Vs Disease burden (DALYs) by age and sex New oral hypoglycaemic prescriptions by age and sex Vs Consultations for diabetes by age and sex

7. Calculation of Expected Outcomes Proportion of treated consultations for women −H 0 : Should parallel relative burden of disease in women Burden of disease in women Total burden of disease (men + women) From WHO 2004 gender-specific global burden of disease estimates by country Proportion of use of particular drugs in women − H 0 : Should parallel relative proportion of visits by women Number of treated consultations for condition in women Total number of treated consultations for condition (men + women) From observed number of visits for condition in IMS data

8. Bias only in treated consultations for diabetes No evidence in acute respiratory infection or depression 8 Women higher than expected Women lower than expected

9. Results Observed prescribing rates do differ significantly from Expected in many cases No consistent bias towards or against women – except in diabetes prescribing No obvious relationship between the World Economic Forum’s Global Gender Gap Index and differences in prescribing rate

10. Key lessons & implications Gender inequity as measured by prescribing rates is condition, country and age specific – One size fits all policies may waste resources or make situations worse Further work needed to understand relationship between prescribing indicator (“process”) and outcome indicator (“GGGI”) – Will require additional data collection (region, caste,...) IMS data can be used to explore key issues, when linked to external data sources