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WHO Collaborating Center in Pharmaceutical Policy

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WHO Collaborating Center in Pharmaceutical Policy

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  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 Netherlands2: 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.org

  6. Method

  7. Calculation of Expected Outcomes From WHO 2004 gender-specific global burden of disease estimates by country Burden of disease in women Total burden of disease (men + women) • Proportion of use of particular drugs in women • H0: Should parallel relative proportion of visits by women Number of treated consultations for condition in women From observed number of visits for condition in IMS data Total number of treated consultations for condition (men + women) • Proportion of treated consultations for women • H0: Should parallel relative burden of disease in women

  8. Bias only in treated consultations for diabetesNo evidence in acute respiratory infection or depression 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

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