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 Centerin Pharmaceutical Policy

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

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?

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

Study countries

Visualization from Gapminder World, powered by Trendalyzer from www.gapminder.org

Method

Observed Vs Expected

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

Calculation of Expected Outcomes

• Proportion of treated consultations for women

−H0: 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

−H0: 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

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

8

Women higher than expected

Women lower than expected

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

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