OBJECTIVES: Following major changes to sexual health provision in England in the past decade, monitoring and evaluation of population-level interventions require re-examination to ensure quality and visibility of key communities. We make the case that sexual health data sources might be used synergistically to improve sexual health and tackle inequalities.

METHODS: We conducted a purposive narrative review to (1) describe national sexual health policy and provision changes in England in the past decade (2012 onwards), (2) map key sexual health data resources and (3) demonstrate how integrated data-driven approaches can be used to understand and evaluate population-level sexual health policy.

RESULTS: There have been major changes at a national and regional level in the availability, targeting and implementation of HIV and sexually transmitted infection (STI) interventions, including through high-level shifts in funding structures, expansion of online services and pathogen-focused policies. Synergistic use of the many data sources available takes advantage of their different features. For example, for HIV, integration of nationally representative behavioural surveys that include people not accessing care (eg, National Surveys of Sexual Attitudes and Lifestyles), targeted surveys (eg, Reducing inequalities in Sexual Health surveys for gay, bisexual and other men who have sex with men (GBMSM)) and national STI/HIV surveillance for people accessing care (eg, GUMCAD STI Surveillance System) can be used to inform progress towards HIV elimination in England through assessment of online and postal-based self-sampling and inequalities in HIV testing uptake in populations and key communities such as GBMSM.

CONCLUSION: In the face of rapid change, approaches that integrate complementary data sources have the potential to harness the strengths of individual assets and mitigate limitations to form a more complete assessment of population-level interventions and should guide sexual health policy and practice in the decade to come. Effective data integration requires addressing a range of methods, mandates and challenges to strengthen contemporary research, monitoring and evaluation.