NHS publishes waiting list breakdowns to tackle health inequalities

Hospitals will be able to address unfair elective waits for working class and minority patients as new data published today shows those from deprived communities are more likely to wait longer.

For the first time, the NHS has published detailed data revealing how long patients wait for elective care based on demographics like age, sex, ethnicity, and deprivation level. The findings are stark: people from working-class communities and those of Asian or Asian British backgrounds are more likely to wait over 18 weeks for treatment — highlighting systemic inequalities that the government’s 10-Year Health Plan aims to tackle.

At the heart of this strategy are targeted interventions: funding for deprived areas, the rollout of neighborhood health centers, and programs to support employment through the NHS. With more than half the waiting list made up of working-age adults, and women disproportionately affected, this data is a crucial step toward transparency and equitable reform.

Leaders across healthcare have praised the move. By making disparities visible, local NHS services can now build evidence-based plans to cut waiting times and improve outcomes in underserved communities.

• Unequal waits: Patients from deprived areas and Asian/Asian British backgrounds are most likely to wait over 18 weeks for elective care.

• Women wait longer: Women make up 57% of the waiting list and are more likely than men to face long delays — especially in specialties like gynaecology.

• By age group:

  • 56% of the waiting list is made up of working-age adults (19–64).

  • 33% are over 65.

  • 11% are 18 or younger.

  • Gynaecology is the top specialty for 18–64s; ophthalmology for those 65+.

• 10-Year Health Plan actions:

  • Billions redirected to deprived areas.

  • 1,000 new NHS roles for people from high-unemployment communities.

  • Neighborhood Health Centers prioritized in cities with the lowest life expectancy.

• Digital access: NHS App now includes multiple language options to expand access for diverse populations.

• Local solutions in action:

  • Sheffield: Used AI to identify missed appointments in deprived areas and improved attendance with prepaid transport.

  • Lancashire: ‘Set for Surgery’ pilot offered prehab support, reducing cancellations and improving outcomes.

• Transparency push: Data will now be updated monthly and support performance improvement and resource targeting across NHS trusts.