Equal waiting for elective care?

New evidence on inequalities in NHS waiting times in England

The proportion of waits within 52 weeks has also improved for people in both the most and least deprived areas since June 2025. In this case, the inequality between the two groups has narrowed substantially (Figure 1). The total number of waits over 52 weeks decreased for both groups across this period, indicating that the proportional improvement is the result of increased activity or removals from the waiting list rather than a growth in more recent referrals. 

A large share of the reduction in inequalities in very long waits stemmed from improvements observed in five ICBs: Birmingham and Solihull, Greater Manchester, Cheshire and Merseyside, Lancashire and South Cumbria, and South Yorkshire (Figure 2). These five ICBs have very high (>20%) proportions of people living in the most deprived areas on their waiting lists, meaning that general improvements in waits within 52 weeks in these locations would be expected to narrow national inequality substantially. In most of these ICBs, the proportion of people living in the most deprived areas who have been waiting over 52 weeks also declined at a faster rate than that of people living in the most affluent areas, indicating real reductions in socioeconomic inequalities. The fastest narrowing of inequality in any ICB was seen in Lancashire and South Cumbria (1.3 percentage point reduction), previously highlighted by The Kings Fund for its efforts to reduce inequalities in the elective waiting list.

Socioeconomic inequalities in the proportion of waits within 18 weeks were present within almost all ICBs (Figure 3), with nearly two-thirds showing inequalities greater than those observed at the national level (1.1 percentage point difference). This indicates that national inequalities in waiting times are not simply due to the most deprived areas tending to be concentrated in ICBs where all patients experience longer waiting times. 

At the specialty level, a reduction in very long waits for ear, nose and throat (ENT) services for people in the most deprived areas has contributed to the narrowing of socioeconomic inequalities in waits within 52 weeks. While the publicly available WLMDS data do not break down metrics for demographic groups by both ICBs and specialties at the same time, wider RTT data from NHS England show general reductions in very long waits for ENT services in the five ICBs mentioned earlier.  

People in the most deprived areas were more likely to be waiting for certain treatment specialties with relatively long wait times, such as gynaecology. However, overall inequalities cannot be attributed simply to the fact that people in more deprived areas may be disproportionately waiting for specialties that have long wait times for all patient groups. There are inequalities in waiting times between people living in the most and least deprived areas within almost all treatment specialties as well, most notably plastic surgery (7 percentage point difference in the most recent three months of data), dermatology (5 percentage point difference) and urology (5 percentage point difference).  

While national-level waiting time inequalities cannot be explained simply by geographic distribution or mix of treatment specialties, differences in age distributions between population groups remain a potential driver. More deprived areas and some ethnic groups (see the following section) often have younger age profiles than the general population in the UK. As such, some degree of difference in waiting times for elective care may be expected given that clinical prioritisation often favours older patients. However, previous analysis by the Networked Data Lab found that inequalities typically persisted when age was held constant, implying alternative drivers.   

However, people whose background was coded ‘any other ethnicity’ in the WLMDS consistently saw a faster pace of improvement in waiting times than any other group across the observed period. As this is a large and likely heterogenous group, it is not possible to gauge from the available data if this trend is being driven by improved waiting times for any particular sub-population within this category. 

Conversely, people with Indian, Pakistani or Bangladeshi backgrounds consistently had among the lowest proportions of waits within 18 weeks over the observed period (Figure 4), as highlighted by NHS England upon the initial data release. In the most recent three months of data, 61% of people with Indian or Pakistani backgrounds and 60% of people with Bangladeshi backgrounds had waits within 18 weeks, 2 and 3 percentage points below the national total of 63%, respectively. 

These overall disadvantages for South Asian populations are not uniform across specialties. They primarily stem from persistently lower proportions of waiting times within 18 weeks in specific specialties. The largest inequalities in waiting times are within dermatology services, where 54% of people with Indian, Pakistani or Bangladeshi backgrounds waiting for care had waits within 18 weeks, compared with 63% of people with White British, Irish or Other backgrounds in the most recent three months of data (9 percentage point difference). Dermatology also has the widest range of waiting times between ethnic groups more generally. Beyond the inequalities observed for South Asian populations, the proportion of people with Black African, Caribbean or Other backgrounds who had waits within 18 weeks was around 6 percentage points lower than the White British, Irish or Other population.  

Large ethnic inequalities are also present in waiting times for plastic surgery, general internal medicine, urology and neurosurgical services. In many cases, these are the same specialties in which gaps between people living in the most and least deprived areas are also greatest, indicating an interrelation, and likely some common drivers, between socioeconomic and ethnic inequalities on the waiting list.  

Barriers to broader elective care access for Asian communities have been observed in previous analysis by the Nuffield Trust and the NHS Race and Health Observatory. The King’s Fund also points to practical challenges navigating the elective care system or attending appointments that likely disproportionately affect systemically marginalised communities, such as linguistic barriers and the unavailability of interpreters, all of which can contribute to treatment delays. Cultural differences in care-seeking behaviour and interaction with the health care system may also influence variation in waiting times and access to elective care for these communities.       

However, the drivers of these disparities cannot be fully understood without a clearer picture of the underlying demographic composition and health needs of the groups compared. Differences in age distribution between groups likely influence variations in their elective waiting times. To understand disparities in waiting times and identify the barriers to accessing care, it is important to consider age, deprivation and ethnicity together, as these factors can interact to influence both waiting times and equity of access. For instance, dermatology, a specialty with a wide variety of case types, has the greatest differences in waiting times between population groups; rates of high-priority issues within dermatology, primarily some skin cancers, are far more common among older and paler-skinned populations, likely shaping the distribution of waiting times for care. Additionally, ethnicity is not always recorded, resulting in gaps and inconsistencies in the data and making it difficult to obtain an accurate picture.