Opioid prescribing to people on orthopaedic waiting lists during the COVID-19 pandemic

Over the course of the pandemic to now, the number of patients on the elective waiting list has grown hugely; from 4.6 million in February 2019 to 7.4 million in June 2025, an increase of 60%. As well as more people on the waiting list - the length of waits has increased. In some specialties this is particularly bad, such as trauma and orthopaedic procedures, where almost half of patients wait more than the care standard of 18 weeks for treatment, and during the pandemic 21% of patients waited over 52 weeks for treatment.

Two very common procedures on the waiting list are knee and hip replacement surgeries. People waiting on these procedures are often experiencing pain, and are frequently prescribed opioids to treat the pain. Longer waiting times mean that patients may require stronger pain relief, or are exposed to opioids for longer periods while awaiting treatment. However, overuse of opioids can have negative impacts like dependence, tolerance and even death, so reducing unnecessary opioid prescribing has been a target of policy and public health interventions in the UK and internationally.

To understand how the longer wait times might have impacted opioid prescribing, we conducted a study in OpenSAFELY-TPP on primary and secondary care data, and the national Waiting List Minimum Data Set. You can read about the data here. The work, now published in BMJ Medicine, focuses on a group at particularly high risk of opioid exposure: over 63,000 people living with painful musculoskeletal conditions such as osteoarthritis who are waiting for hip, and knee replacements, and other orthopaedic procedures.

What did we find?

• Over 20% of people on the elective trauma or orthopaedic waiting lists who received treatment between May 2021 and April 2022 waited over 52 weeks for treatment.
• In the three months before referral to the waiting list for treatment 16% of patients had three or more opioids prescriptions, often considered long-term use, and 6% were prescribed a strong opioid.
• Weekly prescription rates were stable across time, with peaks in prescribing seen immediately after treatment, plateauing about three months after treatment.
• There was a very small reduction in opioid prescribing considered ‘long term’ prescribing before and after surgery, but little evidence that longer waits contributed to more opioid prescribing post-surgery.

What do these findings mean?

Long waits became common

One in five people having elective trauma or orthopaedic surgery in 2021–22 had waited more than a year, a situation that was almost unheard of before the pandemic.

High baseline opioid use

Many patients were already using opioids regularly before referral, often alongside other analgesic drugs.

No strong signal that longer waits worsened post-surgery opioid use

People who waited longer did not have markedly higher rates of long-term prescribing after their procedure than those who were treated more quickly.

But long-term use remained high

Only small reductions in long-term prescribing were seen after surgery, suggesting there may be missed opportunities for opioid reduction.

Taken together, the findings suggest that shorter wait times may not appreciably reduce the risk of long-term opioid use post-treatment. This work highlights that this is a complex problem with many causes. While our study could not identify the causes of high rates of long-term opioid use, There may be a need for:

• Better support for patients to reduce or stop opioids after successful treatment;
• Routine medication reviews around the time of referral and after surgery;
• Improved access to non-pharmacological pain management; and
• Ongoing monitoring to ensure safe use of opioids in high-risk groups.

What’s next?

The study demonstrates the value of linking person-level waiting-list data with primary and secondary care health records inside OpenSAFELY to understand the ongoing impact the pandemic has had on service delivery in the NHS. We hope this research, and more in future will support data-driven policies to reduce harm due to unnecessary opioid prescribing for patients waiting for treatment.

Please read the full paper for the full results and our suggestions for future work in this area.