Harnessing digital data to improve the benefit:harm balance of opioids for non-cancer pain

Background: Opioid use for non-cancer pain has been increasing over the last 15-20-years in North America and Europe and has emerged as a major public health concern in the last decade.

Opioids have led to a major societal burden in North America; however, less is known about their utilisation in vulnerable subgroups and safety in Europe and the UK.

Some opioid users may be particularly vulnerable to related harms due to individual factors such as older age, comorbidities and polypharmacy. Maximising benefits and limiting risks of treatment for such patients is therefore a national priority.

This fellowship application is timely due to the availability of new linked data sources, methodological advances, novel technology such as mhealth, and implementation of findings through health informatics.

Aim: To improve the benefit/harm balance of opioids in the treatment of non-cancer pain Objectives To evaluate the comparative safety of opioids in relation to short, long-term safety outcomes and mortality To evaluate treatment patterns associated with persistent opioid use, dependence and harms in sub-populations susceptible to opioid overprescribing (post-surgery and musculoskeletal conditions) To develop and validate prediction models for key opioid-associated safety outcomes To evaluate the benefits and harms of opioids using social media and mobile (m)health data To develop safety indicators to be implemented into practice using actionable analytics Design and methodology: The fellowship will harness strengths of electronic health records (EHRs) regionally, nationally and internationally.

Using novel techniques such as weighted cumulative dosing, it will model the dynamic pattern of opioid use to accurately estimate how cumulative effects of time varying exposure can affect adverse events. Machine learning will be used alongside traditional predictive modelling for individual risk prediction.

Benefits and harms will be measured directly from patients using new data sources such as social media and mhealth.

Using computerised decision support tools, resulting safety indicators will be implemented in Greater Manchester initially. Timelines for delivery: The research will be delivered over a 5-year period.

Anticipated impact and dissemination: It is not clear which opioid regimens place patients at risk of adverse events, what degree of risk is conferred or what predisposes patients to such events. This work will unpick some of the complexities of opioid-associated adverse events.

It will move risk estimation towards personalised risk, whereby patients can be informed of their individual risk of side effects before commencing the drug.

Although focussed on opioids, the skills and methods developed will have wider application for investigating the safety of other medications.

The results will be directly relevant to clinicians, patients, public health, and policy makers to drive improvements in outcomes and future prescribing.

As a member of Medicines and Healthcare products Regulatory Agency (MHRA) Opioids Expert Working Group, the results will have the potential to influence policy/guidelines where appropriate.

With direct links with NICE, Public Health England and the Science Media Centre, it will also allow wider dissemination of future outputs.