Dr. Benjamin Dodsworth


To reduce the high incidence of postoperative delirium by identifying high-risk patients prior to surgery.


Disorientation, memory loss, difficulties in speech. If you are over sixty and about to undergo surgery, you could be at risk of developing any or all these symptoms. Postoperative delirium (POD) is an enormous problem occurring in 25% of surgical patients aged 60+. POD leads to adverse outcomes such as a 25% mortality within one month, double the risk of nursing home admission, costs of 1-2 B Euros to health insurers in Germany alone and 38% of the affected end up suffering long-term cognitive decline and dementia. There are no treatments available once symptoms arise. Instead, the focus is on prevention. Many highly effective prophylactic treatments have been developed but are too costly to deploy for every patient. We are a start-up developing a novel, AI-based pre-operative risk prediction tool which highlights patients at risk before undergoing surgery. This patient-centric approach increases patient value by improving health outcomes and decreasing costs over the full cycle of care.
Patients are heavily included in the development and implementation of the tool. Typically, these are elderly or frail patients about to have surgeries such as knee or hip replacements. We have interviewed over 20 affected patients and relatives to get their perspective on the problem. The solution itself is “patient centered and doctor driven”. The tool is used by the anaesthesiologist (inputting key risk factors), and the result allows clear communication of risk and benefits of the surgical intervention, thus empowering the patient. Shockingly, the patient is often not informed about their risk of POD. We strongly believe that the patient needs to be adequately informed about the risks and benefits of their interventions – and we are not alone. The Fifth International Perioperative Neurotoxicity Working Group issued a statement in 2018 raising the same issue.
We have collected over 20.000 patients worth of data from over 20 clinical trials around the world. We have used this data to create an AI based algorithm to predict risk. Continuous monitoring of health outcomes of patients who have used the tool allows for further learning and is an effective feedback loop. Subjective replies regarding wellbeing from patients will be included. We are collaborating with hospitals (Hirslanden Klinik Zurich, University Hospital of Basel, Claraspital Basel, Kantonspital Baden, Hôpital de La Tour, UMC Groningen), academic partners (Cochrane Anesthesia, Cochrane Response, McMaster University), software developers (Future Processing) and regulatory specialists (Effectum Medical). Our core team is multidisciplinary and includes an anaesthesiologist (Nayeli Schmutz), a technical expert (Dr. Benjamin Dodsworth) and a business lead (John Klepper). The POD risk prediction tool promotes the formation of IPUs across hospital boundaries, by bringing together patients, their relatives, GPs, surgeons, anaesthesiologists, and likely also pre-hab physiotherapists or geriatricians. Later we plan to add other postoperative complications.
An in-depth budget impact analysis showed that we can save an average public hospital in Switzerland 2.2M CHF (2M Euro) annually by reducing length of stay and improving patient outcome.