March 13, 2024

John featured in intelligent health issue 14, Nov 23

What challenges in healthcare does PIPRA's technology address, especially concerning the prevalence of undiagnosed POD cases in older patients?

POD has staggering effects on patients, their families and carers, and on already strained healthcare systems globally, where hospital beds are limited, healthcare professionals are stressed and overworked, wait times for operations are getting even longer and as the world’s population ages. Using a real-world example, with PIPRA, we have been able to reduce the occurrence of POD by up to 43%.

Where implemented, PIPRA will take significant strain off our already bursting healthcare systems, and that is globally speaking. Medical professionals will be freed up to see patients with other ailments, and will be able to go about their workday without the worry and stress of patients developing POD in their care.

For background, POD is a common condition in adults over 60 years of age who are undergoing a surgical procedure, whether a small routine surgery or something major. POD is a distressing condition, with symptoms that include agitation or profound inactivity, as well as changes to a person’s attention, awareness and cognitive ability. It is also associated with an increase in post-surgery falls, longer hospital stays, increased nursing home admissions, hospital readmissions, cognitive decline, dementia and increased mortality.

The condition also increases hospital stays for those who have undergone a routine surgery by 1.5 times and causes mortality rates to increase by twofold. These short and long term impacts of POD are putting significant strain on healthcare costs every day, stretching hospital’s financial resources even further.

Could you elaborate on the personal motivation behind Pipra AG's journey to develop this life-changing AI technology for preventing POD?

Back in 2010, my mother went in for a routine surgery at a renowned hospital in Switzerland. Sadly, when she woke from her surgery she was a different person. She suffered from POD. For days she saw monsters coming out of the hospital walls and thought the hospital staff were trying to kill her. While she was fortunate enough to ‘recover fully’ she has a type of PTSD from the experience and to this day is still terrified of hospitals. The impact that this had on my mother was one of the driving forces behind me wanting to be able to prevent this ghastly condition. Having previously worked in Alzheimer’s Disease early prediction and prevention, also using AI, and with the strong links between the two diseases, I felt compelled to act on this to prevent others having the same experience.

Many of the patients I spoke to early on, while doing discovery and stakeholder interviews, described the experience of delirium as the “worst days of their lives” and those are the lucky ones who did not suffer from accelerated cognitive decline.

Can you explain how Pipra's AI-powered software works in preventing postoperative delirium (POD) in older adults?

PIPRA is a MedTech start-up based in Zurich, Switzerland, with a focus on the prevention, prediction and diagnosis of delirium. We have developed an innovative AI-based tool called PIPRA that can be used to predict (POD), allowing clinicians to introduce targeted interventions for high-risk patients.

Essentially, PIPRA is a predictive tool that measures the risk of postoperative delirium before a patient goes for surgery, using clinical information that is routinely collected by their healthcare professionals.  

A patient typically sees their anesthesiologist before surgery and is asked a series of routine questions to assess the patient's overall health and rule out any surgical risk. During this pre-anesthesia consultation our software automatically extracts some of the routinely collected data and runs a risk calculation in the background. The risk score allows for slight modification of the patient pathway for high-risk patients, who then receive highly effective preventive treatment. This would be too costly to carry-out for every patient but very cost-effective when targeted on high-risk populations.

Could you provide insights into the role of AI in personalising the treatment and prognosis for patients at risk of POD?

PIPRA's technology, PIPRA, leverages AI algorithms to analyse individual patient data, enabling the identification of high-risk patients before surgery. By considering various clinical parameters routinely collected by healthcare professionals, PIPRA tailors predictions for each patient, allowing clinicians to implement targeted interventions and personalised care plans.

How has PIPRA's technology demonstrated its ability to reduce delirium by up to 43%? Can you share any success stories first hand?

PIPRA has shown promising results in reducing the occurrence of POD by up to 43%. Real-world implementation of PIPRA has resulted in tangible success stories where patients identified as high-risk for POD received tailored interventions, leading to a significant decrease in the incidence of delirium. 

An innovative approach in a recent hospital study involved automated postoperative risk prediction data input with Robotic Process Automation (RPA) and ensuring immediate action by the hospital. The outcomes were striking: a reduction in delirium incidence rates by at least 11% and a shortened hospital stay by 0.8 days. 

Given the increasing ageing population and the rise in surgeries, how do you envision Pipra AG's technology making a significant impact on healthcare outcomes in the UK?

Essentially, with our technology, older populations will not only be able to live longer because of life changing surgical advancements, but they will also be able to live fuller lives without the short-term and long-term complications of POD.

The UK's healthcare landscape, especially the NHS, presents a significant opportunity for our delirium management solution, given the substantial patient waiting list for surgery of over eight million people. By reducing the length of stay for 20% of patients over 60 by at least 0.8 days, we can make a substantial impact on patient care in the UK.

Can you discuss the financial implications of POD and how Pipra AG's solution might help reduce healthcare costs?

With PIPRA in place, we have been able to reduce the occurrence of POD by up to 43% and show savings to an average hospital of up to £2.85m each year.

We monitor cost savings achieved by hospitals using PIPRA, and reduced readmissions and optimised resource allocation contribute to substantial financial gains.

What is the connection between POD and the development of dementia, and how does Pipra AG's technology address this concern?

The link between POD and the development of dementia is well-established in medical literature. Adults who experience POD are at an increased risk of developing dementia by 14 times, compared to those without POD. PIPRA addresses this concern by identifying patients at risk of POD before surgery. By implementing targeted interventions for high-risk individuals, PIPRA aims not only to reduce the incidence of POD but also to mitigate the associated long-term risks, including the development of dementia. This proactive approach aligns with our commitment to improving overall patient well-being.

As technology continues to evolve rapidly, how do you see Pipra AG's AI-powered software adapting and advancing to meet the changing healthcare landscape and the needs of an aging population in the coming years?

The rapid evolution of technology presents exciting opportunities for PIPRA AG's AI-powered software. Looking ahead, we envision continuous advancements in our algorithms, incorporating the latest developments in artificial intelligence and machine learning. 

Our vision is to build an impactful and profitable business by improving perioperative care and postsurgical quality of life for patients while reducing costs for patients, relatives, hospitals and insurers in the communities we serve. We aim to set the standard of care for preoperative risk assessment as a first step then build a platform to improve perioperative care through personalised precision medicine. We are working on innovative products for the prediction, prevention and diagnosis of delirium. One product is a self-administered POD risk assessment to reduce the administrative burden for healthcare professionals and provide opportunities for patients to be more involved in their own healthcare pathway. Another project in development is a prototype for the automated early diagnosis of delirium. 

The goal is to transition from single-use products to an easily integrated platform delivering value to multiple hospital stakeholders while improving patient-care pathways and outcomes.