U N D E R T H E M I C R O S C O P E patient ’ s overall health and rule out any surgical risk . During this pre-anaesthesia 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 at 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 AG ’ 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 AG ’ 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 highrisk 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 ageing 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 and 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 . �
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