Disorientation, memory loss, difficulties in speech. If you are over sixty and undergoing surgery, you could be at risk of developing any or all these symptoms. Postoperative delirium (POD) is an enormous problem occurring in 23% 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% suffer 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 (40% reduction of POD) have been developed. These are cheaper than a patient with delirium but are too costly to deploy for every patient.
Even though preventable, postoperative delirium remains at 23% in surgical patients over 60, unchanged for 30 years; PIPRA, through its innovative AI-driven approach, breaks this long-standing trend and significantly improves patient outcomes.
PIPRA AG has developed a cutting-edge AI-based pre-operative risk assessment tool called PIPRA (short for Pre-Interventional Preventive Risk Assessment), to assess the risk of a patient developing POD. The test uses standard medical data and provides an immediate score-based risk assessment.
By incorporating PIPRA into their clinical workflows, healthcare professionals gain valuable insights to implement targeted preventive strategies, ultimately enhancing patient outcomes and reducing the incidence of delirium.
This individualized approach optimizes healthcare resource allocation, ensuring that each patient receives the best possible care.
Support through training, informative materials, and on-the-ground support, care staff gains practical guidance to effectively manage delirium. This enables them to enhance their skills, improve patient care and experience the benefits of streamlined workflows.
Insights and feedback into daily delirium practices empowers hospitals to swiftly adapt their delirium management plan. PIPRA's robust data analytics capabilities further enhance hospitals' ability to make informed, data-driven decisions, streamline operations and ultimately optimize their financial performance.
Case study 300-bed hospital (data from controlled before-after study)
The product is an algorithm that detects the risk of POD in presurgical patients. The tool can be incorporated into all modern EHR systems. We can already readily integrate into systems by Epic, ChipSoft, SAP and eClinicalWorks.
As an alternative that requires no administrative effort, we have built an easy-to-use and quick browser-based and platform-independent user interface. We received overwhelmingly positive feedback in customer validation tests.