Bingli
NHS Problem:
The NHS faces a pressing challenge in meeting the increasing demands of a growing and aging population while grappling with a shortage of personnel. This issue is particularly pronounced in emergency departments (EDs), where patient expectations for quick and high-quality care are at an all-time high. ED attendance, waiting times, and ambulance offload times have reached unprecedented levels, necessitating a focused effort to maximize efficiency throughout the patient journey. By optimizing internal processes within EDs, we can significantly reduce the time required to make crucial clinical decisions. Ensuring the safety and efficiency of these processes is vital for enhancing patient experience, promoting patient safety, and maintaining a smooth hospital flow.
Solution:
Most decisions in healthcare are based on data collected by asking patients questions during the history taking. This is time consuming and administrative heavy.
Bingli asks the right questions in advance using the most accurate AI. Patients can answer at their own pace, in their own language.
By asking the right questions we help patients get the right care by the right caregiver at the right time in the most time and cost-efficient way. It generates a list of differential diagnoses and other actionable insights based on responses patients give, resulting in a more productive and cost-efficient consultations.
Impact:
– 20% reduction in ED throughput time: reduced waiting times and increased capacity / availability of services
– 20% less time spent on administration (paperless, fully coded/structured information: Snomed CT, ICD10, ensuring EHR integration or PDF export)
– Cost reduction (less unnecessary technical investigations, less need for translators as Bingli is multilingual)
– Complete patient files with coded/structured data results in valuable datasets that can be used for analysis, decision making, training, identification of candidates for clinical studies
– 90% diagnostic accuracy
– Empowered patients: patients can answer questions in their own language (full multilingual support), taking into account health literacy