Deep Medical develops AI-powered tools to predict patient non-attendance for scheduled healthcare appointments. These predictive analytics enable proactive outreach, ensuring patients attend care slots and improving clinical efficiency. The platform helps healthcare providers reduce appointment no-shows and decrease patient waiting lists without increasing staff workload.
Funding
$3.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Missed appointments in healthcare settings lead to schedule disruptions, reduced clinical efficiency, and worse health outcomes for patients, particularly those from marginalized communities. The NHS faces a significant backlog, exacerbated by millions of missed appointments annually, costing billions and hindering access to timely care.
Solution
Deep Medical offers an AI-powered platform designed to predict patient no-shows and optimize appointment scheduling, enabling proactive outreach and efficient rescheduling. By analyzing various data points, the platform identifies patients at high risk of non-attendance without accessing medical records, ensuring patient data safety and GDPR compliance. This allows hospitals to fill vacant slots with patients from waiting lists, improving clinical efficiency and reducing waiting times without increasing the workload of NHS staff. The solution aims to reduce health inequality by helping patients from marginalized communities attend their appointments through targeted and compassionate outreach.
Target Audience
The primary target audience includes hospitals, healthcare providers, and medical professionals within the NHS seeking to improve clinical efficiency, reduce waiting lists, and address health inequalities.
Features
- AI-driven prediction of patient non-attendance using non-medical data.
- Proactive patient outreach to encourage attendance and offer rescheduling options.
- Optimized appointment scheduling to minimize disruptions caused by no-shows.
- Identification of at-risk patients to address healthcare disparities.
- Integration with existing hospital systems for seamless implementation.
- Real-time monitoring and reporting of no-show rates and intervention effectiveness.
- Secure data handling practices to ensure patient privacy and GDPR compliance.