The iQud team is extremely hardworking and understood all of our needs, they got the job done immediately. Overall very happy working with them.
Overview
Our client is a leading multi-specialty hospital group with a prime focus on preventive healthcare and community outreach programs. The pain point of the client was the early identification of diabetes that required manual dependency on lab-based screening methods. Thus, to overcome this challenge, iQud suggested a quick, reliable, and real-time AI-powered solution helping with predictive diabetes risk scoring without any human dependency.
Technical Stack
Highlights
86% accuracy compared to lab-tested HbA1c results
Enabled early intervention in 3 out of 10 high-risk users
️ Reduced diagnostic backlog by 45% during OPD surges
Processed 1,000+ patients/day in screening camps
Challenges & Solutions
Challenges
Solutions
Low Adoption and Trust in the AI Model
Built AI predictive accuracy through clinical training and pilot studies.
Data Privacy and Compliance Concern
For patient data privacy, implemented encryption, anonymization, and compliance checks.
Integration issue with the current EMR System
For seamless EMR workflow integration, developed plug-and-play APIs
Reduction in Demographic Variability due to Model Accuracy
For accuracy with local population data, calibrate AI models to increase chances for variability.
Limited Connectivity or Community Screening
For rural camps and community screening, offline AI scoring was enabled with cutting-edge deployment.
Empowering Early Diabetes Detection – Smarter, Faster, Anywhere
Talk to our Experts!Core Features
- Non-invasive digital questionnaire
- Real-time risk scoring using a trained
- Works on mobile, tablet, and kiosk devices
- Optional lead capture form for follow-up
- PDF summary with doctor handover notes
Conclusion:
By enabling instant, paperless, and predictive diabetes risk scoring with an AI-powered solution, the hospitals and health centers were able to identify high-risk patients efficiently. The proposed solution not only bridged the early diagnosis gaps but also helped drive preventive care with much more confidence and with ease.
What Our Clients Say
iQud took time to really understand our project before diving in. Their work was done in a timely manner and exceeded our expectations.
Our logistics company was struggling with manual data entry and repetitive tasks that consumed valuable time and resources.
Partnering with iQud was a game-changer for our location-based app. They delivered precise geolocation, real-time updates, and an intuitive interface.
iQud transformed our fintech platform with their exceptional web app development services. They built a secure, user-friendly app.
The iQud team is extremely hardworking and understood all of our needs, they got the job done immediately. Overall very happy working with them.
iQud took time to really understand our project before diving in. Their work was done in a timely manner and exceeded our expectations.
Our logistics company was struggling with manual data entry and repetitive tasks that consumed valuable time and resources.
Frequently Asked Questions
The predictive model reached about 86% accuracy versus lab-tested HbA1c results, enabling paperless, real-time risk scoring during outreach camps and OPD surges without waiting on traditional lab turnaround.
Yes. The solution processed 1,000+ patients per day in screening camps and enabled early intervention for roughly three in ten high-risk users, ideal for preventive healthcare programs.
Plug-and-play APIs connect the scoring workflow into current EMR processes so clinicians can act on risk scores without rebuilding their clinical systems.
Encryption, anonymization, and compliance checks were built in so hospitals could deploy AI risk scoring while meeting patient-data privacy requirements.
Diagnostic backlog fell by about 45% during peak OPD periods because instant, paperless scoring identified high-risk patients earlier and prioritized follow-up care.
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