Healthcare

Integrated Care Solutions (ICS)

AI-based readmission prediction service integrated into ICS’s clinical platform.

$8M

Savings during 3-month observation period

32%

Drop in readmissions within 90 days of pilot rollout

84%

Of flagged high-risk patients

Case Studies

Integrated Care Solutions (ICS) – Dubai-based digital health company focused on enhancing patient outcomes and care coordination.

Healthcare

Industry

Dubai

Location

AI Software Development, Predictive Analytics, MLOps & Model Deployment, Frontend & Backend Engineering

Services

$180,000

Budget

Challenge

ICS needed an automated, explainable, and integrated solution to identify at-risk patients in real time and support personalized interventions.

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Outcomes We Deliver

Solution

We developed and deployed an AI-based readmission prediction service integrated into ICS’s clinical platform. The system uses 6 years of patient history and real-time episode data to assign readmission risk scores at 3 stages of the care journey.

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Dalriada
Tech Stack

To developed and deployed an AI-based readmission prediction service, Blackthorn AI applied a production-grade tech stack including:

Python
TypeScript
XGBoost
Docker
Azure
SQL
Pandas
Roadmap

Project duration

01-02 Weeks

Goal Alignment & Data Audit

Validated business objectives with clinical stakeholders, conducted high-level audit of available patient records, defined initial scope and KPIs for prediction accuracy and response time.

03-04 Weeks

Data Infrastructure & Compliance Prep

Mapped data schemas across historical and real-time sources (EHR, episode data, notes), established secure access protocols, and ensured compliance with privacy and clinical data regulations.

05-06 Weeks

Exploratory Analysis & Feature Engineering

Performed in-depth data profiling, identified key predictors of readmission, handled imbalanced classes, and engineered structured + time-series features from up to 6 years of data.

07-08 Weeks

ML Modeling & Risk Stratification Logic

Developed and tuned predictive models using XGBoost and logistic regression, implemented logic to assign patients into three actionable risk categories based on outcome likelihood.

09-10 Weeks

Model Evaluation & Clinical Validation

Benchmarked model performance (accuracy, precision, recall), tested outputs with ICS care teams, and built early explainability features for nurse-facing decisions.

11–13 Weeks

MLOps & API Architecture

Deployed models in a containerized pipeline (CI/CD), designed a standalone prediction API with retraining triggers, enabled secure integration into ICS backend and web dashboard.

14–16 Weeks

Frontend Integration & Release

Integrated model output into production frontend, finalized UX for nurses and clinicians, automated model training with new data, and released live MVP for evaluation across active patient flows.

Team Size

5 team members from Blackthorn.ai
1 x AI Solutions Architect
1 x Data Scientist
1 x Data Engineer
1 x MLOps Engineer
1 x Frontend & Backend Developers

Delivering Impact

Beyond the values already highlighted, there’s even more to discover. Our commitment to innovation, client success, and impactful results sets us apart

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32%

Drop

In readmissions within 90 days of pilot rollout

$8M

Savings

During 3-month observation period

84%

Of flagged high-risk patients

Actually readmitted – enabling targeted care

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