Revolutionizing healthcare: unleashing the power of AI for enhanced operations and
About our Customer
Our esteemed customer is a pioneering entity in the healthcare industry, known for its commitment to delivering
cutting-edge medical services and personalized care to patients. However, like many healthcare organizations, they
faced numerous challenges that impeded their full potential in providing optimized patient care and operational
Before implementing the digital solution with integrated AI, the healthcare client faced the following challenges:
Manual and time-consuming manual processes
Inefficient supply chain management
Limited visibility and access to patient records
Workforce scheduling and resource allocation issues
Reactive maintenance of equipment
These challenges prompted the healthcare client to seek a solution that could automate and optimize processes,
improve inventory management, enhance access to patient records, optimize workforce scheduling, and enable proactive
maintenance of equipment.
The primary objectives of implementing the digital solution with integrated AI for our healthcare client were:
Enable personalised patient care through data-driven insights and treatment recommendations.
Optimise workforce scheduling to minimise staffing gaps and enhance resource allocation.
Implement predictive maintenance and equipment optimization for enhanced equipment performance and cost savings.
Improve supply chain management by optimizing inventory levels, reducing waste, and minimizing stockouts.
KoreCent designed and implemented a comprehensive digital solution with integrated AI technology. The solution
comprised the following components:
Personalized Patient care
The integrated AI technology empowered our healthcare client to deliver personalized patient care, tailoring
treatment plans and services to individual patients based on their unique needs, preferences, and medical history.
i. Data-driven treatment recommendations
The solution utilized AI algorithms to analyze large volumes of patient data, including medical records, test
results, genetic information, and treatment outcomes. By mining this data, the solution identified patterns,
correlations, and insights that healthcare professionals could leverage to make more informed treatment decisions.
the AI algorithms provided data-driven treatment recommendations and options, taking into account factors such as
the patient's medical history, genetic markers, and response to previous treatments.
ii. Precision medicine
The AI technology facilitated precision medicine approaches by identifying patient-specific characteristics that may
influence treatment effectiveness. By considering genetic factors, biomarkers, and other personalized data, the
solution helped healthcare professionals develop tailored treatment plans and interventions. This personalized
approach maximized treatment efficacy while minimizing potential side effects or adverse reactions.
iii. Risk stratification and early intervention
The solution enabled risk stratification by predicting patient-specific risks and complications based on their
medical history, lifestyle factors, and other relevant data. By identifying high-risk individuals, healthcare
professionals could implement proactive interventions and monitoring strategies to mitigate risks and detect
potential health issues at an early stage. This approach supported preventive care and early intervention, leading
to improved patient outcomes and reduced healthcare costs.
iv. Patient engagement and empowerment
The AI-powered solution empowered patients to actively participate in their own care through enhanced engagement and
education. It provided personalized health information, educational resources, and real-time feedback on treatment
progress. Patients could access their medical records, track their health metrics, and communicate with healthcare
providers through user-friendly portals or mobile applications. This increased patient engagement, improved
adherence to treatment plans, and fostered a collaborative relationship between patients and healthcare
AI-driven workforce scheduling
The AI-driven workforce scheduling component implemented by Korecent revolutionized the way our healthcare client
managed their workforce. By harnessing the power of AI and predictive analytics, the solution provided advanced
capabilities for optimizing workforce scheduling and resource allocation.
i. Dynamic scheduling
Unlike traditional manual scheduling methods, the AI-driven solution dynamically adjusted schedules in real-time
based on changing conditions. It considered factors such as patient demand, staff availability, skillsets, and
workload distribution to optimize shift assignments and ensure appropriate coverage.
ii. Staff preferences and constraints
The AI-driven solution also took into account individual staff preferences and constraints when generating
schedules. It considered factors such as preferred working hours, time-off requests, and regulatory requirements,
ensuring that the schedules aligned with both staff needs and operational requirements.
iii. Skill-based resource allocation
Recognizing the importance of assigning the right staff with the appropriate skillset, the solution incorporated
skill-based resource allocation. It matched staff members' qualifications, certifications, and experience with the
specific requirements of each shift or task, optimizing resource utilization and improving the quality of care
iv. Real-time updates and notifications
To keep all stakeholders informed and ensure smooth communication, the AI-driven solution provided real-time updates
and notifications. Staff members received automated notifications regarding their assigned shifts, any schedule
changes, or requests for shift coverage. This streamlined communication minimized confusion and improved overall
v. Performance monitoring and optimization
The AI-driven workforce scheduling component also facilitated performance monitoring and optimization. It provided
analytics and reports on staff performance metrics, such as productivity, attendance, and adherence to schedule.
This data-driven insight enabled managers to identify areas for improvement and make data-informed decisions to
enhance workforce productivity and efficiency.
Predictive maintenance and equipment optimization
The integrated AI technology also facilitated predictive maintenance and equipment optimization, ensuring the
healthcare organization's equipment and medical devices were operating at peak efficiency.
i. Real-time data monitoring
The solution continuously monitored real-time data from medical equipment and devices, collecting information on
performance metrics such as temperature, pressure, and usage patterns. This data was analyzed by AI algorithms to
identify anomalies, detect potential issues, and predict maintenance requirements before equipment failures
ii. Proactive maintenance scheduling
Based on the insights gathered from the data analysis, the solution generated proactive maintenance schedules. It
predicted when specific equipment or devices would require maintenance, enabling healthcare staff to schedule
repairs or servicing during planned downtime, minimizing disruptions to patient care.
iii. Optimal resource utilization
The AI algorithms analyzed equipment utilization patterns to identify underutilized or overutilized assets. This
information allowed the healthcare organization to optimize resource allocation, ensuring that equipment was
efficiently distributed across different departments and facilities. By identifying redundant or underutilized
assets, the organization could make informed decisions about equipment replacement or redistribution.
iv. Equipment performance analytics
The solution provided comprehensive analytics on equipment performance, including metrics such as uptime, downtime,
and mean time between failures (MTBF). These insights allowed healthcare administrators and technicians to monitor
the performance of equipment, identify trends, and make data-driven decisions on equipment maintenance, upgrades, or
Smart inventory control
The integrated AI technology revolutionized inventory management for our healthcare client, enabling them to
optimize inventory levels, improve accuracy, and streamline inventory control processes.
i. Real-time inventory monitoring
The solution provided real-time monitoring of inventory levels and stock movements. By integrating with various data
sources such as point-of-sale systems, electronic health records, and supply chain databases, the AI algorithms
continuously tracked inventory quantities and locations, ensuring up-to-date visibility and accuracy.
ii. Demand forecasting and inventory optimization
utilizing advanced machine learning algorithms, the solution analyzed historical data, including patient flow,
seasonal trends, and supply chain information, to accurately forecast future demand. By leveraging these insights,
our healthcare client could optimize inventory levels, reducing excess stock and minimizing the risk of stockouts.
The AI algorithms automatically adjusted inventory levels based on demand fluctuations, ensuring optimal stock
levels at all times.
iii. Automated reordering and Supply Chain Integration
The smart inventory management solution automated the reordering process by integrating with suppliers and supply
chain systems. when inventory levels reached predetermined thresholds, the system generated automated purchase
orders or replenishment requests. this streamlined the procurement process, reducing manual efforts and minimizing
the risk of human error in inventory replenishment.
i. Enabled personalized patient care through data-driven insights and treatment recommendations, leading to improved
patient outcomes and increased satisfaction.
ii. Optimized workforce scheduling, minimizing staffing gaps and enhancing resource allocation, resulting in
improved operational efficiency and reduced costs.
iii. Implemented predictive maintenance and equipment optimization, enhancing equipment performance, reducing
downtime by 20%, and generating cost savings.
iv. Improved supply chain management by optimizing inventory levels, reducing waste by 40%, and minimizing stockouts
by 15%, resulting in streamlined operations and cost savings.
v. Solution implemented minimised time spent on routine, administrative tasks, which was taking 70 % of a healthcare
The healthcare client experienced tangible benefits in terms of cost savings, operational efficiency, and improved
patient outcomes, solidifying their position as a leader in providing advanced and personalized healthcare services.