CRM SaaS Solution for a Growing E-commerce Platform
- E-commerce
- Saas
EHR SaaS Solution for a Multi-Hospital Healthcare Network
An Electronic Health Record (EHR) software was implemented to enhance patient management, streamline data tracking, and ensure compliance with healthcare regulations across a network of hospitals. The cloud-based solution enabled real-time access to patient records, improved care coordination, and optimized administrative workflows, driving better health outcomes and operational efficiency.
Industry
Healthcare
Client Location
United States
Project Duration
16 months
Team Size
35 members
Key Technologies
AWS, Kubernetes, React.js, Node.js, MySQL, AI/ML, HIPAA Compliance, Power BI
Client Background
The client is a healthcare network consisting of 15 hospitals across the United States, serving millions of patients annually. Established over 50 years ago, the network has grown to include specialty hospitals, urgent care centers, and outpatient facilities. Despite their growth, the hospitals faced challenges with disparate systems and outdated technologies, limiting their ability to efficiently manage patient records and comply with evolving healthcare regulations.
Project Scope of EHR SaaS for Healthcare Network
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Centralized Patient Management: Implementation of a unified platform for storing and managing patient records across all facilities in the network.
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Real-time Data Tracking: Ability to monitor patient progress, track treatments, and update records in real time.
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Compliance with Healthcare Regulations: Ensuring compliance with HIPAA and other healthcare regulations through data encryption and secure access control.
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Cloud-based Infrastructure: A scalable cloud solution that allows seamless access to data for healthcare professionals, regardless of location.
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Integration with Medical Devices:The system connects with medical devices and wearables to automatically input health data into patient records.
Our Approach
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Market Research and Planning
- A thorough analysis of the healthcare industry’s regulatory landscape and technological needs.
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Agile Development
- Modular development with continuous feedback loops from hospital administrators and healthcare professionals.
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AI Integration
- Predictive analytics for patient outcomes and automated diagnosis support using machine learning algorithms.
AI Features Introduced in EHR SaaS Solution
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Predictive Health Analytics
- AI models provide early warnings for potential health risks based on historical data and real-time updates.
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Automated Diagnosis Suggestions
- The system offers diagnostic suggestions based on patient symptoms, improving decision-making for healthcare providers.
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Patient Data Anomaly Detection
- Machine learning algorithms detect anomalies in patient data, flagging potential errors or inconsistencies in records.
Addressing Challenges Faced by the Healthcare Network
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Fragmented Data Systems
- The network was using different patient management systems across hospitals, causing delays in accessing crucial patient information.
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Manual Record-Keeping
- Outdated systems required manual entry of patient data, leading to errors and inefficiencies.
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Regulatory Compliance
- The client needed to ensure HIPAA compliance and protect patient data against potential breaches.
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Scalability Issues
- As the network expanded, the legacy systems struggled to handle the increased volume of patient data.
EHR SaaS Solution Business Impact
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30% Improvement in Patient Care Efficiency:Real-time access to patient data allowed healthcare providers to make faster and more informed decisions.
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40% Reduction in Administrative Costs:Automation of administrative workflows and patient record management reduced manual tasks.
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25% Improvement in Regulatory Compliance: Built-in compliance features ensured that all patient data adhered to HIPAA standards, reducing the risk of regulatory penalties.
Project Milestones We Achieved
| Milestone | Tasks | Timeline | Responsible |
|---|---|---|---|
| Project Initiation | – Define project scope, stakeholder engagement, project planning | Month 1 | Project Manager |
| Requirements Gathering | – Conduct business analysis, gather functional and technical requirements | Month 2-3 | Business Analysts |
| System Design | – Design EHR system architecture, develop data models, and database schema | Month 3-4 | Solution Architect |
| Development | – Develop core EHR modules, implement AI-based predictive models, integrate cloud services | Month 4-10 | Development Team |
| Testing and QA | – Perform unit, integration, and user acceptance testing, ensure compliance testing | Month 7-12 | QA Team |
| Training and Documentation | – Create user manuals and conduct training sessions for healthcare professionals | Month 10-13 | Training Team |
| Deployment and Go-Live | – Final data migration, go-live planning, post-launch monitoring and support | Month 13-16 | IT Team, Project Manager |
