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Development of a Web-Based Clinical Insights and Medication Recommendation Portal for Hypertension Treatment
  1. case
  2. Development of a Web-Based Clinical Insights and Medication Recommendation Portal for Hypertension Treatment

Development of a Web-Based Clinical Insights and Medication Recommendation Portal for Hypertension Treatment

buildableworks.com
Medical
Healthcare

Challenges in Hypertension Management and Data Utilization

Healthcare providers managing patients with hypertension face difficulties in prescribing optimal medications due to varying patient health data, including vital signs and lab results. Manual analysis can be time-consuming and prone to oversight, complicating timely treatment adjustments. There is a need for an integrated system that consolidates patient data and provides actionable medication recommendations to improve patient outcomes and streamline clinical workflows.

About the Client

A mid-sized healthcare organization specializing in chronic disease management, seeking to enhance clinical decision-making through data-driven insights.

Goals for an Intelligent Hypertension Treatment Support System

  • Develop a web-based portal to visualize patient health data relevant to hypertension management.
  • Implement an algorithm to generate medication recommendations based on patient vitals, labs, and current clinical guidelines.
  • Enable seamless integration with existing Electronic Health Record (EHR) systems to automate data upload and retrieval.
  • Ensure compliance with healthcare data privacy regulations through secure role-based access and automatic session timeouts.
  • Deliver real-time, actionable insights to healthcare providers to facilitate prompt treatment modifications.

Core Functionalities for Hypertension Treatment Decision Support

  • Patient Data Dashboard: Visual display of vital signs, lab results, and historical health data.
  • Medication Recommendation Engine: Algorithm that analyzes patient data to suggest effective antihypertensive medications and dosing adjustments.
  • Data Integration Layer: Automated upload and synchronization with EHR systems via APIs (e.g., Epic integration).
  • User Role Management: Role-based permissions ensuring secure access and editing rights for healthcare providers.
  • Security Measures: Automatic timeout after inactivity, audit logs, and HIPAA-compliant data handling.
  • Notification System: Alerts for abnormal patient vitals or lab results requiring immediate attention.

Preferred Technology Stack and Architectural Approaches

.NET Core for backend development
Entity Framework for ORM
SQL Server for data storage
RESTful API architecture
Secure authentication protocols
Client-side frameworks facilitating fast, responsive interfaces

Essential External System Integrations

  • Electronic Health Record systems such as Epic for automated data import/export
  • Health data exchange platforms (e.g., Redox) for interoperability
  • Medical device interfaces (e.g., Omron) for vitals data collection

Critical Non-Functional System Requirements

  • Scalability to accommodate increasing patient data and user base over time
  • High performance with system response times under 2 seconds for data visualization
  • Strict security measures ensuring HIPAA compliance, including data encryption and role-based access controls
  • Automatic session timeouts to prevent unauthorized access
  • Reliable data synchronization with external systems for real-time updates

anticipated Business Benefits and Success Metrics

This portal is expected to enhance the accuracy and timeliness of hypertension treatment decisions, leading to improved patient outcomes. By automating data analysis and recommendations, healthcare providers can reduce decision-making time and minimize medication errors. The system aims to increase treatment consistency with clinical guidelines, ultimately improving patient blood pressure control rates and reducing hospital visits related to hypertension. Deployment is projected to support healthcare providers more efficiently, with measurable improvements in treatment accuracy and workflow efficiency.

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