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Development of an Advanced Electronic Health Record System for Healthcare Providers
  1. case
  2. Development of an Advanced Electronic Health Record System for Healthcare Providers

Development of an Advanced Electronic Health Record System for Healthcare Providers

snotor pro
Medical
IT

Identifying Clinical Data Management and Security Challenges in Healthcare Organizations

Healthcare providers face significant challenges in managing, securing, and sharing patient data across multiple clinics and hospitals. Ensuring data security, providing personalized user experiences, and maintaining compliance with industry standards such as HIPAA are critical pain points. Additionally, ensuring seamless access via personalized portals for various clinics remains a complex task without tailored solutions.

About the Client

A midsize healthcare organization comprising multiple clinics and hospitals seeking an integrated, secure electronic health record platform to enhance operational efficiency and patient care.

Goals for Implementing a Secure, Customizable EHR Platform

  • Design and develop a comprehensive electronic health record system that enables efficient composition, storage, and sharing of medical data including symptoms, appointments, and assessments.
  • Implement multilevel administration and access controls to ensure data security and compliance, allowing only one user session per account at any time.
  • Create a personalized experience for each healthcare facility by supporting subdomains or branding customizations.
  • Enable automated document generation based on clinical assessments and diagnoses.
  • Incorporate intelligent algorithms to assist healthcare professionals in diagnostic hypotheses based on entered data.
  • Deploy a scalable, secure platform capable of supporting both small clinics and large hospital networks.

Core Functional Features for the Custom EHR System

  • Multilevel administration panel for managing access rights and system configurations.
  • Template creation for recording patient complaints and primary assessment details, sortable by anatomical regions.
  • Automated generation of patient documents required post-assessment.
  • Decision support algorithms to aid diagnosis based on input symptoms and examination results.
  • Secure user session management limiting to one active session per user to ensure data security.
  • Subdomain-based customization for different clinics, including branding and settings.
  • Dashboard for secure and convenient management of medical data.

Technology Stack and Architectural Considerations for the EHR Platform

Ruby on Rails for backend development
JavaScript and React for frontend interface
PostgreSQL database for reliable data storage
CSS3 and HTML5 for UI/UX design
Implementation of scalable architecture with security best practices

Necessary External System Integrations

  • Secure authentication mechanisms aligned with healthcare standards (e.g., OAuth2, LDAP)
  • Integration with hospital management systems for seamless data exchange
  • Compliance modules for auditing and reporting

Essential Non-Functional System Attributes

  • Data security compliant with HIPAA and industry standards
  • Single-session enforcement to prevent simultaneous logins
  • High availability and scalability to support growing user base
  • Responsive UI ensuring usability across devices
  • Performance optimized for real-time data access and processing
  • Extensible architecture to incorporate future features

Anticipated Business Benefits and Outcomes

The implementation of this advanced, secure, and personalized EHR system is expected to streamline clinical workflows, reduce administrative overhead, and enhance patient data security. By providing tailored portals for each clinic, the system will improve user engagement and satisfaction. The decision support algorithms aim to increase diagnostic accuracy, ultimately elevating the quality of patient care. The scalable platform could enable healthcare organizations to increase patient throughput and operational efficiency, leveraging automation and improved data management practices.

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