ABDM-Compliant Hospital Management Software

Executive Summary

About Client

ABDM-Compliant Hospital Management Software for all-size hospitals.

 
Ekanshi Solutions Pvt Ltd offers expert management consultation services to healthcare organizations. They provide strategic guidance and support to help organizations achieve their goals. With the in-depth expertise and industry knowledge, they help organizations optimize their operations, make informed decisions, and achieve excellence in patient care.

 

https://ekanshisolutions.com/
Location: Lucknow, Uttar Pradesh, India

Project Background

Ekanshi Solution requires reviewing its clients’ hospitals and clinics to ensure they meet the compliance requirements. To achieve this, we recommended developing a software solution that meets the basic compliance requirements and also eases the operational burden on hospitals.

  1. Registration and demographic data collection.
  2. Patient history and medical record management.
  3. Appointment scheduling and reminders.
  4. Patient check-in and waiting list management.
  5. ABDM Compliance M1  , M2 and M3 scenarios therefore create Verify ABHA and to manage patients records

Scope & Requirement for ABDM-Compliant Hospital Management Software

In the 1st Phase of custom application development, we discussed the implementation as follows:

  • A customized app, furthermore, helps to generate ABHA ID and integrates ABDM-compliant APIS 
  • The client hospital team should be able to view patient records easily and receive and send to the central server
  • Able to book appointments and moreover schedule reminders easily. 
  • We would create a Web version of the app to help manage the above functionality, which will replace the current paper-based and unorganized work the admin was doing. 

Implementation

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Technology and Architecture of Hospital Management Software

Read more on the technology and Architecture we used for AWS Custom Application Development using ESRI ArcGIS.

Technology/ Services used

The web app was deployed with the below technological component

  • Backend Code: .NET Core, C#
  •  Web App code: AngularJS
  • Database: PostgreSQL
  • Cloud: AWS

Integrations:

  • Google APIs 

  •  ABDM Integration

  • Auth0

  • SendGrid

Security:
  • AWS WAF service is used for the firewall
  • All API endpoints are token-based

Scalability

  • The application is designed to be running on serverless services so that it can easily scale up and down automatically based on usage. 

Backup and Recovery

  • Additionally, Automated backups are configured to backup the database and store multiple copies of the backup. 

Cost Optimization 

  • Alerts and notifications are configured in the AWS to notify if the budget is being exceeded. 
  • Deployed on serverless infrastructure, the application does not incur any additional costs when it is not in heavy use.
  •  Peritos, being a cloud partner, is managing the environment for the client, keeping a close watch on the cost, and finding ways to optimize the same 

Code Management, Deployment

  • CI/CD is implemented to automatically build and deploy any code changes

Features of the Application

  • Integrated Patient Profile with NDHM: This application seamlessly integrates with NDHM, enabling the swift creation of ABHA IDs and facilitating the exchange of patient health data. By interfacing with the National Digital Health Mission, the system ensures that patient data is standardized, up-to-date, and easily accessible, fostering more informed medical decisions.
  • Multi-tenancy Architecture: The system’s ability to cater to multiple hospitals or health providers under a single unified platform is a significant advantage. Each hospital can manage its operations while benefiting from centralized updates and features, ensuring scalability and simplifying administrative tasks.

Challenges in implementing ABDM Compliant Hospital Management Software

  • Integration with ABDM APIs is needed to achieve compliance; however, the API documentation was not up to date. Also, the API versions keep checking. During the app development from v1 to V3, we had to reach the APIs and perform code refactoring to ensure the utilization of the latest set of APIs.
    • Furthermore, Help from PWC team was provided and explained the API endpoints and the test scenarios to cover to ensure the app compliance checks can be passed. 
  • Testing of the application with multiple end users who were experts in their domain was a challenge.
    • We found the data quite complicated to understand and relied on the client’s team to test and inform us about the expected result in case of any issues. Additionally, we identified key users such as doctors, administrators, nurses, department heads, etc., to ensure coverage of all user scenarios.
  • Given the sensitive nature of medical data, ensuring robust security measures against breaches and unauthorized access is paramount.
    • The hospital management application ensured data security and privacy through end-to-end encryption for both data at rest and in transit. AWS’s suite of security tools, including IAM for access control, KMS for key management, and VPCs for network isolation, were leveraged. We fortified the APIs with security tokens and rate limiting and conducted regular training sessions for staff on security best practices.

Project Completion

Duration of Hospital Management Software Implementation

Jan 2023 – Dec 2023 ~ 1 year   months 1st Version 

June 2024 – Present Currently working on Reporting, Enhancements, and Billing , In patient and Out patient feature addition along with M2 Billing

Deliverables for ABDM-Compliant Hospital Management Software

Setting up the AWS environment for the client system

• Custom web application for two environments production and UAT system 

• We delivered the features as agreed in the scope 

  1. Registration and demographic data collection.
  2. Patient history and, furthermore, medical record management.
  3. Appointment scheduling and reminders.
  4. Patient check-in and waiting list management.
  5. ABDM Compliance M1, M2, and M3 scenarios to create Verify ABHA and to manage patients records
  6. We developed the following set of core features. 
    User: Manages user registration, authentication, roles, and permissions.
    Hospital: Multi-tenant application to handle hospital registration, department management, and related configurations.
    Doctor: Manages doctor profiles, availability, specialties, and associated scheduling.
    Patient: In addition, Interfaces with ABDM for patient data operations, ABHA ID creation, and retrieval of patient health history.

Support

  • As part of the project implementation we provide 2 months of Ongoing extended support.
  • This also includes 20 hrs a month of development for minor bug fixes and an SLA to cover any system outages or high-priority issues.

Testimonial

After working for 6 months on the project, we took feedback from the Product owner whom we have worked closely for project execution:

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Peritos and using AWS have been instrumental in transforming our hospital’s operations for clients. It empowered us to create a custom multi-tenant application that not only meets our current needs but also positions us for future growth and innovation to showcase this to our larger client base and prospects. With a solid system now, we have the confidence to continue our mission of providing exceptional healthcare services to our community, knowing that our technology backbone is secure, reliable, and ready to scale. Additionally, We are happy with the services and look forward to completing more projects in the future with Peritos team.

Akanksha Niranjan
OWNER, EKANSHI SOLUTIONS

Next Phase

We are now looking at the next phase of the project which involves:

1. Furthermore, Ongoing Support and adding new features every Quarter with minor bug fixes

2. Electronic Medical Records (EMR) Integration: Incorporate a system that not only stores patient data but also tracks their entire medical history, including medications, allergies etc

3. AI-Powered Predictive Analysis: Moreover, Use AI and machine learning to analyze patient data for potential health risks, helping doctors make informed decisions

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