Prev Mama Mia: A platform to connect patients with healthcare experts.

Prev Mama Mia is a healthcare business facilitating consulting, communications, and outreach for women in Sweden to expert “midwives”(doctors).  The main objective of Prev Mama Mia was to build a platform that enables patients to connect with healthcare professionals

• The most significant challenge for the client was providing patients with easy access to communication with different healthcare professionals.
• Ensuring the security and compliance of sensitive patient data stored in the database and managing compliance with regulations like HIPAA was a challenge.
• Setting up comprehensive data monitoring, managing regular system maintenance, and ensuring high availability of services was complex.
• Managing the infrastructure costs associated with data storage and communication services was a significant challenge.
• Developing effective communication features to connect patients with doctors, recording sessions, and ensuring patient data management needed effective solutions.

• Simform developed and implemented features to connect patients with doctors, record sessions, and manage patient data securely.
• To ensure the security and compliance of patient data and regulatory adherence, Simform implemented robust access controls, encryption mechanisms, and regular security audits using AWS WAF.
• Simform designed a comprehensive architecture leveraging containerization and enabled infrastructure management with multiple AWS services like Amazon ELB, Auto Scaling Groups, and Amazon ECS.
• Our team integrated Amazon Chime, enabling effective communication between patients and healthcare professionals through chat, audio, and video calls.
• We set up comprehensive data monitoring and alerting using AWS CloudWatch to manage regular system maintenance and maintain high service availability effectively. 
• Our team of experts included prudent management of infrastructure costs associated with data storage and communication services by optimizing AWS services usage.
• We implemented cost-effective storage strategies within Amazon S3 and Amazon RDS.
• Our team used AWS CloudFront as a CDN to enable edge location caching for faster patient content delivery.

• We improved security by 50% and achieved GDPR compliance through access controls, encryption, and regular audits.
• Using AWS CloudWatch, we achieved a 60% improvement in data monitoring and system maintenance efficiency
• Our team reduced infrastructure costs by 30% through AWS optimization and cost-effective storage strategies.
• Simform achieved a 55% improvement in maintaining high service availability by using Amazon ELB, Auto Scaling Groups, and Amazon ECS.

• AWS CloudWatch: We used AWS CloudWatch for log collection, alarms, and resource visualization for all AWS services on the account.
• AWS Cloudfront: Our team leveraged AWS CloudFront as CDN to provide end users with edge location caching for low-latency content delivery.
• AWS WAF: We used AWS WAF to protect the application from bot attacks, SQL Injection, DDoS attacks, Windows PowerShell & Linux LFI attacks.
• Amazon Chime: With the Amazon Chime SDK, our experts added real-time voice, video, and messaging powered by machine learning into their applications.
• Amazon Elastic load balancer: We leveraged Amazon ELB to enhance the availability and fault tolerance of the platform by distributing incoming traffic across multiple targets.
• Amazon ECS: Our team used Amazon ECS to offer a highly scalable containerized environment to run applications.
• Auto Scaling Group: We used Auto Scaling Group to manage the server scaling algorithms for the ECS cluster.
• Amazon S3: We leveraged Amazon S3 for static data storage for application artifacts data.
• Amazon Pinpoint: Our team of experts used Amazon Pinpoint to send end users push and in-app notifications.
• Amazon RDS: We used Amazon RDS to support different SQL servers like MSSQL, MySQL, and PostgreSQL.
• AWS Code pipeline: Our team leveraged the AWS Code pipeline to provide capabilities to create CICD pipelines to automate the application build and deployment.
• AWS Codebuild: We used AWS Codebuild to create dockerized application builds for deployment in a containerized environment.
• AWS Codedeploy: Our experts leveraged AWS Codedeploy to deploy the newly created application build to the ECS cluster without downtime.