BDMS aims to be a leader in providing internationally accepted, efficient, and ethical high-quality care through a dedicated healthcare team, effective leadership, and up-to-date technology. To achieve that vision, the group needs to continually improve its management system and services by emphasizing ongoing quality improvement throughout the organization. Maintaining a constant focus on keeping up with the rapid pace of technology development is integral to delivering on these goals.

Four years ago, Monvalee Phathanothai, who was then Managing Director of GLS, started looking at how to build on BDMS’ vision and mission of improving services and support from a different perspective. Due to rapid growth of BDMS’ network, the recurring theme she encountered was the opportunity for better access to, and use of, data. The need for interoperability was already paramount and proved even more so several years later when COVID-19 hit. This led her to build the case for data-driven digital transformation as the next step in the network’s evolution.

According to Phathanothai, now Chief Data Officer of GLS, to achieve digital transformation they needed to start with the integration of fragmented data and siloed systems for them to become interoperable and shared on a standardized platform. This would then provide reliable information and knowledge for quality and comprehensive healthcare services.

“To move forward on our mission, we needed a solution to unify the entire hospital network with a digitized information platform to get a single view of the massive and complex data set for patient and business analysis as well as medical research,” said Phathanothai.

Phathanothai's team, mentored by Dr. Michael McCoy, then BDMS Chief Medical Information Officer, was tasked with evolving the group’s existing information systems into a platform that would be a single repository and interface for all hospital data. It would be known as the Hospital Management System (HMS), a strategic program to enable the exchange of patient records across BDMS hospitals.

One of the first and most strategic technology choices was the underlying data infrastructure. Tinnarat Aromsuk, Director of Enterprise Data Architecture, led this part of the initiative. His team initially tried to rebuild the HMS Open Health Platform version 1.0 on a relational database. However, after nearly a year of trying, Aromsuk realized that the unstructured nature of their data would never fit efficiently into a relational database, so he went looking for an alternative.

Aromsuk described his vision as seeking a modern real-time healthcare platform that was highly interoperable with all their other systems. Beyond a database that could handle a huge variety of data types, the team had four other important criteria their infrastructure needed to support:

• Enterprise grade security and ability to comply with exacting healthcare regulations
• Excellent scalability and easy for developers to use
• Fast speed to market and ability to help GLS ship features quickly
• A great, responsive experience for application users

They found what they were looking for in MongoDB Atlas.

“MongoDB’s document model helped us quickly figure out that there was no way a relational database was going to work for us. We had so many different types of data and documents spread across the hospital network. Using Opensource RDBMS was not only far too complicated but presented risk with performance issues and would not allow us to scale in the way MongoDB does,” said Aromsuk.

Using MongoDB, they were able to build the prototype software platform in just a few months. But this was only the first step. GLS was looking to a cloud-based future strategy for the hospital’s system to support its data needs as well as requirements for ongoing scalability, innovation, and enhanced security. So, when the application was ready to go into production, GLS made the simple move from MongoDB running on-premises to MongoDB Atlas, the cloud database service, which was deployed on AWS.

MongoDB Atlas gave GLS the same great underlying flexibility and scalability of the document model as well as the added advantages of a fully managed cloud service.

This helps ensure the group adheres to the highest global security and compliance standards meeting HIPAA and ISO2020, which is paramount to protecting patient data privacy and safety. Using MongoDB Atlas also helps GLS with operational tooling and management so that their development team can better monitor the deployment, spend more time building new features and not managing the database.

“One of the most compelling features we appreciate now is how Atlas modernizes and speeds up our development, making it simple to manage such a complex deployment,” said Aromsuk.

The GLS team are also focused on improving and speeding up their analytics capabilities. They are already taking advantage of MongoDB's aggregation pipeline to do analytical queries within the database. This will expand as the group has a growing need for more sophisticated data analysis.

By mid-2021, the HMS Open Health Platform V2.2 was released to improve real-time integration incorporating several different hospitals' information systems, such as Arcus Air. To date, 15 hospitals have successfully migrated from the legacy hospital information system to Arcus Air, which is also run on MongoDB. Those are fully integrated with the HMS V2.2 Platform.

In just three years, the transformation has been implemented across more than 15 hospitals enabling information exchange and improving the healthcare journey for around five million patients.

The BDMS team reports a greatly improved experience for patients, clinicians, carers and for the hospital group itself. The hospital now has much better access to its data enabling improved decisions and planning. A simple example of how the information exchange works is when pharmacist and cashier are now automatically alerted if a patient’s medication state gets changed, meanwhile both personas are using different add-on applications within the core hospital information system.

The transformation, which began in 2018, also helped reduce cost within the IT department and significantly increased the speed with which the development team can scope and shape new futures. The hospital network is also now even more resilient and was able to continue delivering quality healthcare throughout the pandemic.

The transformation has also been timely as Thailand’s Ministry of Health is setting out a new vision to achieve a more unified approach to handling patient and healthcare data.

Underlying these successes is the proven scalability, usability, and security of their managed data infrastructure. Aromsuk experienced an example of how important scalability is when an operational input error caused CPU consumption to massively increase in just a few minutes. With the previous system, it would have resulted in a crash and down time, but with MongoDB Atlas in place everything scaled up seamlessly, he explained. The team identified, then fixed, the issue and the infrastructure scaled back down.

The hospital transformation is still in its early phases and is rapidly fueling the group’s appetite for ongoing innovation. There are big plans on the horizon. The HMS Open Health Platform continues improving application user’s experiences and GLS is in the process of migrating the integration of 35 existing applications from on-premises relational database to real-time APIs, which has MongoDB Atlas as the core database.

GLS have planned to further enable the HMS using Atlas App Services, which can sync data effortlessly between MongoDB Atlas and a mobile device, as well as natively incorporating services including triggers, functions, and Graph Query (aka GraphQL) for a rich mobile experience.