In this case study, using TAS Platform as an example, we explain why a simple website, corporate mobile app, or even the development of several separate software products are often insufficient for full-scale digital business transformation.
In 2017, we worked with the American medical company NextMed, which is located in Arizona. They are addressing the issue of kidney stones and offering a comprehensive solution for it. For them, we created an entire software ecosystem called the TAS Platform, which I'll describe in more detail.
NextMed is a modern medical company that advocates evidence-based methods in its practice. It collects statistical data, analyzes the results, constantly studies research from authoritative sources, and utilizes modern digital technologies.
The company was founded in 1996 by the sons of a urologist. They understood the difficulties faced by doctors dealing with lithotripsy. At that time, this sector was dominated by old, large companies using outdated technologies.
NextMed set a goal to provide the highest quality services using the most innovative methods. To achieve this, the company began to rely on honest research based solely on facts and to collaborate only with time-tested partners.
After 20 years, the company is proud to employ only the latest technologies in hardware and software. Thanks to Focus21, all these are connected into a single ecosystem, a key feature of which is the integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies.
In 2017, NextMed was looking for a technology partner to design, develop, and implement a comprehensive platform to support its business. The company turned to Focus21 on a recommendation and presented several complex tasks, which evolved into an entire software ecosystem.
Firstly, the company needed a platform for registering diseases, accounting for cases of kidney stone treatment using shock wave and other devices, and a statistical web trainer for the most effective training of technicians, doctors, and other personnel involved in the process.
Another important task was to create a platform for students, doctors, universities, and hospitals to compare the effectiveness of shock wave (ESWL) and laser (URS) therapy based on patient demographic data and kidney stone disease parameters.
Plus, the entire ecosystem needed to integrate systems based on Artificial Intelligence and Machine Learning. With AI and ML, it was essential to detect stones in X-ray images to remove them as effectively as possible without missing them and causing significant harm to the patient's organs.
When we start working with a new client, we first deeply immerse ourselves in all their internal business processes. Only after that do we jointly decide on a strategy. Implementing such a project requires systemic thinking and a holistic approach to assessing the company's activities.
In software development, it was important to consider the user experience, analyze a large volume of data, train artificial intelligence with it, ensure high availability, and bring the software into compliance with privacy requirements (HIPAA).
Before beginning development, a comprehensive study was conducted, including interviews with relevant technical specialists and doctors. As a result, a thought-out and implemented software ecosystem named TAS Platform was conceived and realized.
The development team was tasked with creating software so simple and intuitive that even an untrained employee could theoretically use it. This is where AI and ML-based systems were supposed to help.
Thanks to the joint efforts of Focus21 and NextMed, they succeeded in creating not just separate applications, but a true software ecosystem, comprising a full set of diverse tools necessary for the most effective treatment of kidney stones. This includes several key elements.
It's important to understand that this is far from the complete list of applications that eventually became part of the software ecosystem, which was continuously developed over several years. Many tools ultimately received integration with artificial intelligence and machine learning.
Gateway and Portal. The basic entry point into the system, which provides unified authentication across all applications implemented within the TAS Platform. This is a very flexible tool, based on intelligent mapping of capabilities according to a defined set of rights.
The control panel, which the user accesses after authentication, changes depending on the specific set of access rights they have. Meanwhile, all rights provisioning is controlled by an administrator who creates and distributes roles as needed.
Stone Decision Engine. An intelligent decision-making system that selects the treatment method: shock wave (ESWL) or laser (URS) therapy. It predicts the likelihood of success and complications based on information about the patient and data on all possible previous procedures.
For this, technologies based on artificial intelligence and machine learning are used. AI and ML facilitate a detailed analysis, ultimately allowing the development of an as effective as possible treatment system with the highest chances of success.
Simulator. A simulator that allows modeling the SWL procedure based on data from previous procedures performed for a specific patient. This helps to develop a truly effective treatment plan considering various nuances and predicting its outcome.
Vision AI. The core of the ecosystem's artificial intelligence, created for analyzing X-ray images of kidney stones. Tens and hundreds of thousands of images were processed through it, enabling the system to accurately identify the necessary objects.
The more images the system processed, the more accurate it became. A significant advantage of software interaction within a single ecosystem was the continuous receipt of new material for training during the platform's use.
TxPro. A separate desktop application created specifically for technologists. It allows not only to conduct the procedure but also to record data about patients and their body's reactions to specific impacts when using shock wave (ESWL) or laser (URS) therapy.
This tool, among other things, became an important basis for obtaining additional data necessary for artificial intelligence and machine learning. Thanks to this, the system continued to learn and improve continuously during its use.
Follow Up. After completing therapy, the treating physician schedules a follow-up appointment to check the patient's condition. Using this application, they transmit to the company information about everything that happened to the patient after treatment (e.g., possible complications during recovery).
Reports. Quarterly reports are also an important statistical tool directly for doctors and partner institutions. This tool allows comparing current values with the best indicators and, if necessary, downloading the results in a convenient format.
When considering the creation of a software product ecosystem, one should not focus only on the size of the company. There are many examples where not only large, but also medium and small enterprises choose them. It all depends on the tasks that need to be solved.
Thanks to the ecosystem, it was possible to implement common access to information, convenient division of data usage rights after authentication, a scalable structure with the prospect of further expansion, a clear overall UX for all products, and optimal cost for the project's implementation.
Of course, the implementation of artificial intelligence and machine learning technologies throughout the system would also have been impossible without using all the advantages offered by a unified ecosystem. This particularly concerns the process of the system's automatic improvement during its use.
If a company needs to automate just one specific process, narrowly focused tools are sufficient. However, if the task is to fully digitize the business, organize the proper storage of all information, and use it in different directions, an ecosystem of applications should be considered.
NextMed
NextMed
Healthcare
AWS
Docker
Electron
Flutter
GraphQL
Javascript
Python
React
Terraform
Product Strategy
Digital Transformation
Ecosystem Architecture
Software Architecture
Artificial Intelligence (AI)
Machine Learning (ML)
User Research & Testing
In this case study, using TAS Platform as an example, we explain why a simple website, corporate mobile app, or even the development of several separate software products are often insufficient for full-scale digital business transformation.
In 2017, we worked with the American medical company NextMed, which is located in Arizona. They are addressing the issue of kidney stones and offering a comprehensive solution for it. For them, we created an entire software ecosystem called the TAS Platform, which I'll describe in more detail.
NextMed is a modern medical company that advocates evidence-based methods in its practice. It collects statistical data, analyzes the results, constantly studies research from authoritative sources, and utilizes modern digital technologies.
The company was founded in 1996 by the sons of a urologist. They understood the difficulties faced by doctors dealing with lithotripsy. At that time, this sector was dominated by old, large companies using outdated technologies.
NextMed set a goal to provide the highest quality services using the most innovative methods. To achieve this, the company began to rely on honest research based solely on facts and to collaborate only with time-tested partners.
After 20 years, the company is proud to employ only the latest technologies in hardware and software. Thanks to Focus21, all these are connected into a single ecosystem, a key feature of which is the integration of Artificial Intelligence (AI) and Machine Learning (ML) technologies.
In 2017, NextMed was looking for a technology partner to design, develop, and implement a comprehensive platform to support its business. The company turned to Focus21 on a recommendation and presented several complex tasks, which evolved into an entire software ecosystem.
Firstly, the company needed a platform for registering diseases, accounting for cases of kidney stone treatment using shock wave and other devices, and a statistical web trainer for the most effective training of technicians, doctors, and other personnel involved in the process.
Another important task was to create a platform for students, doctors, universities, and hospitals to compare the effectiveness of shock wave (ESWL) and laser (URS) therapy based on patient demographic data and kidney stone disease parameters.
Plus, the entire ecosystem needed to integrate systems based on Artificial Intelligence and Machine Learning. With AI and ML, it was essential to detect stones in X-ray images to remove them as effectively as possible without missing them and causing significant harm to the patient's organs.
When we start working with a new client, we first deeply immerse ourselves in all their internal business processes. Only after that do we jointly decide on a strategy. Implementing such a project requires systemic thinking and a holistic approach to assessing the company's activities.
In software development, it was important to consider the user experience, analyze a large volume of data, train artificial intelligence with it, ensure high availability, and bring the software into compliance with privacy requirements (HIPAA).
Before beginning development, a comprehensive study was conducted, including interviews with relevant technical specialists and doctors. As a result, a thought-out and implemented software ecosystem named TAS Platform was conceived and realized.
The development team was tasked with creating software so simple and intuitive that even an untrained employee could theoretically use it. This is where AI and ML-based systems were supposed to help.
Thanks to the joint efforts of Focus21 and NextMed, they succeeded in creating not just separate applications, but a true software ecosystem, comprising a full set of diverse tools necessary for the most effective treatment of kidney stones. This includes several key elements.
It's important to understand that this is far from the complete list of applications that eventually became part of the software ecosystem, which was continuously developed over several years. Many tools ultimately received integration with artificial intelligence and machine learning.
Gateway and Portal. The basic entry point into the system, which provides unified authentication across all applications implemented within the TAS Platform. This is a very flexible tool, based on intelligent mapping of capabilities according to a defined set of rights.
The control panel, which the user accesses after authentication, changes depending on the specific set of access rights they have. Meanwhile, all rights provisioning is controlled by an administrator who creates and distributes roles as needed.
Stone Decision Engine. An intelligent decision-making system that selects the treatment method: shock wave (ESWL) or laser (URS) therapy. It predicts the likelihood of success and complications based on information about the patient and data on all possible previous procedures.
For this, technologies based on artificial intelligence and machine learning are used. AI and ML facilitate a detailed analysis, ultimately allowing the development of an as effective as possible treatment system with the highest chances of success.
Simulator. A simulator that allows modeling the SWL procedure based on data from previous procedures performed for a specific patient. This helps to develop a truly effective treatment plan considering various nuances and predicting its outcome.
Vision AI. The core of the ecosystem's artificial intelligence, created for analyzing X-ray images of kidney stones. Tens and hundreds of thousands of images were processed through it, enabling the system to accurately identify the necessary objects.
The more images the system processed, the more accurate it became. A significant advantage of software interaction within a single ecosystem was the continuous receipt of new material for training during the platform's use.
TxPro. A separate desktop application created specifically for technologists. It allows not only to conduct the procedure but also to record data about patients and their body's reactions to specific impacts when using shock wave (ESWL) or laser (URS) therapy.
This tool, among other things, became an important basis for obtaining additional data necessary for artificial intelligence and machine learning. Thanks to this, the system continued to learn and improve continuously during its use.
Follow Up. After completing therapy, the treating physician schedules a follow-up appointment to check the patient's condition. Using this application, they transmit to the company information about everything that happened to the patient after treatment (e.g., possible complications during recovery).
Reports. Quarterly reports are also an important statistical tool directly for doctors and partner institutions. This tool allows comparing current values with the best indicators and, if necessary, downloading the results in a convenient format.
Thanks to the joint efforts of Focus21 and NextMed, it was possible to create not just separate applications, but a real software ecosystem that includes a full range of diverse tools necessary for the most effective treatment of kidney stones. It included six key elements. Gateway and Portal. The main entry point into the system itself, which provides unified authentication into all applications implemented within the TAS Platform. Plus, a portal, which is a dashboard that changes depending on the user's access rights. Stone Decision Engine. An intelligent decision-making system that chooses the treatment methodology: shock wave (ESWL) or laser (URS) therapy. It predicts the likelihood of success and complications based on patient information and data on all possible previous procedures. Simulator. The simulator allows the modeling of the SWL procedure based on data from previous procedures used for a particular patient. It allows the development of a truly effective treatment plan depending on various nuances. TxPro. A separate desktop application created specifically for technologists. It gives them the ability to record data about patients and their body's reaction to specific procedures when using shock wave (ESWL) or laser (URS) therapy. Follow Up. After the therapy is completed, the attending physician appoints a follow-up appointment to check the patient's condition. With this application, he passes on to the company information about everything that happened to the patient after treatment (for example, about possible complications during the recovery process). Reports. Quarterly reports are also an important statistical tool directly for their doctors and partner institutions. With this tool, you can compare current values with the best indicators, and if necessary, download the results in PDF.
When considering the creation of a software product ecosystem, one should not focus only on the size of the company. There are many examples where not only large, but also medium and small enterprises choose them. It all depends on the tasks that need to be solved.
Thanks to the ecosystem, it was possible to implement common access to information, convenient division of data usage rights after authentication, a scalable structure with the prospect of further expansion, a clear overall UX for all products, and optimal cost for the project's implementation.
Of course, the implementation of artificial intelligence and machine learning technologies throughout the system would also have been impossible without using all the advantages offered by a unified ecosystem. This particularly concerns the process of the system's automatic improvement during its use.
If a company needs to automate just one specific process, narrowly focused tools are sufficient. However, if the task is to fully digitize the business, organize the proper storage of all information, and use it in different directions, an ecosystem of applications should be considered.
When you book a call, our team will attentively listen to your vision, needs, and goals, tailoring an estimate to suit your budget. Whether it's a website update or a software ecosystem, count on us to assist you every step of the way.