Developing A Healthcare Tool with Go
Recently, I had the exciting opportunity to architect a tool in Go. The tool focuses on handling NPI healthcare provider data from the Center for Medicare. This was an exciting opportunity, because most of my programming work has been using Python or Javascript in production, and I am always excited to learn new skills.
The Go Programming Language
If you’re not familiar with Go, it’s a powerful and efficient programming language that has gained popularity in recent years. Go, also known as Golang, is a programming language created by Google and is designed for building reliable and efficient software. Its simplicity, strong support for concurrency, and excellent performance make it an ideal choice for a wide range of applications.
Benefits of Using Go for this Project
There are several reasons why Go was the perfect choice for this project:
- Concurrency: Go has built-in support for concurrency, which allows the tool to handle multiple requests and process data efficiently.
- Performance: Go is known for its excellent performance, making it ideal for handling large datasets and complex calculations.
- Simple and Readable Code: Go has a clean and simple syntax, making the code easy to read and understand. This is especially important when working on a project that involves complex data processing.
- Strong Ecosystem: Go has a strong and growing ecosystem with a wide range of libraries and tools that can be leveraged to enhance the functionality of the tool.
Caduceus – Handling NPI Healthcare Provider Data
NPI stands for National Provider Identifier, and it is a unique identification number assigned to healthcare providers in the United States. The Center for Medicare is responsible for maintaining and distributing this data.
With the increasing amount of healthcare data being generated, it’s essential to have efficient tools for processing and analyzing this information. Caduceus aims to streamline the process of working with NPI healthcare provider data, making it easier for developers and healthcare professionals to access and utilize this valuable information.
Working with Postgresql Database
The tool utilizes Postgresql database. Postgresql is a powerful open-source relational database management system that offers robust features and excellent performance. Because there are millions of entries in the NPI registry, it is crucial that data is handled in a scalable way. By integrating the tool with Postgresql, we can efficiently store and retrieve data, ensuring the reliability and scalability of the application.
Generating API Endpoints
Certain business cases require access to specific data. For example, when you are looking to grow a provider network, you may be interested in providers in a specific zip code who have registered within the last 6 months. This would indicate a newly licensed provider who may be an Essential Community Provider that can minimize your regulatory exposure.
In order to keep this data available across multiple business units, custom API endpoints have been created utilizing our existing authentication user pool. Permissions to the API endpoints can be mapped by the user pool to separate the concerns of authentication.
Conclusion
Architecting a tool in the Go programming language to handle NPI healthcare provider data has been an exciting and challenging project. Go’s concurrency, performance, and simplicity have made it an ideal choice for this task. By integrating with a Postgresql database and providing the ability to generate CSV reports, the tool offers a comprehensive solution for working with healthcare data.