10 Best medical coding languages In 2025 For Developers

To remain competitive in the healthcare market, healthcare providers must have a user-friendly and visually appealing app. Developing such an app is a difficult endeavor that necessitates it being secure, inclusive, and robust. Choosing appropriate medical coding languages for healthcare apps is one of the first steps in creating a solid foundation for the development project. Although Python, Java, C, Kotlin, and a few more programming languages are well-known, it is critical to select the right fit for your healthcare app.

This article provides an overview of the top 10 medical coding languages for healthcare apps to help you make an informed decision.

First, if you just want a brief summary about these medical coding languages, you can just check out comparison table:

Now let’s dive into the details about top 10 medical coding languages in 2025:

1. Java

Java is a programming language that is widely used in various industries. It is favored for its reliability, safety, user-friendliness, versatility, and support for cross-platform application development. Java is already widely used in healthcare (for diagnostic and interventional systems, record-keeping, cloud and server applications, and online applications). In short, Java makes a good choice for developing healthcare software, particularly due to its capabilities among medical coding languages.

1. Platform independent: Java is a platform-independent programming language, which means that it can run on any operating system, such as Windows, Linux, or macOS. 
2. Security: Java has a strong security model, which is particularly important for healthcare applications that handle sensitive patient data in compliance with HIPAA compliance checklist.
3. Scalability: Healthcare applications often need to handle large amounts of data and support multiple concurrent users. Java’s scalability features, such as its support for multithreading and distributed computing, make it well-suited for building scalable healthcare applications that can handle high volumes of data and traffic.
4. Large developer community: Java has a large and active developer community, which means that there is a wealth of resources, tools, and libraries available for healthcare software development companies. 
5. Integration with other technologies: Java integrates well with other technologies commonly used in healthcare, such as databases, web servers, and messaging systems. 

2. Python

Python is a versatile, robust programming language that is widely used in many industries, including healthcare. It’s simple to learn, and it includes a plethora of libraries that allow you to do practically anything you can think of. Python can be an excellent choice if you intend to integrate vast volumes of data or if you intend to employ AI or ML, making it one of the prominent medical coding languages utilized in healthcare.

1. Rapid prototyping: Python is a high-level programming language that is easy to learn and use. It has a simple syntax that allows developers to quickly prototype and test their ideas. 
2. Data analysis and machine learning: Python has strong capabilities in data analysis and machine learning, which are increasingly important in healthcare. Python has a large number of libraries and frameworks, such as NumPy, Pandas, and TensorFlow.
3. Integration: Python has a wide range of libraries and tools that make it easy to integrate with other technologies commonly used in healthcare, such as databases, web servers, and messaging systems. 
4. Open-source: Python is an open-source language, which means that there are many open-source libraries and frameworks available for healthcare app development. 
5. Cross-platform: Python is a cross-platform language that can run on multiple operating systems, including Windows, Linux, and macOS. This makes it easier to develop healthcare apps that can run on different devices and platforms.

3. Kotlin

After learning about Kotlin, you can create powerful applications using its modern, concise, and easy-to-learn programming language. Developers can use multi-platform mobile, server-side, web frontend, and other tools. Because it has more functionalities than other programming languages, healthcare mobile app development services use Kotlin’s capabilities when designing Android-based applications. This further showcases its position among effective medical coding languages.

1. Interoperability with Java: Kotlin is fully interoperable with Java, meaning it can use all existing Java libraries, frameworks and tools. 
2. Null Safety: NullPointer exceptions are a common source of bugs in many languages. Kotlin has built-in null safety, meaning it’s less prone to such errors. 
3. Expressiveness: Kotlin is designed to be more expressive than Java, meaning you can often achieve the same functionality with fewer lines of code. 
4. Coroutines: Kotlin’s coroutines simplify asynchronous programming by making it more linear and readable, which can be critical for app responsiveness. 
5. First-class Android support: Kotlin is officially supported by Google for Android development, meaning it has first-class tooling support in Android Studio. 
6. Modern language features: Kotlin includes many modern language features like lambda expressions, extension functions, and destructuring declarations that can make your code more readable, flexible, and efficient.

4. R

R is known as the “lingua franca of statistics” since it was created by statisticians and is specialized in statistical computing. As technology advances, the data businesses and research institutes collect becomes more complicated, and R has become the language of choice for data analysis. Furthermore, as an open-source language, R has an exceptional ability to develop an effective user interface. The visual representation of data is critical for a custom personal health record software application’s user interface (UI) among the medical coding languages.

1. Statistical Analysis: R is specifically designed for statistical analysis. It offers a wide variety of statistical and graphical techniques, including linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, and clustering.
2. Data Visualization: R has strong data visualization libraries (like ggplot2) which can convert complex data into easy-to-understand, visual formats. This is especially important in healthcare, where it’s often necessary to present data in a way that can be easily understood by non-technical users.
3. Bioconductor: Bioconductor is an open-source healthcare IT software project based on R that provides tools for the analysis and comprehension of high-throughput genomic data. 
4. CRAN Packages: R has a large number of packages (libraries) available for specific tasks through The Comprehensive R Archive Network (CRAN). 
5. Reproducibility: R is well-suited to creating reproducible research. This is an important factor in healthcare, where it’s often necessary to recreate analyses as new data becomes available or methodologies are refined.

5. SQL

SQL is a specialized computer language for interacting with databases. It works by studying and comprehending databases made up of data fields within tables. SQL is a necessary prerequisite for developing healthcare apps since it allows for data updating, query use, and record changes. It makes it easy for administrators of healthcare applications to conduct audits, analyze data, and maintain databases, marking its significance among medical coding languages.

1. Data Manipulation and Management: Healthcare apps often need to work with large amounts of data, including patient records, medical histories, billing information, etc. SQL allows you to interact with this data, doing everything from basic tasks like inserting, updating, and deleting records to more complex operations like querying multiple tables, creating views, or running complex transactions.
2. Standardization: SQL is a standardized language recognized by the ANSI and ISO. This makes it a reliable choice for managing databases, as it’s widely supported by virtually all relational database management systems, including MySQL, Oracle, SQL Server, PostgreSQL, and SQLite.
3. Data Integrity: SQL databases help maintain data integrity through constraints, which ensure the accuracy and reliability of data. This is crucial in a healthcare context, where inaccurate data could potentially have serious consequences.
4. Relational Databases: SQL is used in relational database management systems (RDBMS), which are excellent for managing structured data. 
5. Security: SQL databases usually offer strong security features, including advanced permissions and access controls. This is particularly important in healthcare, where protecting patient data is a legal and ethical necessity.

6. Ruby or Ruby On Rails

Ruby on Rails, often just referred to as Rails, is a popular server-side web application framework that uses the Ruby programming language. It is designed to make programming web applications easier by making assumptions about what every developer needs to get started. Here are some reasons why you might choose Ruby and Ruby on Rails for healthcare app development, highlighting its role among leading medical coding languages.

1. Rapid Development: Rails is designed to help you move from planning to actual development very quickly. It’s a full-featured framework that includes everything needed to create a database-backed web application. 
2. MVC Architecture: Rails follows the Model-View-Controller (MVC) architectural pattern, dividing the work of an application into three interconnected parts. 
3. DRY Principle: Rails emphasizes the DRY (Don’t Repeat Yourself) principle. With Rails, developers can create reusable chunks of code that can be used across different projects, increasing efficiency and consistency.
4. Testing Environment: Rails comes with built-in testing tools and encourages test-driven development. 
5. Gems: RubyGems, the package manager for Ruby, allows developers to quickly and easily use third-party libraries (known as gems) in their projects. 
6. Active Record: Rails includes Active Record, an Object-Relational Mapping (ORM) system. It simplifies data handling and database interactions, making it easier to create, retrieve, update and delete records from your database using Ruby code rather than SQL.
7. Scalability: With proper configuration and architecture, Rails apps can be very scalable, which is important for healthcare apps that might need to handle large amounts of data or traffic.
8. Community and Resources: The Rails community is large and active, which means that developers can find a wealth of resources, tutorials, and libraries to help with their projects. 

7. PHP

This open-source programming language is used in web development to create websites such as Yahoo and Facebook. PHP is increasingly being used to construct healthcare applications. PHP uses its coding skills to build mobile applications, the majority of which are based on iOS and Android healthcare apps, securing its place among other recognized medical coding languages.

1. Server-Side Scripting: PHP is primarily used for server-side scripting. This allows for dynamic content to be generated, a feature that would be particularly useful in a mobile health app where patient data needs to be accessed and displayed.
2. Easy Integration: PHP can easily be integrated with a number of popular databases including MySQL, PostgreSQL, and MongoDB. 
   1. Cost-Efficiency: PHP is open-source and free to use, which can reduce the healthcare app development cost. It also has a large community, which means a wealth of resources, libraries, and tools are available to speed up and simplify development.
3. Compatibility: PHP is compatible with almost all servers (like Apache, IIS) and also supports all major web browsers. 
4. Scalability: PHP can be used to create scalable applications, which is crucial for healthcare apps that may need to grow over time in terms of users or data volume.
5. Mature Language: PHP has been around for a while, and it has matured as a language over this time. It has a large community, considerable resources, and many pre-built modules that can help expedite the development process.
6. Frameworks: PHP offers several robust frameworks like Laravel, Symfony, CodeIgniter, and more. These frameworks can speed up the development process and provide well-organized, reusable, and maintainable code.

8. Rust

It’s a systems programming language that runs blazingly fast, prevents segmentation faults, and guarantees thread safety, placing it as a strong contender among medical coding languages for creating high-performance healthcare systems.

1. Safety: Rust’s design prioritizes safety and avoids many types of errors common in other languages, like null pointer dereferencing and data races. 
2. Performance: Rust provides performance similar to languages like C and C++. This can be useful for healthcare applications that require high performance, such as those dealing with large amounts of data or complex computations.
3. Concurrency: Rust has excellent support for concurrent programming, which can be beneficial for creating applications that need to handle many tasks at once without running into race conditions or other common concurrent programming problems.
4. Interoperability: Rust can interoperate with C, and it’s possible to write a Rust library that can be used from C. This could be useful in a healthcare setting where you might have legacy C code that needs to be maintained or used in conjunction with newer code.
5. No Garbage Collector: Rust doesn’t use a garbage collector, which can lead to more predictable performance. This can be important in healthcare applications, where delays or lags can impact user experience or even patient care.
6. Fearless Concurrency: Rust allows for the creation of concurrent systems that are safe from data races by design, which can be very important in complex healthcare systems where different threads might need to access shared data simultaneously.
7. Memory Efficiency: Rust’s ownership model ensures effective and efficient memory management, which can be crucial in healthcare applications handling large amounts of data.

9. Swift

Swift, developed by Apple, is an efficient and robust programming language ideal for healthcare app development on iOS and other Apple platforms. Its fast performance ensures a responsive user experience, crucial for healthcare applications where timely data access matters. Swift’s design encourages clean, error-free coding, enhancing app stability—a vital aspect in healthcare contexts. Additionally, it offers interoperability with Objective-C, useful in evolving legacy projects. Its effective memory management with Automatic Reference Counting (ARC) further boosts app performance, making Swift a reliable choice for healthcare app development and an essential part of the medical coding languages landscape.

1. Speed and Efficiency: Swift is designed to provide seamless performance similar to C/C++ and is significantly faster than Objective-C. This can result in a smoother, more responsive user experience, which is important in healthcare apps where timely access to information can be critical.
2. Safety: Swift’s syntax and language constructions exclude the several types of mistakes potentially leading to crashes and errors in the code. It forces developers to write clean and correct code, which can contribute to overall better quality apps.
3. Interoperability with Objective-C: You can use both Swift and Objective-C code in the same project, allowing a smooth transition to Swift for existing Objective-C projects or using Objective-C libraries in Swift projects.
4. Readable and Clean Syntax: Swift’s syntax is concise and expressive, which makes the language easy to read and write. This can speed up development and make it easier to maintain and update your app.
5. Memory Management: Swift uses Automatic Reference Counting (ARC) for memory management across all APIs, which can help to improve app performance and reduce the likelihood of memory leaks.

10. C Programming Languages (C# & C++)

C# and C++ are two powerful and versatile programming languages that are frequently used in various domains, including healthcare app development. C#, developed by Microsoft, is a part of the .NET framework and is known for its simplicity and robustness. C++, on the other hand, offers high performance and is widely used for system/application software, game development, drivers, and embedded systems.

Here’s why you might use C# for healthcare app development, contributing to its classification among medical coding languages:

1. Ease of Use: C# has a relatively simple syntax which is easy to understand and write. This makes the development process quicker and more efficient.
2. .NET Framework: Being part of the .NET framework, C# has access to a vast number of libraries and tools which can greatly speed up the development process and provide robust functionality.
3. Cross-Platform Support: With the .NET Core framework, C# can be used for creating applications that run on multiple platforms, which is highly beneficial for healthcare apps.
4. Strongly Typed Language: C# is a strongly typed language, which can help prevent type-related errors that could lead to bugs in the application.
5. Support for Web Services: C# has excellent support for creating web services, which can be critical for a healthcare app that needs to communicate with different systems.

Conclusion

When it comes to medical coding languages for healthcare apps, there are many options to choose from. Each language has its pros and cons, so selecting the one that works best for your business is important. Additionally, considering outsourcing in healthcare can be a viable strategy to reduce costs and bring in specialized expertise that may not be available in-house. Leveraging insights from healthcare analytics companies can also guide you in selecting the best technologies and approaches for your projects. If you’re looking for innovative healthcare app ideas, consider how technologies like conversational AI in healthcare can enhance patient engagement through interactive interfaces.

To ensure that your healthcare app is successful, it’s wise to work with healthcare app development companies that have plenty of experience in the healthcare industry, like Savvycom. They can assist you in implementing custom healthcare software solutions and help with electronic health record integration to ensure a seamless user experience. Staying updated with the latest tech innovations in healthcare will also place your app at the forefront of industry advancements.

How had Covid-19 changed the Healthcare App Market?

• Telehealth and Virtual Care: With lockdowns and social distancing measures in place globally, in-person medical consultations became challenging. As a result, telehealth apps experienced a significant boost as they provided a platform for patients to consult healthcare professionals remotely.
• Contact Tracing and Health Tracking: Apps designed to track the spread of the virus and notify users of possible exposure became prevalent. Additionally, health tracking apps that allowed users to monitor their symptoms and vital signs saw an increased demand.
• Mental Health: The pandemic's impact on mental health was substantial, leading to increased demand for mental health apps offering services like therapy sessions, mindfulness and meditation, stress management, and more.
• Fitness and Wellness: With gyms and fitness centers closed or restricted, there was an increased interest in fitness and wellness apps that provided home workout routines, nutrition advice, sleep tracking, and more.
• Information Dissemination: Apps also played a critical role in disseminating accurate and timely information about the pandemic, preventive measures, vaccine rollouts, etc.
• Chronic Disease Management: For people with chronic diseases, managing their health became even more crucial during the pandemic. Apps helping in disease management, medication reminders, and remote patient monitoring saw increased demand.

Even after the pandemic, it's anticipated that the demand for healthcare apps will remain high. The crisis highlighted the value of digital health and accelerated its adoption. Many patients and healthcare providers recognized the convenience and potential cost savings associated with these technologies, leading to expectations of continued use.