It is a no-brainer that healthcare companies are dealing with a humungous amount of data from their facilities and patients on a daily basis. As per a study by Statista, the healthcare data equalled nearly 153 exabytes in 2013, which has grown to 2,300 exabytes in 2020.
With the pandemic luring, there is pressing pressure on the healthcare industry to deliver exceptional results. As a result, the healthcare industry is treading on the digital route for efficient data management, thereby addressing the challenges of the physical healthcare system.
One of the key technologies assisting healthcare in handling its data and making accurate predictions is Python. In fact, Python is deemed the fourth commonly used programming language and has a vast community of developers.
The incredible flexibility and features of Python in healthcare applications have proven their capabilities. So let’s understand the importance of it.
8 Top Features of Python that Attracts Healthcare Entrepreneurs
Since Python is a programming language, it can’t offer any direct benefit. However, it is the use of Python in Healthcare applications that cushions the health and medical system.
Below are some areas wherein Python in healthcare applications has shown great potential:
Increased Productivity
The precise syntax of Python makes the programming language more readable. In addition to this, the reusability of code and clean object-oriented designs enable software developers to code better and faster. Besides this, Python is competent to build complex features for healthcare applications.
Dynamic Semantics
Python is known for its dynamicity with decreased volume of source code and shorter design cycles. As a result, Python offers flexibility and saves a lot of hours for developers. In addition, the dynamic semantic features of Python enable developers to code, test, and deploy quickly, which simplifies the road for the development of healthcare applications.
Open Source
Since Python is an open-source programming language, it can be easily distributed and used freely. To put this in perspective, Python has a vibrant and large community of contributors sharing their experience and expertise regarding the new capabilities of the programming language. As a result, applications of Python in the healthcare industry is only going to widen.
Available Libraries and Frameworks
Python features a rich set of libraries as well as flexible frameworks. Using these libraries and frameworks of python, healthcare projects can be developed without a lot of coding requirements.
Test-driven Development
Python is known for its test-driven development. The programming language highlights readability, simplicity, and effectiveness, which benefits software developers to handle the complex requirements of healthcare applications. Owing to the test-driven development, healthcare projects can reduce the time taken in fixing the bugs, thereby decreasing the maintenance costs of the healthcare product development lifecycle.
Interoperability
Python has specific frameworks, which exhibits excellent interoperability alongside the other programming languages as well as technologies. As a result, healthcare solutions can leverage benefits from the seamless integration of Python with other competing technologies.
Versatility
As commonly known, Python is a general-purpose programming language. It also decreases the overall complexity of the healthcare projects and features better versatility over the functionalities. As a result, the area of experimentation and innovation to play with for software developers increases, thereby increasing the peripheries of novelty for healthcare apps.
HIPAA Compliance
One of the best characteristics of Python is HIPAA Compliance. There are multiple readily available and free Python packages for cryptography and data security. Since security is as important for the healthcare industry as it is for the finance industry, the HIPAA compliance of Python ticks every box required for the development of healthcare software.
Why is Python in Healthcare Applications Useful?
If your question is, “What is the use of Python in Healthcare applications?”
Let’s delve deep into the answer with the top uses of Python in healthcare applications.
Primarily, Python is used for the development of web/desktop applications. It is a convenient programming language for building complex healthcare applications. Python frameworks enable the secure exchange of information along with other solutions for handling digital healthcare data. In addition to this, as discussed previously, features of Python that integrate with databases streamline with the HIPAA rules.
Besides this, Python is seen as a great language for analyzing large sets of data through machine learning algorithms for gaining meaningful insights. Data scientists swear by the importance of Python for the development of applications that demands efficient handling of data, owing to its extensive libraries–Pandas, SciPy, and NumPy.
Below are the best uses of Python in healthcare applications:
Predictive Analytics
Predictive analytics is one of the most prominent benefits of Python in healthcare appl. Software developers can rely on Python for developing Machine Learning models, which predicts diseases before they reach the extreme stage. In addition to this, predicting how severe can a disease get is a challenge in itself. In such a case, healthcare data analytics system developed with Python can predict the right course of treatment for patients.
Image-based Diagnostics
Diagnostic errors are the grave problematic areas for the healthcare industry. Many deaths of patients happen on account of mismatch of diagnostic data and the wrong course of treatment. As a result, Python is seen as the best-suited programming language for applying data science to healthcare software, which can create accurate diagnoses using image analysis. The machine learning algorithms can skim through the DTIS, ECGs, and MRIs for identifying any disease pattern that might be building up in the body.
Better Patient Management
Patient management consumes a lot of time for healthcare professionals. With loads and piles of files with patient data, the patient management system often becomes complicated and an error-prone process. In such a case, introducing Python for the development of a patient management system or an electronic health record system facilitates clinicians, patients, and related stakeholders to ensure accurate processing. Since the patient management system is likely to home a large amount of data, Python can be used for the development of a user-friendly, dynamic, and scalable suite of software.
What are the Top Healthcare Startups Developed Using Python?
Below are the top healthcare startups that use Python frameworks for building applications that provide convenience to patients and internal teams:
AiCure
AiCure is a New York-based healthcare startup, which is working towards bridging the gap between effective treatments and diseases through AI. The digital healthcare system uses computer vision along with pill recognition technology for constantly monitoring the response of a patient’s system to treatment. It is an intuitive medical assistant, developed using Python and Django, which helps medical professionals to validate that patients are following the right medicine schedule.
Roam Analytics
Roam Analytics Inc. is a physician pathway and patient analysis based in San Mateo, California. The Silicon Valley startup leverages machine learning along with the natural language processing models for converting large amounts of disorganized and heterogeneous data sets into a structured format to help medical professionals get a clear idea about the patient’s health status.
Drchrono
Drchrono is a comprehensive electronic health record management platform based in Silicon Valley. The healthcare startup offers end-to-end EHR software that provides customizable workflows along with the patient portal. In addition to this, Drchrono also permits patients to schedule their appointments and enter into direct communication with healthcare professionals.
Besides this, Drchrono enables patients to undertake self-check-in and underpins automated reminders for appointments.
Fathom Health
Based in San Francisco, Fathom Health is a medical startup using natural language processing models and deep learning models for structuring, analyzing, and reading datasets in EHR systems. Fathom Health leverages AI models for coding millions of datasets from billing records and patient charts. The healthcare startup company uses the Python open-source frameworks to develop identification technology that secures PHI in real time. The billing records can be retrieved with high accuracy and matchless speed.
Qventus
Qventus is headquartered in California. It offers a real-time predictive analysis to assist hospitals to allocate their resources to meet the influx of patients based on the forecasting. Qventus uses machine learning-oriented forecasting techniques for healthcare professionals to reduce the time of hospital stays, unnecessary lab diagnosis and improve the patient experience.
Which Python Framework is Better for Healthcare Applications?
While there are multiple python frameworks available, Django and Flask are considered top frameworks.
Django is the most commonly used python framework for the development of web applications, which require scientific computing platforms, social networking portals, communication modules, and more. Python developers use Django to be able to develop clean code and expedite the software development lifecycle. Django can be used to secure the healthcare software against CSRF, XSS, and SQL injection attacks.
In addition to this, Django enables software developers for modifying and customizing decoupled components for meeting the requirements of project needs.
Another key python framework that can be used for the development of healthcare applications is Flask. Flask provides modular code blocks, enabling multiple applications as well as distribution across multiple servers. Besides that, Flask is considered flexible, and it is known for delivering high performance. However, Flask requires more configuration time than Django, which further narrows down its number of users.
If you can’t make the decision between Flask and Django, we are here to help.
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