Artificial Intelligence, Software Development

What Are The Best Practices For AI In Healthcare? Explained!

Posted on March 8, 2024

By Jim Hutchings

May 25, 2024

Healthcare is a challenging industry. It has to deal with high costs, aging people, and complicated diseases. To solve these problems, healthcare needs new and better solutions. One of them is artificial intelligence (AI). AI can improve healthcare in many ways.

But what are the best practices for AI in healthcare? In this article, we will talk about how AI is transforming healthcare and what you need to do to use it effectively and ethically.

How AI is Transforming Healthcare

AI is reshaping the healthcare industry by making it more accurate and efficient. Let’s see how AI is currently impacting various aspects of healthcare:

Medical Imaging and Diagnosis

AI-powered image analysis is a game-changer in medicine. It enables computer vision algorithms to evaluate medical images, such as MRIs, CT scans, and X-rays, with remarkable precision.

AI can help detect anomalies, measure changes, and provide diagnoses faster and more reliably than human experts.

Drug Development and Discovery

AI is speeding up the process of finding and developing new drugs. By handling large datasets and simulating complex chemical interactions, AI can identify potential drug candidates more quickly and cheaply. It can also optimize drug design, testing, and delivery, reducing costs and risks.

Clinical Decision Support

AI can assist healthcare professionals in making better decisions. AI-based clinical decision support systems can help doctors make informed treatment decisions, diagnose diseases, and prevent errors. These systems can offer recommendations and alerts in real time during patient interactions.

Predictive Analytics and Patient Management

AI can help healthcare providers anticipate and meet patient needs. By analyzing patient data, AI can predict disease outbreaks, identify at-risk individuals, and assist in managing chronic conditions.

Additionally, AI has the ability to improve patient engagement, satisfaction, and outcomes by providing personalized and proactive care.

Electronic Health Records (EHR)

AI can enhance the management and retrieval of patient data. AI-integrated EHR systems can automate data entry, extraction, and analysis, saving time and resources.

Also, it will improve the security, quality, and interoperability of health data, facilitating data sharing and collaboration.

Innovation and Research in Medicine

AI can enable medical researchers to handle and analyze large datasets more efficiently. It can discover patterns, relationships, and new research areas that humans might miss.

AI can also augment human intelligence and creativity, leading to novel discoveries and breakthroughs.

Want to learn more? Book a meeting with us today!

10 Best Practices for Implementing AI in Healthcare

We have already talked about how artificial intelligence is transforming healthcare. Now, let us talk about the 10 best practices for implementing AI in healthcare:

1. Identify the Problem and Set Clear Goals

The first step in implementing AI in healthcare is to define the specific project objectives and the problem you want to solve.

For example, you may want to use AI to save time for doctors or to find the best treatment for patients. You need to have a clear idea of what the problem is and what success means so you can measure how well the AI works.

2. Ensure Data Quality and Security

Implementing AI in healthcare requires a lot of data, so it is essential to ensure the security and quality of the data.

This means that the data should be free of errors or gaps, and it should be stored securely and legally. You need to follow the rules for data sharing and protect the patient’s privacy at all times.

3. Ethical Data Handling

Healthcare organizations must prioritize safeguarding patient data while following strict ethical principles. This is especially important in the US, where you need to follow the Health Insurance Portability and Accountability Act (HIPAA).

You need to design AI that keeps patient data anonymous and useful. You also need to check the data regularly and follow the best practices for data governance.

4. Include Stakeholders and Clinicians in the Process

Clinicians and other stakeholders must support the effective use of AI in healthcare. They are the ones who will use the AI or benefit from it, so you need to get their input and feedback.

You need to include them from the start and ensure the AI meets their needs and expectations. You also need to address any concerns or doubts they may have about the AI.

5. Natural Language Processing (NLP)

Healthcare organizations can benefit from using NLP technology to extract relevant information from unstructured data, such as patient records and clinical notes.

This can help you create better patient profiles and make better decisions. Medical coding can also benefit from NLP techniques, which reduces administrative work.

6. Choose the Right AI Technology

Healthcare organizations can choose from many AI technologies, such as robots, natural language processing, and machine learning.

You need to evaluate the options and choose the best one for your situation. You may need to work with experts or vendors to help you with this.

7. Test and Validate the AI Solution

It is important to test and validate the AI system after development before using it in a clinical setting. You need to run tests or simulations to see how the AI performs and if there are any issues or areas to improve.

It is important to involve doctors and other relevant parties in this process to ensure that the AI is reliable and efficient.

8. Monitor and Evaluate The AI

Continuous monitoring and evaluation are essential for the effective use of AI in healthcare. This is to ensure that the technology is meeting expectations and achieving goals.

You need to track how the AI is doing and if it is meeting your goals. You must review the AI regularly and find any problems or areas to improve. Also, you must be ready to make changes to the AI as needed to make sure it keeps working well.

9. Provide Training and Support

It is important to provide training and support to staff members and doctors to ensure that they can use the AI system effectively.

This may involve providing instruction on the technology itself, as well as any new workflows or processes that have been implemented. You need to make sure they are comfortable with the AI and understand how it can help them and their patients.

10. Patient-Centric Approach

When implementing AI in healthcare, it is essential to have a patient-centric perspective. Prioritizing patient care, enhancing the patient experience, and ensuring that AI solutions meet patient needs and expectations should always be the main goals.


AI is a game-changer in the healthcare industry. It can help healthcare organizations achieve a higher level of accuracy, efficiency, and personalization. However, it also requires a strategic and ethical approach to ensure that AI is used beneficially and responsibly.

By following the best practices discussed above, healthcare organizations can harness the power of AI to improve their healthcare delivery and outcomes. If you’re interested in learning how AI can benefit your business, get in touch with us today.

Steve Solt headshot

Jim has been a veteran in the software development and project management sphere before even joining KDG as our VP of Software Development. He has over a decade of experience in technology supporting the financial services industry, specifically investment banking and life insurance.

Want to learn more? Book a meeting with us today!

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