How AI Integration Can Improve Patient Care

The COVID-19 pandemic has not only transformed our lives but also pushed healthcare institutions to seek ways to optimize their work by utilizing technologies and AI in patient care. This was the way to support medical workers, most of whom were experiencing pandemic-related stress (93%), anxiety (86%), frustration (77%), exhaustion, and burnout (76%).

But even if the pandemic is officially canceled now, new technologies are here to stay as patient treatment can still be improved. According to a 2022 survey conducted by The Beryl Institute – Ipsos PX Pulse, 76% of people cannot describe their patient experience as a positive one, while 60% of people frankly say it was negative.

The Beryl Institute - Ipsos PX Pulse Consumer Perspectives on Patient. Experience in the U.S. 2022

Hopefully, this is about to change if the use of AI in patient care becomes more widespread. How can artificial intelligence improve patient treatment, diagnostics, and overall experience? Read further to find out!

How AI Integrations Could Improve Patient Outcomes: Benefits And Use Cases

AI-based technologies have a lot of perks. They can:

  • analyze and structure huge chunks of data quickly;
  • provide valid suggestions based on the processed data;
  • automate and optimize repetitive tasks and processes;
  • offer full-time support;
  • reduce the risk of human error;
  • and many more.

Due to that, there are many ways to combine AI and patient care. Here are the most widespread options:

1. Chatbot assistance

These days, we are more or less used to healthcare chatbots popping up on almost every website and either asking or offering you something. Not all of them are advanced enough and sometimes it’s quicker and easier to reach out to the contact center to get what you need.

But as AI-based technologies develop, such chatbots become smarter. When it comes to healthcare, they can help patients with two things primarily:

  1. Make a doctor’s appointment.
  2. Get an initial diagnosis.

The second option looks more advanced and less realistic, but it’s already a reality. In 2020, pharmaceutical giant Sanofi teamed up with video consultation business Babylon to use their AI-enabled chatbot for diagnosing digestive health conditions.

Sanofi reminded that only an estimated 30% of the UK population suffering from Irritable Bowel Syndrome (IBS) have been diagnosed correctly. While this condition is very common, it is often mistreated or undiagnosed. The new chatbot, however, managed to give a Level 1 diagnostic for IBS.

2. Mental health treatment

AI solutions for mental health treatment

Mental health treatment is another way for artificial intelligence to improve patient care. And no, this is not about having online therapy with ChatGPT (although this could be an option for those who are interested).

Currently, there’s already a plethora of AI-powered mental health apps with various functions. One of the most popular of them is Calm, an app created to help deal with depression and anxiety. Depending on your needs, the app suggests meditations, focus music, sleep stories, movement tips, and other things that can help you feel better.

Another great example of such solutions is Wysa — an AI mental health coach offering immediate support. While it cannot be used to treat severe mental health issues and it isn’t a solid alternative to medical treatment, it can still serve as a first step of care. Wysa uses evidence-based techniques such as DBT, CBT, breathing, yoga, meditation, and other things to help you feel better sooner.

There’s also:

  • Replika, which uses a chatbot-based approach to help deal with stress
  • Sanvello, which tracks users’ mood and offers them support based on their mental state at the moment
  • TogetherAI, which is focused on children-parent communication, and others.

If you want to add your project to that list, turn to Mind Studios — we help our clients build high-quality custom healthcare solutions for mental health, wellness, and other things.

3. Pregnancy management

Enhancing pregnancy patient care with AI-powered solutions can help mothers feel more protected and safe daily. It can also help the doctors monitor the pregnancy with more accuracy and interfere on time if something goes wrong.

AI techniques can analyze data from medical records and smartwatches to predict pregnancy disorders, from preterm birth to suicidal behavior and postpartum depression.

For instance, the Northwell Health Pregnancy Chats is both a chatbot, an educational tool, and a virtual safety net aimed to recognize and handle urgent concerns. Each week it initiates a dialog with a mother to monitor her condition and help her notice even the subtlest changes that can affect the pregnancy.

96% of patients using this chatbot reported being either satisfied or somewhat satisfied with the experience.

4. Personalized treatment plans

This approach is already used to some extent in telemedicine apps. Such apps often collect and analyze various data (number of daily steps, weight, and height, food preferences, etc.) to suggest lifestyle improvements (diet plans, mental health tips, workouts, and many more).

Similarly to that, it is possible to automate basic patient care with AI. It can study patient data to create the best treatment plans specially for them. This increases the effectiveness of care as well as helps optimize costs: the more personalized the treatment is, the quicker a patient will recover and the less money they will spend in the process.

For instance, Aitia uses a machine learning algorithm that studies the patient data and creates Digital Twins of human disease to test out drugs and choose the most efficient treatments.

5. Patient data analytics

Data analytics can improve the accuracy and speed of diagnosis. And AI technologies, in turn, can massively speed up the data analysis process.

Besides traditional data analytics, AI can analyze medical images, such as MRI scans and X-rays to compare them with other visuals in the database and identify anomalies and possible patterns.

Furthermore, it’s possible to use natural language processing (NLP) to analyze old data that was difficult to process before, such as handwritten notes and audio records. NLP allows computers to understand written and spoken words similarly to how humans do it.

That, in turn, helps process the data that wasn’t properly structured and analyzed before. Potentially this could aid in identifying previously unknown disease patterns and improving treatments.

6. Robot-assisted surgery

Robot-assisted surgery backed by AI

AI can train robots to assist human surgeons. While this isn’t a common use of artificial intelligence to improve patient care in hospitals yet, it could help doctors a lot in the future.

AI-trained robots learn from large sets of data, quickly recognize and master new approaches, and reduce the risk of human error. They can also work for hours without fatigue, allowing human surgeons to take breaks and therefore relieving their cognitive and physical stress.

While it’s currently difficult to imagine that such surgery can be performed without human surveillance, it could still make the surgeons’ job much easier, as well as improve the results.

Challenges and considerations

Despite the positive impact of AI in patient care described above, it’s still not all rainbows and sunshine yet. Just like most new technologies, this one still has its challenges.

Patient comfort

While the main reason to combine patient care and artificial intelligence is to improve patient satisfaction, we are not there yet. As of 2023, 60% of Americans feel uncomfortable about being treated by healthcare providers relying on AI.

The PEW Research Center survey explores public views on AI in health and medicine

At the same time, 38% of the respondents already believe that utilizing AI in health and medicine will improve patient outcomes. So while there’s no solution to that challenge at the moment, public opinion could potentially improve even more as time goes on.

Patient data protection

Medical data is one of the most sensitive ones. Because of that, it is heavily protected by various regulations such as HIPAA and GDPR. Knowing which projects have to comply with these regulations and which can avoid that is essential for any healthcare app development process.

AI-based tools often need to access lots of patient data to deliver relevant and efficient solutions. At the same time, this could increase the possibility of data breaches and leakages.

Therefore, if you work with AI technology, you have to make data privacy your top priority. This could be achieved by leveraging privacy-enhancing technologies (PETs).

One of the most widespread PET is data masking: another inauthentic although a realistically-looking version of an organization’s data is created to be used for user training, software testing, and other purposes.

Read also: Healthcare Industry Regulations for AI

Training and education for the healthcare workers

The rapid advancement of AI technologies raises a lot of concerns among various specialists, medical workers included. As AI-based solutions can efficiently perform various tasks, they might potentially replace certain jobs. Therefore, many healthcare professionals are wary about adopting AI.

However, at the moment it seems that AI is here to support the medical workers rather than replace them —and this is unlikely to change soon. So it’s important for tech healthcare professionals to work with the AI technology and to monitor its efficiency to minimize potential risks. Because, after all, artificial intelligence also makes mistakes.

Diagnostic errors

Diagnostic errors of AI-powered healthcare programs

Speaking of mistakes: in the healthcare industry, they could cost not only money but also human lives. That’s why it’s extremely important to prevent them.

As of now, AI can often offer more accurate diagnostics than human specialists (Sanofi’s story supports that), but this isn’t always the case. For instance, hundreds of AI-based tools created to diagnose COVID-19 failed.

In the end, the outcome largely depends on the quality of data used to train the AI solutions. Therefore, it’s up to healthcare organizations to evaluate and verify the data used.

Correct implementation

Not all development teams are familiar with AI and know how to implement it properly. To avoid that, you need to have a clear goal (what you want to achieve with the help of a certain AI technology), high-quality data to train AI on, and a well-defined strategy.

While the goal definition stage is up to you, we at Mind Studios could help you with the other two. We constantly monitor new technology trends in healthcare, AI included, and know how to implement them in an existing product or to design one from scratch for you.


People need to stay healthy, but it isn’t always easy to do that. Unpleasant patient experiences can cause a lot of stress, force people to change medical institutions, or, worst case, start avoiding treatment at all. That’s why it’s so important to look for ways to improve patient care.

New technologies such as AI can help a lot with that. They can be used to optimize routine tasks, support pregnant women, help deal with mental health issues, personalize treatment plans, and even train robot surgeons. While AI implementation has its challenges, such as patient concerns, data protection issues, and difficulties in finding a skilled development team, adding such technologies to your healthcare solutions can still benefit you greatly.

So if you’re looking for a reliable tech partner that can do that for you, Mind Studios is here to help. The healthcare industry is one of our main areas of expertise, so we know well how to create a product in this niche that stands out among competitors. Contact us to learn how to utilize AI for your project!