7 Reasons AI and Healthcare Can Work Together to Lead to a Better Future

Our current healthcare system needs help. The unforeseen events this year have shown us how important it is to invest in a better healthcare system. One method that will become vital to our future is the combination between AI and healthcare to identify, track, and fight viruses.

Overwhelmed medical professionals are in desperate need of help with the surge in patients at a time when traditional methods of detection have become less effective. Artificial intelligence (AI) helps medical professionals make smarter decisions faster, so they can save more lives.

Many of the best minds in AI are using their technology to solve the world’s greatest health crisis. For example, tech giant Alibaba produced a new AI detection system that identifies viruses with 96% accuracy in 20 seconds based on patients’ chest CT scans.

This is the beginning. Soon AI and healthcare will work together to solve more of the world’s great health crises.

7 Reasons AI and Healthcare Can Work Together

1. Improved monitoring

The modern wearable technology era started in 2009 with the launch of the clip-on Fitbit tracker. In the past decade, these devices have gone from novelty to lifesaving tools with broad applications in the healthcare industry.

Wearable technology provides a wealth of health information due to the continual tracking that is not possible with traditional methods like an annual checkup.

The challenge becomes how to separate the critical from the mundane information in this wealth of data. AI is starting to play a huge role in monitoring wearable technology statistics.

For example, researchers at the University of California, San Francisco have started to test whether wearables can offer an early-warning system to many throughout the country who have experienced coronavirus.

2. Help those with chronic health conditions

In an era where those with chronic health conditions are in grave danger, we need help.

According to a recent Healthcare IT News study, 66% of health care professionals believe AI and ML (machine learning) will help those with diabetes. 63% feel heart disease and cancer will also see better results because of these technologies. 56% expect to see benefits in neurological diseases and 46% with infectious diseases.

3. Improve decision-making

The same Healthcare IT News study found 77% of healthcare professionals believe AI can improve their decision-making capabilities.  Even after things settle down with Covid-19, doctors need help identifying an array of diseases today.

The stream of data is too much and fast for any human to go through on their own. AI tools can find specific diseases by reviewing the data to determine their identify.

For example, Harvard University’s teaching hospital Beth Israel Deaconess Medical Center started using AI to diagnose potentially lethal blood diseases in the earliest stages of development. They scanned for toxic bacteria like E. coli and staphylococcus.

Doctors scanned 25,000 blood sample images and with a 95% accuracy were able to name and predict who and how these harmful bacteria would affect patients.

4. Reduce the length of stays

Science Direct reported on how big data can improve the quality of treatment for ER centers. Based on the information the hospitals used, they reduced the length of stay by 40% while the effectiveness of these stays improved by 50%.

For example, John Hopkins Hospital in Baltimore partnered with GE to use predictive AI techniques to improve the overall patient flow.

The two organizations used AI to prioritize hospital operations. Because of the program, John Hopkins saw a 60% increase in their ability to admit patients and a 21% rise in the number of patients discharged before noon.

Imagine how this could help with the ICU beds and ventilator shortages.

5. Drug development

The average cost to get a new drug in the US into a clinical trial is now $2.6 billion. Even then only 10% of drugs which get to clinical trials ever get approved.

AI can improve the efficiency and accuracy of this process. Over the past few years, drug developers have seen how powerful databases can reduce the costs and find which drugs on the market could fight other diseases.

For example, the Google DeepMind division is using their AI algorithms to help researchers treat Covid-19. Their AI algorithm reviews the massive amount of data researchers around the world compiled over the past few months to find proteins scientists can use in treatments.

DeepMind can go through this data in minutes and hours with a higher level of accuracy where researchers might take days and months.

6. Prescribe the correct drugs

Even when new drugs make it to market, sometimes they people do not use them for their intended purpose.

The FDA has over 20,000 approved prescription drugs and 6,500 medical devices. While doctors want options, it is impossible for any doctor to be aware of the drug interactions, level of pain, medical history, and dosage amount needed for each patient.

This has become a dangerous trend since CNBC estimates between 250,000 to 440,000 people die every year from medication errors. It does not matter how many years of training doctors receive; humans cannot keep up with the sheer amount of data.

That is why misdiagnoses and medication errors account for 10% of US deaths every year.

As we said earlier, AI diagnoses medical issues faster than humans. For example, one study showed how an AI model diagnosed breast cancer at a rate faster than 11 pathologists.

This doesn’t mean AI is perfect. One of the biggest challenges to AI adoption in healthcare is trust. A survey from Health IT Analytics found 54% of respondents felt AI would cause at least one fatal error. At the same time, humans can avoid making fatal errors as well. The key is how much can AI help to reduce these errors.

7. Cost savings

Accenture believes the investment into AI can bring about $150 billion in annual healthcare savings by the year 2026. Since the US spends about 4% of their annual GDP on healthcare ($3.5 Trillion), this would trim 4% off our annual healthcare costs.

That said, not all these cost savings are positive. Some reports from the National Institute of Health suggest AI technology could eliminate between 5- 35% of healthcare jobs in the next 10-20 years.

Fortunately, the biggest cost savings now come from routine jobs humans cannot perform fast enough like review samples. Many of these are boring, repetitive tasks we will be more than happy to assign to a computer. As technology improves this might change.

Final Thoughts on AI and Healthcare

The investments we made in AI over the last decade will help us fight some of the deadliest diseases we ever faced. That is why professionals in the healthcare field need to use the data AI analyzes to save more lives.

If you have more questions about how to use AI for your healthcare organization, connect with us today for a free 1-hour consultation.