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How AI Will Shape The Healthcare Industry in 2020

By Team Altus | Published Mar 13, 2020 | 8 MIN READ

The rise and complexity of data in healthcare means the field will increase the use of artificial intelligence (AI) and continue to innovate. As consumer and patient trusts continues to grow, the faster AI will develop. And the more AI is pushed, the more reliable it will become.

Some people are more comfortable with AI. Some may worry and be reluctant to replacing humans with a computer. There are many steps and regulations that have not been taken or made before we reach the point of trusting and fully implementing AI diagnoses and treatments.

Despite the fact that we are still in the early stages of AI, and the possibilities seem to be endless, many organizations in the healthcare field have already begun using AI in their workflow. AI helps with accurate diagnoses, treatment recommendations, preventing the spread of disease, patient engagement and more. AI facilitates decision-making and improves diagnoses and processes. Decisions are made based on the data AI acquires, collects and organized.

Below is a guide on how AI will share the healthcare industry in 2020 and beyond.

AI and machine learning are sometimes used interchangeably. Here is the difference:

AI vs Machine Learning

AI

“A machine’s ability to keep improving its performance without humans having to explain exactly how to accomplish all the tasks it is given.” - Harvard Business Review

Machine Learning

“An application of artificial intelligence, focusing on the idea that humans can provide machines access to data and let them learn for themselves.” - Forbes

Both AI and machine learning with impact society and the healthcare industry specifically, in substantial ways. Now and in the near future, machines will have a greater impact on healthcare.

Medical data will double every 73 days

According to Forbes, “AI can assist with many clinical problems as long as governing and regulatory bodies can determine how to regulate the use of algorithms in healthcare.” This new data reveals information that was previously not possible.

Because of AI’s success, there is an urgency to increase the rest of the adoption in IA in all facets of the healthcare system. According to Tractica, healthcare AI-powered tools market is expected to exceed $34 billion worldwide by 2025,

There are great benefits and opportunities. Healthcare professionals can use the power of AI to deliver better care and outcomes for their patients. Below is a complete list of how AI will share the healthcare industry in 2020. AI and machine learning are playing a major role in:

Improving the patient experience

Because of AI, no one is patient zero. Collective health data from around the world can give powerful insight to managing one’s own health. In 2020 and beyond, we are able to analyze a patient’s data faster and better. Therefore, lowering costs and improving access to the quality of care.

AI can diagnose and prioritize complex and acute cases. AI reduces and mitigates the risk of preventable medical scenarios and avoids unnecessary interventions such as surgery.

AI chatbots and virtual health assistants are changing the industry. Chatbots can perform a multitude of roles such as customer service, therapists and diagnostic tools. The chatbot market is projected to reach $314.3 million by 2023 from $122 million in 2018.

Smart wearables such as watches and smartphones are helping patients monitor their health while collecting their data. These wearables can be used for automated reminders and deliver personalized dosage recommendations. They can also prevent patients' emergencies before they even occur. Predictive analytics and health trackers are becoming more of a focus point for hospitals.

With advanced technology and research, people today are living longer than in previous generations. Many end of life patients suffer from dementia, heart failure or osteoporosis for years before their death resulting in a poor quality of life and dependency on others. With AI, the healthcare industry is hopeful to provide better end of life care to patients and beyond. AI can help people live independently longer and help themselves avoid loneliness.

Providing the right treatment at the right time

According to the Precision Medicine Initiative, precision medicine is "an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person." This approach tailors healthcare to the specific needs of individual patients, based on variability in genes, environment, and lifestyle. With this information, doctors and researchers can predict more accurately which prevention and treatment strategies will work best for diseases and groups of people.

AI and machine learning can go through terabytes of genetic data and can process and understand at a faster rate than humans. This data comes from all over the world. When information is presented from machine learning, clinicians can treat patients at an individual level and understand outcomes through a cause and effect model.

For example, cancer patients used to receive unpersonalized, cookie-cutter treatments that resulted in high failure rates. AI’s pattern recognition tools provide patients with access to personalized treatments tailored to their genetic makeup and lifestyle.

This will impact the pharmaceutical industry as well. Top pharmaceutical and biotechnology companies are using algorithms to shorten the drug development cycle. It’s been found that AI can generate cost savings up to 60% and shorten timelines by four years against the industry average.

Transforming the delivery of care

As hospitals continue to incorporate AI and machine learning, they are transforming the delivery of care.

Operations are becoming automation such as patient admittance and discharge, staff scheduling, financial collections, and other administrative tasks. This may seem like it takes the human interaction out of the equation, but in reality, it is free clinicians from repetitive, administrative work letting them spend more quality time with their patients. Assistance in automation increases clinician productivity.

AI is supporting frontline healthcare including medical imaging and hospital treatments. There is a decrease in medical errors and patient profiles, and AI is recognizing nature language to efficiently decipher electronic healthcare records quickly, making information clearer to patients, providers, and administrators.

Even in the beginning stages of AI, clinicians are still spending hours on administrative tasks. In 2020 and beyond, the hope is to further optimize clinical operations and workflows for maximum productivity.

In medical imaging diagnostics, AI helps radiologists spot details that escape the human eye. This too will reduce errors and catch early diagnosis. AI will continue to boost decision making.

Innovations like telehealth are quickly replacing in-person visits. Webcams are placed on clinician medical workstations and patients can access their clinicians from home on their computer. This saves us time and money and prevents the spread of disease.

Conclusion

AI is in its infancy when it comes to healthcare. It’s important for healthcare organizations to keep on top of the everchanging technological advancements, as will likely see the benefits more quickly and keep up with other leading healthcare organizations.

In order for companies to successfully implement AI in their facilities, there is a need for clear guidance. Legal, ethical and regulatory issues are associated with AI and its collecting and using patient data with patient privacy being at the highest tier. While AI-powered solutions are development, staying within these high standards is essential.

AI is forecasted to bring in $150 billion dollars in annual savings by 2026 in the United States. In order to ignite these savings, the number of active AI startups has increased 14-fold since 2000.

There are drawbacks to these early stages of implementing AI. One challenge is ensuring the data sources informing AI are not only accurate but large enough to develop correct outputs. It’s important for healthcare leaders to come together and ask the right questions, dig deeper, utilize product evaluations and create a budget before adopting AI into their strategies.

AI in the healthcare industry will continue to improve costs, service quality, and accessibility.

It is evident AI can easily surpass other leading technologies used in the healthcare industry, so it’s important for healthcare leaders to invest time now into how your healthcare organization can best utilize AI tools come 2020 and beyond.



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