2017 has been a year filled with technological innovation, especially with the emergence of blockchain technology and bitcoin. Additionally, there’s been a lot of talk about artificial intelligence and machine learning. Although these technologies are described as impactful as the Internet, there are fears about their full integration into society.
For those in healthcare, it’s worth evaluating and strategizing the implementation of artificial intelligence and machine learning into facilities to drive patient outcomes, improve productivity and efficiency, and reduce costs. Here are some things to consider.
What is artificial intelligence and what is machine learning?
Artificial intelligence, or AI, has been used interchangeably with machine learning. However, what exactly is AI? What is machine learning? Is there a difference between the two? Finally, why are they both important?
A Harvard Business Review article defines artificial intelligence as “a machine’s ability to keep improving its performance without humans having to explain exactly how to accomplish all the tasks it is given.” Machine learning, as defined in a Forbes article, is “an application of artificial intelligence, focusing on the idea that humans can provide machines access to data and let them learn for themselves.”
As we enter an age of technological innovation, artificial intelligence and machine learning have found their ways to impact various industries, such as retail, manufacturing, and marketing. They are both significant because big players have realized that machines are going to have a greater impact in the near future, and both artificial intelligence and machine learning will impact society in substantial ways.
Impacts of AI and machine learning on healthcare
When we think of healthcare, we think about the patient-physician relationship, doctors conducting procedures, the large amount of available clinical data, insurance, and government regulations. With the rise of AI and machine learning, several companies are working to make their mark on healthcare. Here are some ways artificial intelligence and machine learning can impact the industry:
- Machine learning and precision medicine: Precision medicine is a form of medicine that tailors healthcare to the specific needs of individual patients, based on variability in genes, environment, and lifestyle. In 2015, President Obama launched the Precision Medicine Initiative, a research effort that focuses on improving health and treating disease. Precision medicine would allow physicians and health professionals to target specific treatments, focus research efforts on new diagnoses, and work to keep communities healthy. Precision medicine relies on understanding patients’ genomes, a massive DNA dataset within an individual’s 23 chromosomes. Machine learning would help shape precision medicine by processing and understanding genomic data at a faster rate than humans. If such information is processed faster, physicians can treat patients at an individual level due to greater understanding of the specifics of a patient’s disease. Furthermore, simulation, an alternative to pattern recognition, can help physicians understand outcomes through a cause and effect model, which could impact precision medicine and population health management.
- Cybersecurity and privacy: Cybersecurity and privacy are major concerns in healthcare, especially protecting patient privacy. Although steps have been taken to prioritize security, machine learning could help reduce any potential threats through the generation of intelligent algorithms and strong protection of clinical health data. Machine learning tools might be able to identify EHR usage patterns and therefore detect any outstanding events at a faster rate than humans can, therefore altering authorities and reducing risk of security breaches.
- Diagnostic and mobile health applications: Artificial intelligence in healthcare is currently focused on disease identification and diagnosis. AI has been incorporated into smartphone apps to aid in patient treatment and diagnoses. Now, machines are learning to read CT scans and other imaging diagnostic tools to identify any visible abnormalities. AI and machine learning will also impact consumer health applications. Some tools are currently using emotional and artificial intelligence to detect depression through qualitative questions and collection of health information. AI will be further integrated in applications that will impact patients’ health experiences outside hospitals. Furthermore, AI could be used to identify at-risk patients within a population.
- Data and analytics: The amount of available data has rapidly increased in the last several years. As AI further develops, it will become more integrated with data and analytics, influencing how data is stored, shared, and used in various healthcare applications. However, in order for artificial intelligence and machine learning to effectively work, hospitals need good, reliable, and timely data. At Dimensional Insight, our technology not only ensures the highest levels of data integrity and meaning, but it is also completely compatible with emerging machine learning and AI techniques. It provides the data algorithms needed and then incorporates the results back into analytics information to make it accessible.
What does the future of healthcare look like?
As hospitals consider incorporating AI and machine learning into their budgets and strategies, many questions arise when thinking about the impact of this new technology. Will jobs be lost, and if so, who will be at risk? Will it impact the patient-physician relationship? How will it transform the nature of decision-making? Although there is much doubt surrounding AI, healthcare providers need to start preparing for these major technological forces to disrupt the industry.
If you’d like to learn about predictive analytics and simulation, you can download our Simulation eBook now.