HR Technology

Lessons for HR Technology: AI in Health Care

While many industries are playing catchup when it comes to implementing technologies like artificial intelligence (AI), one industry, in particular, has shown the value such technology offers.  That industry is healthcare. Take note, as much of what AI has done for that industry translates very well into the needs of the HR professional.


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Healthcare spending in the United States accounts for trillions of dollars per year and nearly 20% of our gross domestic product. So, it makes sense to take advantage of tools that can increase the efficiency of such a substantial part of our economy.

A task force set up by Connected Health recently published a report titled “Policy Principles for Artificial Intelligence in Health,” which discusses and makes recommendations on the use of AI in health care.

We’ll discuss the recommendations in a later post, but first, we’ll look at the current uses and benefits of AI in this industry.

Medical Records

“Every two years, the amount of available data in the world doubles,” says D/SRUPTION Senior Staff Writer Laura Cox in an article on AI in health care. “Medical professionals need high-quality administrative organization to make sense of mass datasets.” Therefore, AI is a great tool for managing and processing this massive amount of information.

Clinical Decision-Making

Companies like IBM have developed medical algorithms with analytical reasoning capabilities that can use existing data to provide practitioners with additional clinical knowledge.

AI-Powered Health Assistants

The healthcare industry has its own version of Alexa and Siri—Catalia Health’s Mabu, which is built on a Health Insurance Portability and Accountability Act (HIPAA)-compliant system located in the cloud and can provide real-time data about the patients it interacts with.

Precision Medicine

AI can be used to assist in the development and prescription of medications by looking at genomic factors, for example.

Clinical Trials Procedure

“Traditional clinical trials are slow and expensive, taking years to complete and often failing due to participant fall out,” says Cox. “This is largely because of legacy processes that make it difficult both for clinics and the people they invite to join the trials. However, there are various ways that AI can improve clinical trials, from matching potential participants with relevant trials to finding meaning in test results.”

AI has the potential to revolutionize many industries, and the size, complexity, and importance of the healthcare industry make it a great field in which to deploy these technologies.

Artificial intelligence (AI) has been revolutionizing the way people and businesses complete a variety of tasks, and it promises to continue to do so at an increasing pace. One area that has great potential for AI applications is the healthcare industry.

Goals for Healthcare AI Systems

The policy principles report suggests four goals for healthcare AI systems:

  • Improving population health
  • Improving patient health outcomes and satisfaction
  • Increasing value by lowering overall costs
  • Improving clinician and healthcare team well-being

The report also proposes 11 policy principals to achieve these goals.

1. National Health AI Strategy

Given the importance of AI in health care, policies should be implemented on a national level rather than having different policies in each state.

2. Research

Funding should be facilitated for the research and development of AI in health care at levels sufficient to advance the new science.

3. Quality Assurance and Oversight

With so much at stake and with the power of this new technology, quality assurance and oversight need to be top focuses.

4. Thoughtful Design

“Policy frameworks should require design of AI systems in health care that are informed by real-world workflow, human-centered design and usability principles, and end-user needs,” says the report, which adds that AI systems should also be designed to overcome existing industry fragmentation and dysfunctions.

5. Access and Affordability

The report suggests implementing payment and incentive policies, designing systems with an eye toward value, and seeking scalable solutions to promote access and affordability.

Connected Health proposes these five policies to successfully integrate AI technologies into the healthcare industry, and we’ll look at the last six in our final post covering this report.

6. Ethics

The medical industry has a long-standing and well-developed system of ethics in place that the report says needs to be used to guide the development and use of healthcare AI technologies.

7. Modernize Privacy and Security Frameworks

Using AI to collect, analyze, and store sensitive patient data will require re-evaluating and modernizing existing privacy and security frameworks to support advanced technology.

8. Collaboration and Interoperability

The report recommends fostering collaboration among policymakers, health AI technology developers and users, and the public to promote eased data access.

9. Workforce Issues and AI in Health Care

The combination of an aging population and lower birth rates means that AI will be critical in increasing the productivity and efficiency of the smaller cadre of medical professionals treating a relatively larger patient population.

10. Bias

Data bias and errors are expected to remain an issue with AI systems, so steps should be taken to identify, disclose, and mitigate bias, as well as to ensure that bias does not cause harm to patients or consumers.

11. Education

This is two-fold. Policymakers are encouraged to include a curriculum in academic and medical education that advances providers’ understanding of and ability to use health AI solutions, and the report recommends that patients and consumers also be educated to help them better understand how AI is being used to treat them.

AI has the potential to dramatically change the healthcare industry, but because of the enormous size and importance of this industry, such a powerful tool needs to be used carefully and responsibly. Expect to see a growing number of policy recommendations as AI’s healthcare footprint continues to grow.