Resources for job seekers, health information technology workers, and human resources professionals. Plus, 7 job roles that will drive healthcare AI development.
Hey there, humans. Are you ready to do what artificial/augmented intelligence can’t do for healthcare without your help? Do you have the skills you need to guide AI to its highest and best use?
Medical researchers and HIT visionaries have been exploring how AI might propel healthcare forward for years. But the pace of interest and innovation in healthcare use cases has accelerated to the point where AI is now a budget item for a significant percentage of IT leaders.
According to a recent HIMSS/Arcadia survey, 29% of healthcare organizations have already implemented AI and ML (machine learning), 33% plan to implement the technology within the next two years, and 25% have longer-range AI plans.
AI Innovation in Healthcare
Why all the interest—and why now? The 2022 release of ChatGPT has been a major catalyst with healthcare users exploring its utility for summarizing clinical notes and improving patient engagement.
AI is also being used in healthcare to:
- Flag key findings from lab tests, imaging, and data from patient monitoring devices;
- Support clinical decision making and treatment plans;
- Upgrade and simplify clinical documentation;
- Drive personalized medicine forward;
- Improve patient scheduling;
- Track and restock inventory;
- Anticipate and plan for short-term and long-term healthcare staffing needs;
- Optimize revenue cycle management;
- Revolutionize medical and public health research.
By simplifying existing healthcare processes and creating new, more efficient ones, AI has the power to slash healthcare spending in the U.S. by up to 10% over the next five years. Savings could reach $360 billion, researchers at McKinsey and Harvard estimate.
Will AI Take My Job… Or Find Me a New One?
If you are a healthcare professional, you may be wondering if robots are coming for your job. We don’t think so, but AI is going to eliminate a multitude of human tasks and be disruptive to healthcare and other industries. Goldman Sachs economists estimate that roughly two-thirds of U.S. occupations are exposed to some degree of automation by AI.
The good news, especially for knowledge workers and IT professionals, is that AI is more likely to complement your existing role than replace it, according to John McDaniel, FACHDM, our Chief Innovation & Transformation Officer.
“If anything, AI is going to usher in a new era of job growth in healthcare IT,” says McDaniel. “HIT professionals will be vital resources helping organizations harness the power of AI, and we’re going to see new categories of jobs that didn’t exist ten years ago.”
The human HIT skills that got you here will get you there.
Healthcare AI’s quality and usefulness is nothing without good data, so the data skills that HIT pros have mastered are essential to harnessing its power.
There are two categories of AI. The first, machine learning (ML) learns from data and makes predictions and decisions based on that data.
The second, deep learning, is more complicated and depends even more heavily on good data. Deep learning relies on neural networks, which are computer systems inspired by the human brain and nervous system. Over time, deep learning becomes better at making decisions because the AI incorporates what it learned from past decision-making.
There is a lot of data for AI to learn from. The average hospital generates 137 terabytes of data a day. Healthcare alone generates 30% of the world’s data, and that data is piling at a 36% compound annual growth rate.
7 healthcare AI job descriptions, plus links to help you learn more.
To build AI careers, HIT professionals need to figure out how to enhance and deploy the skills they already have.
We dug into resources like the HIMSS Job Mine, the recently updated HIMSS library HIT job descriptions, and our own current job postings to suss out AI-related skills healthcare employers are looking for right now. Here’s the lowdown.
Health Data Analyst
Ensures that data is optimal for AI – machine learning, deep learning, and natural language processing (NLP).
Education and Mindset: Bachelor's or Master’s degree in Health Informatics, Data Science, Computer Science, Statistics, or related field. Strong communication and collaboration abilities. Attention to detail and a commitment to data accuracy and quality.
Skills: Proficiency in programming languages such as Python or R for data analysis and AI; SQL for data retrieval and manipulation; data visualization tools such as Tableau and Power BI; and EHR and healthcare data standards such as HL7, FHIR. Strong knowledge of AI and machine learning techniques, including deep learning and natural language processing (NLP).
Medical Data Scientist
Leverages data science techniques and artificial intelligence (AI) to improve patient care or advance medical research.
Education and Mindset: Master's or Ph.D. in Data Science, Computer Science, Bioinformatics, Medical Informatics, or a related field with a strong focus on healthcare data and AI. Expertise in statistical analysis, data mining, data visualization. Understands context for the data, such as medical research or clinical workflows
Skills: Proficiency in programming languages such as Python or R for data analysis and machine learning development; database management systems, such as SQL, for data retrieval and manipulation; and healthcare-specific software and tools, including EHR systems and medical imaging software.
Healthcare AI Engineer
Applies AI and machine learning techniques to address various challenges and opportunities within healthcare. Workers currently in healthcare data modeler and data architect roles have many of the skills that healthcare AI engineering will require.
Education and Mindset: Bachelor’s or graduate degree in Computer Science, Data Science, Bioinformatics, or related field, with experience in AI and healthcare. Exceptional problem-solving, communication and collaboration skills for interdisciplinary teamwork. Sound understanding of patient privacy and data security requirements.
Skills: Programming skills in Python, R, and other common AI languages. Knowledge of healthcare data standards (e.g., HL7, FHIR) and medical terminologies (e.g., SNOMED CT, ICD-10). Experience building and deploying machine learning models. Ability to work cross-functionally with healthcare professionals to identify needs and integrate AI solutions.
Healthcare AI Prompt Engineer
Crafts and refines AI prompts and conversational interfaces that drive healthcare interactions such as clinical documentation, patient communications, and interactions with payers.
Education and Mindset: Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, Computational Linguistics, or a related field with a focus on AI and NLP. Background in healthcare data, understands healthcare-specific language and terminology, and is familiar with clinical workflows. Exceptional problem solver. Strong communicator who works effectively across interdisciplinary teams.
Skills: Proficiency in programming languages used in AI and NLP. Works effectively with database management systems like SQL, and understands healthcare data standards like SNOMED CT and LOINC.
Healthcare AI Project Manager
Plans and executes AI projects that harness interdisciplinary teams. Provides the data and analysis necessary to make data-driven decisions.
Education and Mindset: Bachelor's or Master's degree in Project Management, Healthcare Management, Computer Science, or a related field. Problem solver, critical thinker. Excellent communication and leadership abilities.
Skills: Leverages project management software, data analytics and data visualization tools, and collaboration and communication tools.
Healthcare AI Ethics, Governance, and Compliance Specialists
AI will present huge challenges for the professionals who ensure that healthcare operations comply with all relevant laws, regulations, and ethical standards. These professionals will need to account for AI in compliance audits, risk assessments, and internal investigations.
Education and Mindset: Law degree or a Bachelor’s or Master’s Degree in Healthcare Administration. Deep working knowledge of regulations that govern data, such as HIPAA.
Skills: Exceptional analysis and problem-solving skills. Attention to detail. Strong organization and communication skills.
Healthcare Cybersecurity and Data Privacy Specialists
Think healthcare information security is challenging now? Strap in for a much bumpier ride.
Back in the good old days, cybercriminals needed to know how to code or how to buy pre-packaged codes in order to launch attacks on healthcare systems. Now they are asking AI to do these dark arts for them. Now more than ever, healthcare needs professionals who can prevent such attacks, and resolve them when they happen.
Many healthcare organizations boosted their 2022 cybersecurity budgets by 15%. Annual cybersecurity spend will continue to climb as systems feed machine learning the data it needs, some experts predict.
Education and Mindset: Bachelor's or Master's degree in Cybersecurity, Information Technology, Computer Science, or a related field. Relevant certifications such as CISSP. Strong analytical and problem-solving skills. Passion for learning about evolving cybersecurity threats and adapting practices to combat those threats.
Skills: Proficiency in security tools and technologies, including firewalls, intrusion detection/prevention systems, antivirus software, and endpoint security solutions.
Ready to boost your own healthcare AI skills?
Visit our HIT job board to learn what employers are looking for. Bookmark it for updates on opportunities as AI rapidly evolves.