🩺 ChatGPT: Nurse's BFF
Plus: McKinsey Report, Tackling Healthcare’s biggest burdens with AI | Mark Cuban Cost Plus Drug Company | Emerging Tech in IoMT Privacy
TOGETHER WITH
Good morning!
Welcome to Healthcare AI News, your weekly dose of the latest developments and headlines in the world of Healthcare AI.
In this issue, we explore:
✅ Headlines: Hospitals begin test driving Google’s medical AI chatbot
✅ Industry: Powering wearable health monitoring devices without batteries
✅ Feature: Workforce ecosystems and AI
✅ Interesting Reads: Does sugar actually feed cancer?
✅ Tech: 7 IT consultant tricks CIOs should never fall for
✅ Venture Pipeline: J&J to Nanobiotix, $1.8B licensing deal
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HEADLINE ROUNDUP
Hospitals begin test driving Google’s medical AI chatbot (Read More)
Physicians who use AI will replace those who don't (Read More)
ChatGPT by the bedside? New group to explore AI in nursing (Read More)
McKinsey Report, tackling Healthcare’s biggest burdens with AI (Read More)
GatesNotes: The risks of AI are real but manageable (Read More)
Healthcare privacy risks of AI chatbots (Read More)
Harnessing AI for pharma sales (Read More)
Inadequate mental healthcare has given rise to AI therapy – What’s the harm? (Read More)
TOGETHER WITH AE. STUDIO
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INDUSTRY NEWS
Mark Cuban Cost Plus Drug company, Posterity Health collaborate on men's health care (Read More)
Phone data in public health efforts may magnify health inequities (Read More)
NLP tech can help providers address social drivers of health (Read More)
Powering wearable health monitoring devices without batteries (Read More)
AI’s increasing role in the healthcare delivery system: Key legal considerations (Read More)
The impact of generative AI on medical devices (Read More)
Machine learning model predicts PTSD following military deployment (Read More)
THE FEATURE
Workforce Ecosystems and AI
Medical AI doesn’t just tackle the staffing crisis. Here’s how it’s impacting your whole workforce ecosystem.
If you’ve been paying attention, you know healthcare has a staffing problem.
And it’s not just a local issue. The World Health Organization projects a global shortage of 15 million healthcare workers by 2030.
Medical AI is helping to address this crisis. AI-enabled solutions are bringing less friction to health workers ranging from nurses to insurance claims processing.
However, for a fuller understanding of how AI is (or may soon be) impacting your healthcare organization, we also need to consider how AI impacts the overall workforce ecosystem your organization is in, including…
The design and supply of work
How work is conducted
How companies are organized and evaluated.
In today’s feature, we’ve put together a primer on how to evaluate medical AI’s impacts on these 3 elements of your part of the healthcare industry
Let’s dive in, shall we?
How AI impacts the design and supply of work in healthcare
One of the biggest ways AI is changing the design and supply of work in healthcare—and beyond—is through enabling more integrated teamwork.
The rise of digital health platforms has allowed AI to fill in the blanks between healthcare’s many operational workflows. This, in turn, has further increased the demand for medical AI tools—from AI medical scribe software to clinical design support.
This is also where we come back to that clinical staffing crisis.
In healthcare, the way clinical workflows operate determines which and how many staff need to be hired and trained. AI may then be used to improve communication and matching in that labor supply—such as through AI-enabled staffing tools like Nomad Health’s collaboration with PandoLogic.
Here are some questions to consider for how AI factors into the work design and labor supply in your area of healthcare expertise:
How is work delegated or supplied in your niche of the healthcare industry? Where may there be inefficiencies?
What roles can be broken down into more modular tasks that can be delegated to (or with the help of) AI?
AI-human collaboration is changing the way work is conducted in healthcare
Of course, AI isn’t just impacting how work is organized and human staff are acquired.
In certain cases—even in healthcare—AI is beginning to operate as a collaborator. As an assistant or even a colleague.
While news of ChatGPT passing clinical board exams may be click-worthy, we’re not likely to see AI replacing clinicians anytime soon. Across healthcare, AI assistants can free clinicians from the laborious tasks of image analysis or data entry—and, in many cases, even perform more effectively.
We’re extra excited about this path to addressing clinician burnout. So, here are some clinical AI assistant tools we’re following (and you should, too):
MedInReal: Clinical note transcription software for physicians
Eyenuk: AI-enabled screening for diabetic retinopathy
Symptoma SME: A symptom-based triage tool for patient self-assessment
How AI impacts organizational structure and evaluation in healthcare
The natural extension of rising AI-human collaboration? It doesn’t happen just in 1:1 relationships.
AI is getting nitty gritty into monitoring healthcare firms’ overall performance. It does this through its superior ability to quantify and analyze everything from standard KPIs to less tangible metrics like mood and leadership potential.
Of course, there’s always the chance that workers may perceive such monitoring as intrusive surveillance—even if it does overall improve their efficiency. Especially in healthcare, maintaining the human touch and trusting clinicians’ intuition with their patients is of paramount importance. It’s an intangible aspect of care that AI-enabled quantification can feel incompatible with.
When considering AI-enabled evaluation and analysis in your healthcare organization, ask yourself the following questions:
Which KPIs is your workforce already monitoring? Which additional metrics can AI make easier to track?
Where does your workforce experience the most burnout? How can more intelligent metric tracking help you predict—and intervene—in this burnout?
How can you ensure your AI-enabled monitoring prioritizes your workforce’s humanity and doesn’t reduce them to scores? Where may there be risk for AI-based discrimination?
Final Thoughts from Healthcare AI Team
We get it: “Reducing clinician burnout” may be starting to sound like a buzzword among digital health companies offering AI solutions.
However, this potential impact of AI in healthcare is nothing to scoff at.
So, we’ll leave you with this advice: When infusing medical AI into to your workforce ecosystem, be open and curious. But also be mindful about the roles you allow AI to play in your organization.
Tell us: What did we miss? Reply back and let us know what aspects of the healthcare workforce ecosystem you see AI making the biggest splash in.
INTERESTING READS
TECH NEWS
VENTURE PIPELINE
A SPECIAL MESSAGE FROM OUR PETS! 🐾
TWEET OF THE WEEK
🍏🚗 Apple's never-ending innovation doesn't stop at design & construction for the rumored #App#AppleCarThey're reinventing the 🎶 sound system too! 🎵 5 patents point to an immersive, personalized, dynamic audio experience.🔈🎚🎛
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— Healthcare AI Newsletter (@AIHealthnews)
Jul 12, 2023
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