💡 How is Johns Hopkins Medicine using generative AI in the revenue cycle? Watch this Becker's webinar to find out. Link in the comments 👇 💬 Joel Hammer, director for revenue cycle operations and innovation: “This is such an ever-changing landscape. You need to find that vendor that recognizes that the products that are offered now may become obsolete within the next couple of years, is willing to grow with you and has that forward-thinking mindset."
AKASA
IT Services and IT Consulting
South San Francisco, CA 7,001 followers
AKASA is the preeminent provider of generative AI solutions for the healthcare revenue cycle.
About us
Healthcare revenue cycle teams are strained. Volumes are rising, margins are constricting, and hiring and retaining enough staff is impossible. That’s why you need technology. It’s the only way things are going to get better. AKASA is the preeminent provider of generative AI solutions for the healthcare revenue cycle Our offerings are built on the AKASA platform, which integrates the company’s proprietary generative AI technology and deep revenue cycle expertise to deliver exceptional impact for hospitals, health systems, and the patients they serve. AKASA is the only AI company whose technology is trained on a health system’s own clinical data, enabling AI to better understand the specific nuances of a health system. We’ve helped healthcare providers decrease A/R days by 13%, improve efficiency by 86%, save 300+ hours of staff time per month, and increase gross yield by $30M. With investors that include Andreessen Horowitz, BOND, Costanoa Ventures, and more, we’ve raised more than $200M to help eliminate the financial complexity of healthcare. We’re rebuilding the healthcare revenue cycle with AI. Let’s chat.
- Website
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https://www.akasa.com
External link for AKASA
- Industry
- IT Services and IT Consulting
- Company size
- 51-200 employees
- Headquarters
- South San Francisco, CA
- Type
- Privately Held
- Founded
- 2018
- Specialties
- AI, Machine Learning, Revenue Cycle Management, Hospital Operations, Healthcare, Large Language Models, RCM, Automation, Prior Authorization, Healthcare Operations, Medical Billing, Revenue Cycle Automation, Claims Processing, Patient Access, Business Office, Generative AI, Claims Management, and Revenue cycle
Locations
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Primary
South San Francisco, CA, US
Employees at AKASA
Updates
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🎯 What matters the most in medical coding? Accuracy. How do we get there? Comprehensiveness. Amy Raymond weighs in on an important metric that the coding industry needs to prioritize. https://lnkd.in/ezbrfEVy
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Where is true AI and machine learning being used to improve revenue cycle management? Healthcare IT Today chatted with experts including AKASA CEO Malinka Walaliyadde to find out. Link to the article is in the comments. 👇
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AKASA reposted this
In our latest episode, I sat down with Malinka Walaliyadde to explore the groundbreaking work of AKASA, a company leveraging generative AI to revolutionize healthcare revenue cycles. He shared with us how AKASA’s AI tools simplify complex tasks like medical coding and prior authorization, boosting efficiency and reliability. Malinka also noticed a shift towards greater confidence in AI’s potential at the HFMA conference, highlighting a new era of AI acceptance. If you’re curious about how AI can transform your revenue cycle management, AKASA’s educational content is a great resource. Tune in to this episode and discover how AI is making a tangible difference in healthcare! Click this link to listen to the entire interview and get access to the episode’s resources: https://lnkd.in/epZJ-JNx #outcomesrocket #podcast #AI #healthcare #revenue #coding #medical
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🤔 What can generative AI do for the revenue cycle? And how should RCM teams prepare? Ask Stanford Health Care. ⬇️ Becker's recently hosted a webinar featuring Noel Juaire, vice president of patient financial services at Stanford, and Cory Costley, AKASA's chief product officer. 🛠️ "We have to ready our staff...so they can use new tools to dig deeper into A/R and resolve issues at a scale that we were never able to touch in the past," Mr. Juaire said. Read about their conversation 👇
Generative AI and the revenue cycle: Best practices from Stanford Health Care and AKASA
beckershospitalreview.com
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In the latest issue of AHIMA, find out how medical coding and coders will benefit from LLMs and GenAI technology. Our SVP of revenue cycle operations and deployment, Amy Raymond, weighs in. 💪 "This isn’t about taking away peoples’ jobs...It’s about using the technology to empower teams. 🤝 "Coders will work side-by-side with this amazing technology to level up."
Are LLMs Coming for Coding? Yes, and Medical Coders Should Prepare
journal.ahima.org
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🎉 AKASA is one of the fastest-growing generative AI startups to watch in 2024! Only two healthcare companies made the list. 🎉
14 fastest-growing generative AI startups
beckershospitalreview.com
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8️⃣0️⃣% of healthcare leaders say they're either using generative AI technology in the revenue cycle or exploring it. 🚀 Becker's Healthcare recently hosted a webinar on GenAI and the revenue cycle, led by experts from Stanford Health Care and AKASA. With record-bursting attendance, active Q&A, and survey responses like this, it's clear that GenAI is the future of the revenue cycle.
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AKASA is a remote company based in San Francisco. But even though we live all over the country, we still get together for fun virtual and in-person events. Last week, AKASAns gathered on Zoom to 🌱 build terrariums, 🕯️ melt candles, 🍵 drink tea, 🖌️ paint mandalas, 🌿 plant herbs, and 🛸 compete in Star Wars trivia. Lots of summertime team bonding and laughter.
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"GenAI is a magical tool that can help us be substantially more efficient and comprehensive. But having humans work together with GenAI is critical." Read Integrated Healthcare Executive's Q&A with AKASA CEO and co-founder Malinka Walaliyadde and learn: 🤖 Why generative AI is important for the revenue cycle 📈 How leading health systems are using it — and the results they're seeing 🚫 Pitfalls to avoid when implementing this technology 🤯 How it helps reduce staff burnout 🧠 Why you need to train the technology on your data
Improving Health Care Revenue Cycles Through AI
hmpgloballearningnetwork.com