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Outsourcing will pivot to a more surgical, targeted strategy, focusing on high-impact, specialized areas like revenue integrity, underpayment recovery, and the more commonplace out-of-state Medicaid and small balance recovery work where RCM outsourcing supplements streamlined, automation-empowered teams instead of replacing them.
At MEDITECH Live, John chatted with Mike Elder and Kelsey Reed at the southwest Georgia health system, which recently opened a Living and Learning Center to really recruit and train the next generation of nurses. The limitations of interoperability has made value-based care more complex , said Ashay Thakurat Cedar Gate Technologies.
Tellingly, 60% of recommended imaging isn’t followed up on , and panelists said the one-two punch of limited interoperability and poor engagement play a big part in that. The Healthcare IT Today community expects automation will continue transforming RCM in 2025 , with a primary focus on eliminating waste and reducing inefficiency.
Bn by 2032, driven by the demonstrated value in improving diagnostics, replicating patient responses, simulating disease progression, and synthesizing datasets for testing and training. RCM is Ripe for GenAI-Enabled Transformation In simple words, it goes beyond note-taking and summarizing.
Ultimately, the integration of true AI and machine learning in RCM contributes to greater accuracy, reduced denials, and a better patient experience. The best RCM work is eliminating the work itself, and if the work cannot be eliminated then it’s about automating the work through AI and machine learning models.
AI-based technologies that enhance medically trained natural language processing (NLP) not only have the power to mine massive volumes of data at scale but also to understand the deeper context and meaning within each clinical note.
RCM will be managed by AI-powered agents every step of the way, including generating appeals letters, submitting appeals to payers, and converting paper EOBs to ERAs. In 2025, we predict that using AI-powered agents will reduce the cost of Revenue Cycle Management (RCM) by 70%, helping streamline the end-to-end billing process.
Read more… Overcoming Obstacles to Healthcare Training Data Accuracy. AI models need to be trained on high-quality data. Cybersecurity, privacy, and interoperability represent the biggest hurdles that vendors will need to overcome. RCM vendor Access Healthcare acquired Envera Health , a patient engagement vendor.
The Sequoia Project has released additional documentation support the implementation of TEFCA , the Trusted Exchange Framework and Common Agreement for health IT interoperability. Illinois-based Midwest Orthopaedic Center went with eClinicalWorks for its patient engagement, cloud-based EHR, and RCM products.
The most pressing needs include better data collection, training AI models, privacy and security, and a smart approach to personalization. Read more… 2024 Health IT Predictions: Interoperability, Data, and the Cloud. Read more… 2024 Health IT Predictions: The Healthcare Workforce. million in funding.
Achieving Interoperability One Practical Byte at a Time. Upstate New York’s Rochester Regional Health began its interoperability journey with lab data , Colin Hung learned, as there was a clear need to bring in lab test results from many external sources to help care teams make better clinical decisions and improve outcomes.
The Consortium for State and Regional Interoperability is partnering with eHealth Exchange in anticipation of the exchange being named a Qualified Health Information Network. Smile Train and BioDigital launched a VR platform for cleft and palate surgeries , enabling surgeons around the world to collaborate.
Digital surgical platform Proximie is partnering with Smith&Nephew on advanced robotics and sports medicine training resources. Products Interoperability platform Particle Health launched Particle FOCUS , a data product suite that provides comprehensive patient health information across seven chronic disease states.
Ben Scharfe at Altera Digital Health outlined why organizations must address the challenge of integrating semi-structured data from ambient listening tools into EHR, analytics, and RCM systems. Roei Sherman at Mitiga said the answer is improving visibility, training, threat detection, and incident response. million in Series A funding.
Read more… Exploring Augmented and Virtual Reality Apps for Training. In conversations with Inteleos and Mobiquity, Andy Oram unpacked how VR can simulate health assessments and how AR can train emergency responders for disaster situations. Read more… To Achieve Success With AI, Focus on the Results.
The market will see increased asks/attention for bots as they are critically needed in RCM to offset staff shortage, enhance staff retention, and accelerate tasks (ultimately cash flow). Automation is making a big difference in revenue cycle management (RCM). Even chatbots that can triage and provide information are automated.
This frees up staff to focus on more complex and strategic aspects of RCM. Additionally, hospitals and health systems will explore new training and upskilling programs to ensure teams are ready for the influx of automation. If managed incorrectly, this can actually impact outcomes.
However, while there’s plenty of hype around generative AI, few companies possess the depth and quality of health data and financial resources to accurately train models with the goal of making healthcare more affordable, equitable, or effective.
Read more… Technology’s Role in Advancing Interoperability. Read more… Best Practices for Training During EHR Implementation. Read more… GenAI Is Catalyzing Healthcare RCM Transformation. Streamlining RCM can improve access to high-quality and affordable healthcare.
One part of this initiative is using 30 years’ worth of data to train an internal version of ChatGPT. Read more… Healthcare IT Today Podcast : Is Epic the Biggest Obstacle to Interoperability in Healthcare ? They also touched on other main barriers to interoperability and tried to predict where interop would be in 10 years.
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