Shining a Light on Healthcare: Phare Health’s Mission to Illuminate Financial Sustainability and Patient Care

Healthcare exists for one purpose: patient well-being. Yet, amidst the dedication of medical professionals, a hidden reality lurks – financial struggles within hospitals. In this complex system, fair reimbursement often gets obscured by inaccurate coding, hindering not just hospitals’ sustainability but ultimately, their ability to deliver optimal care.

At Phare Health, we’re on a mission to illuminate this critical intersection, where financial health meets patient health. We believe hospitals shouldn’t have to navigate financial shadows when caring for patients. That’s why we’re starting with clinical coding, the language that translates medical actions into reimbursement.

Our proprietary AI technology delves into medical records, extracting vital information with precision. It identifies inconsistencies and gaps, ensuring that clinical codes accurately reflect the care delivered while identifying gaps in clinical documentation. This leads to fair and timely reimbursement, but the benefits ripple far beyond that.

For hospitals, Phare Health is a beacon of financial clarity. Transparent coding reveals true costs, empowers strategic budgeting, and illuminates opportunities for efficiency. Resources freed from chasing incorrect payments can be redirected towards patient care, nurturing a positive cycle of financial stability and improved service.

But our vision extends beyond individual hospitals. By ensuring accurate coding across the healthcare ecosystem, we’re laying the groundwork for a data-driven future. Imagine a landscape where precise financial information fuels research, informs policy decisions, and guides resource allocation, leading to a more resilient and equitable healthcare system for all.

This is not just about numbers on a spreadsheet. It’s about empowering hospitals to focus on what they do best – caring for patients. When doctors and nurses aren’t burdened by financial uncertainties, they’re free to devote their energy to what truly matters: the well-being of their patients.

Join us in this mission. Let’s shine a light on the back office of healthcare. Together, we can ensure that hospitals have the resources they need to be beacons of health, where every interaction, every procedure, and every moment of care is illuminated by financial transparency and patient-centred dedication.

Beyond the Code: A Medical Coder’s Perspective on AI

Medical coding is a fascinating puzzle – essentially, it’s the translation of medical narratives into alphanumeric codes that drive healthcare reimbursement, reporting and research. Coders have performed their job in the same way for decades and the prospect of the AI Revolution sweeping through our field is fear-inducing and exciting all at the same time.  AI has the potential to raise the effectiveness of our efforts and assisting us with the following challenges:

  • The Knowledge Avalanche: Medical coding guidance is constantly being expanded and revised with emergence of new technologies, procedures, and diagnoses. Staying on top of this new information requires continuous learning and meticulous attention to detail.
  • The Documentation Jungle:  Each provider has their own unique style, leading to chart notes that may be ambiguous or inconsistent. Documentation issues make it extremely difficult to tell the true clinical story, often due to a mismatch between the provider narrative and codeable information.
  • The Time Crunch: Efficiency is crucial.  Hospitals and clinics have tight deadlines for submitting claims, putting pressure on coders to work quickly while maintaining quality.
  • The Analysis Paralysis: The complex nature of medical cases, understanding of the guidelines, and the pressure to perform may overwhelm and create an inability to decide on the correct code.
  • The Frustration of Denials:  Even the most meticulous coder can face claim denials from insurance companies due to medical necessity, coding errors or missing documentation. This can be disheartening – “Do I even know how to code?” is the constant internal monologue.

Embracing the AI Revolution  

If AI can reduce or eliminate all of the above, won’t it replace me? Absolutely not, AI isn’t here to replace us but to help us!  Imagine having a digital assistant that can provide real time decision support with the latest coding guidance and correct code suggestions.

AI can flag potential inconsistencies and missing information in records, allowing coders to focus on resolving them before submission. Predictive analytics powered by AI can even help anticipate denials, streamlining the appeals process.

With AI, our roles are elevated from production coders to empowered coding experts. AI can handle the grunt while we leverage our expertise and critical thinking skills to tackle the most complex cases, resolve coding opportunities missed by AI, and dedicate more time to the knowledge work we were trained to perform. 

The future of medical coding isn’t about humans versus machines – it’s about collaboration. By adopting AI tools, we can improve efficiency, accuracy, and ultimately, patient care.AI is no threat – it is a powerful ally in the ever-evolving world of medical coding.

The Glitches in the Matrix: Why AI in Healthcare Revenue Cycle Isn’t a Silver Bullet (Yet)

Artificial Intelligence (AI) promises a revolution in healthcare, and the revenue cycle is a prime target for its transformative potential. However, implementing AI effectively in RCM presents unique challenges that can’t be ignored. Here’s a closer look at the roadblocks on the path to a fully AI-powered revenue cycle:

Data Hurdles:

  • Data Quality: AI thrives on clean, complete data; however the electronic health record (EHR) is far from clean (e.g. one analysis found that half the content of an EHR was copied forward). Inconsistent documentation, coding errors, and missing information in medical records can significantly hinder the accuracy and effectiveness of AI algorithms.
  • Data Interoperability: Healthcare data often resides in siloed systems, making it difficult for AI to access and integrate the information it needs to function optimally.

Algorithmic Obstacles:

  • Complexity of Healthcare data: Medical coding and billing involve a vast array of rules, regulations, and nuances. Developing AI models that can navigate this complexity and handle edge cases effectively remains a challenge.
  • Explainability Issues: AI algorithms can sometimes be “black boxes,” making it difficult to understand how they arrive at specific decisions. This lack of transparency can be problematic for regulatory compliance and provider trust.

Human Hurdles:

  • Change Management: Transitioning to AI-powered RCM requires cultural change within healthcare organisations. Staff may need training and support to adapt to new workflows and overcome potential fears of job displacement.
  • Integration Challenges: Integrating AI seamlessly with existing IT infrastructure can be complex and require significant upfront investment.


The Road Ahead: Overcoming the Obstacles

Despite these challenges, AI holds immense potential for RCM. Here’s what can bridge the gap:

  • Focus on Data Quality: Improved data capture practices, standardisation, and data cleansing efforts are crucial for laying a solid foundation for AI.
  • Open and Interoperable Systems: Standardising data formats and promoting interoperability between healthcare systems will allow AI to access the data it needs to function effectively.The adoption of data standards like FHIR and regulations like the 21st Century Cures Act are helping to break down data silos.
  • Explainable AI Models: Developing AI models that provide clear explanations for their decisions will build trust and ensure regulatory compliance. LLMs actually offer an opportunity to make traditional AI systems more interpretable and user-friendly.
  • Collaboration is Key: Successful AI implementation requires collaboration between healthcare providers, IT teams, and AI vendors, using the principles of human-centered designs.


Phare Health: Your Partner in AI-Powered RCM

While challenges exist, Phare Health is committed to helping you navigate the journey towards an AI-powered revenue cycle. We understand the importance of data quality and offer solutions that can help you clean and standardise your data. Additionally, our focus on explainable AI ensures transparency and builds trust in our solutions.

By partnering with Phare Health, you gain access to cutting-edge AI technology combined with a deep understanding of healthcare RCM. Together, we can overcome the hurdles and unlock the true potential of AI to optimise your revenue cycle and ensure long-term financial stability.

12 Hospital Tech Startups to Watch, According to VCs

“Phare Health is a tool used to automate non-clinical administrative tasks. Founded by ex-DeepMind and Google Health workers, its initial approach of using AI to improve non-clinical workflows focused on medical coding really stands out as a clear wedge into the broader back office workflows. This approach is essential to ensure hospitals effectively manage resources and recover costs for the care delivered. Having accurate coding is essential for population health management at scale.”

Continue reading on

Our Investment in Phare Health: Making the Healthcare System More Financially Resilient

“Making healthcare organizations more financially resilient is the mission of Phare Health, an AI-native financial operating system that we believe provides a lighthouse for the industry. Phare Health co-founders Martin Seneviratne, Lee Kupferman, and Tymor Hamamsy, to us, not only have unique talent and expertise that sets them apart to take on this challenge, they are also funny, kind and positive – the type of founders we dream of partnering with. ”

Continue reading on