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Unsure about AI? 5 Steps to evaluate and implement it confidently

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Here are five steps to start integrating AI, using medical coding and revenue cycle management as examples.

AI finger touch | © Prostock-studio - stock.adobe.com

© Prostock-studio - stock.adobe.com

AI has enormous potential to improve efficiency and decision-making in healthcare organizations, while also improving patient outcomes. It’s only a matter of time before its use becomes the industry standard. However, despite the technology’s rising popularity, some common concerns about AI persist – such as proving out more case examples and concretely measuring ROI, according to RevCycleIntelligence.

Part of the apparent resistance to AI comes from a lack of guidance about how to find the best solution for your organization. In this article, we provide a roadmap for evaluating an AI solution so you can build confidence about investing in the technology. But first, let's clear up a couple of AI misconceptions.

Common misconceptions about AI
AI's impact on the healthcare industry and the wider world is undeniable, yet lingering concerns and misconceptions persist among organizations. Questions about implementation and its implications loom large: How can organizations effectively integrate this technology into their practices and teams? Add in the technical hurdles and staff training, and you have a recipe to raise the collective blood pressure of even the most seasoned executives.

The most important point to recognize is that AI enhances team productivity. This is particularly useful in healthcare, an industry that struggles with chronic work shortages across many functions, with 58% of leaders citing staffing as their largest issue. For example, technology like autonomous medical coding takes on repetitive and time-consuming tasks to help free up medical coders’ time to work on higher-value activities. It also benefits physicians who are otherwise forced to take on coding duties and spend more time on administrative tasks.

Another common concern relates to questions about whether staff will embrace AI in their day-to-day roles. But studies prove that working with AI boosts productivity. A Harvard Business School study, for example, found that AI helped workers complete an average of 12.2% more tasks, at a rate 25.1% faster than usual. A Stanford and MIT study also revealed that using AI tools led to a 14% increase in staff productivity and higher employee retention.

The AI roadmap: 5 Steps to integrate AI into your practice

Now that you see how AI can positively impact your workforce and bottom line, how can you integrate it into your practice? Here are five steps to start, using medical coding and revenue cycle management as examples.

  1. Assess your organizational readiness: Half the battle of a successful AI integration is ensuring your practice has laid the proper foundation. This involves a detailed evaluation of your organization’s existing processes, IT infrastructure, and capabilities. What does this look like in practice? Develop a complete understanding of your workflows and the requirements for an AI system to integrate successfully. Among other assessments, this comprehensive effort upfront will surface features and needs that enable a more targeted vendor search and a smoother implementation down the road. Also, consider your data management practices. How much data is available to help fine-tune an AI application, and how is it organized? Answering these kinds of questions will help you determine if your organization is ready to implement AI.
  2. Identify inefficiencies in your operations: Once your practice appears ready for AI, the next step is pinpointing where the technology can make the most significant impact. Start by evaluating your daily operations. Do appointment bookings and patient visits flow smoothly, or do bottlenecks exist? Examine your billing cycle: perhaps coding inaccuracies lead to claim denials and revenue losses. Also, consider patient care. Are there delays in diagnosis or treatment due to administrative overload? Identifying your pain points not only clarifies where AI can streamline workflows but also reveals opportunities to elevate patient care.
  3. Set measurable goals: Having identified potential AI applications, it’s time to set clear, achievable goals. What does success look like for your practice? It might be cutting billing errors by half, enhancing patient satisfaction scores, or fully automating coding for 90% of encounters. Establish metrics that matter, both qualitative and quantitative. For instance, you can track the reduction in administrative tasks to see how it impacts staff workloads, and you can measure patient feedback pre- and post-AI integration. Setting these targets provides a roadmap for implementation and a clear benchmark for evaluating AI's impact.
  4. Research AI vendors: Finding the best AI solution for your company starts with research. Begin by cataloging the specific challenges and goals you identified from points two and three above. Next, assess the available AI providers. Which options have a proven track record in healthcare? Aspects to consider include compatibility with your current systems, ease of integration, and the level of support offered by vendors. Lastly, don’t forget to evaluate whether the solution can meet your goals. For example, can it scale with your practice? This research phase ensures you select AI tools that not only resolve current issues but also propel your practice toward future goals.
  5. Trial an AI solution and vendor: Trialing a vendor before selecting an AI solution is highly recommended. The goal is to ensure the solution meets your practice’s needs and expectations. It’s not uncommon for vendors to make big claims. Any reputable vendors will welcome the audition and allow you to see their solution in action. What should you look for in this trial run? A good vendor who helps you seamlessly integrate the AI system into your daily workflows and provides both staff training and ongoing support. You should also evaluate ROI. Does the solution save time, reduce errors, and improve accuracy? You’ll find out in this test run.

The future of your practice starts now

By now, your feelings of uncertainty about AI have likely softened. You can see that it’s another new technology, one in a long history of new technologies, that will improve jobs and the workplace.

By embracing AI now, you're not just keeping up with the times, but giving your organization a competitive edge. Efficiency improves, growth prospects expand, and success becomes more achievable.

Austin Ward is Head of Growth at Fathom, the leader in autonomous medical coding. He oversees the company's go-to-market efforts and client analytics. He brings broad experience in health systems, technology, and data science and has worked at BCG, the Bill & Melinda Gates Foundation, and in venture capital. He holds an MBA from Stanford University, MPA from Harvard University, and BAs from the University of Chicago.

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