{"id":3450,"date":"2025-01-26T16:43:40","date_gmt":"2025-01-26T16:43:40","guid":{"rendered":"https:\/\/zenmedinc.com\/blog\/?p=3450"},"modified":"2025-01-26T18:04:33","modified_gmt":"2025-01-26T18:04:33","slug":"how-will-ai-improve-coding-and-billing","status":"publish","type":"post","link":"https:\/\/zenmedinc.com\/blog\/how-will-ai-improve-coding-and-billing\/","title":{"rendered":"Lions and Tigers and AI, Oh My \u2013 How Will AI Improve Coding and Billing in Your Practice"},"content":{"rendered":"\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

As Dorothy stepped onto the yellow brick road with Toto, realizing they weren\u2019t in Kansas anymore, so are we as a people in the healthcare landscape, as we embrace Artificial Intelligence. Over the next few years, AI will be a major part of the healthcare landscape and a dynamic process of integration into the various sectors under the healthcare umbrella. Already, there are close to 150 million Americans enrolled in government programs such as Medicare, Medicaid, and the Child Health Insurance Program (CHiP). CMS alone houses one of the most vigorous data portfolios in the federal government. They store millions of patient and provider claims, beneficiary enrollments, and medical records. There has been almost <\/span>$30 billion<\/b><\/span> raised by various healthcare start-ups to promote AI over the last three years and a recent report by McKinsey & Company forecasts that generative AI will produce significant reductions in overall healthcare costs in the United States upwards of <\/span>$150 billion annually by 2026<\/b><\/span>. Overall projections point to AI\u2019s contribution to the global economy market, which should come close to <\/span>$16 Trillion by 2030<\/b><\/span>. <\/span><\/p>

We know that many practices and facilities struggle with the day-to-day of most administrative practices in healthcare due to outdated and inefficient EMRs and process flows. Recently, Chime-Cerner conducted a survey that reflected a disappointing <\/span>54 percent of referrals<\/b><\/span> resulted in an appointment, which ended up costing close to <\/span>$971,000<\/b><\/span> per physician annually<\/b><\/span>.<\/span>\u202f\u202fAdditionally, the same survey yielded roughly <\/span><\/span>40 percent of respondents<\/b><\/span> stating referral issues cost an average of almost <\/span>10 percent of patient revenue annually<\/b><\/span>. The overall impact of moving to an AI environment in healthcare is an overwhelming cost saving to providers, practices, facilities, payer spaces, and ultimately patients, with better health risk outcomes. <\/span><\/p>

Coding and AI: <\/b><\/span><\/p>

We know that accuracy in coding plays a vital role in healthcare and CMS requires a 95% accuracy rating in submitted claims. So, it is mission-critical to ensure that certified coders and any AI programs are monitored and audited regularly. The manual coding process is often littered with coding errors due to a lack of education, no understanding of variances in payer rules and\/ or billing processes, and timely filing of claims for reimbursement. Often, claims are submitted with numerous errors which leads to incorrect billing codes and various compliance issues. When AI algorithms are present, coding accuracy for non-complex coding has shown marked improvements. An AI-driven system allows for analyzation medical records, the extrapolation of pertinent data, and the designation of correct billing codes with a high level of precision. The utilization of machine learning algorithms allows these systems to continuously learn and adapt to evolving coding standards, ensuring precision and reducing the risk of costly mistakes.<\/span><\/p>