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Automating Medical Billing and Coding: Minimizing Mistakes and Easing Employee Exhaustion

Healthcare billing teams are benefiting from AI tools by increasing accuracy, cutting down on claim denials, and alleviating burnout. As a result, the management of revenue cycles has been streamlined comprehensively.

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3 min read
Streamlined healthcare billing teams capitalize on AI advancements, minimizing claim errors,...
Streamlined healthcare billing teams capitalize on AI advancements, minimizing claim errors, denials, and work stress, thereby enhancing overall revenue cycle efficacy.

Automating Medical Billing and Coding: Minimizing Mistakes and Easing Employee Exhaustion

The intricacies of healthcare systems and their revenue cycle management (RCM) can be daunting. Errors in coding, denied claims, and inefficient processes can lead to financial losses and inadequate patient care. One staggering statistic indicates that up to 80% of medical bills may contain errors, with 42% of claim denials rooted in coding issues.

Historically, billing and coding teams have battled through a labyrinth of codes manually, using the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM). This system boasts over 70,000 codes, with constant additions, deletions, and revisions each year.

Battling burnout while optimizing RCM

Artificial intelligence (AI) offers a haven of hope, promising greater accuracy, efficiency, and relief for stressed billing and coding teams. By automating and streamlining workflows, AI reduces administrative burdens and minimizes errors concurrently.

One influential voice in support of AI is Steven Carpenter, a billing and coding instructor at the University of Texas at San Antonio. "AI streamlines workflows and improves outcomes by reducing delays and errors," Carpenter explains. "Coders no longer need to dig through the ICD-10-CM and records to find accurate, up-to-date codes for each diagnosis."

Beyond merely recommending codes, AI tools can scrutinize and verify claims, automate claim submissions, confirm insurance eligibility, and acquire prior authorizations from payers. This optimization of RCM benefits not only the healthcare provider but also the patient, who experiences smoother claim processing and increased transparency.

Reducing errors, avoiding burnout

Medical billing engages more than just assigning the right codes. Billing teams weigh in on addressing patient inquiries about insurance coverage and medical charges. Stanford Health Care recognized an opportunity to augment their billing staff's abilities, minimize time wastage and avert burnout.

"Healthcare workers have experienced intense focus on burnout among physicians," says Aditya Bhasin, Vice President of Software Design and Development at Stanford Health Care. "However, our billing reps also field a torrent of complex queries from patients daily. When our employees are exhausted, it impacts our service delivery."

Stanford Health Care piloted an AI tool that generates draft billing responses tailored to individual patient queries. The AI tool considers factors like insurance policies, and crafts precise responses that align with the organization's brand and voice. "We streamlined our day-to-day workflow by utilizing AI,” says Bhasin. “Reps experience a significant reduction in the time required to generate replies."

The staff reported feeling "super excited" about the AI tool during an internal survey, and as of March, the entire billing staff now uses it regularly. "Stanford Health Care has realized that AI offers a powerful tool in alleviating burnout and enabling staff to focus on higher-value activities," Carpenter asserts.

Revolutionizing healthcare with AI

AI's transformative potential in healthcare systems is unquestionable. "AI is revolutionizing revenue cycle management by reducing claim denials, enhancing the patient experience, and optimizing financial performance," Bhasin emphasizes.

However, the human touch remains vital in the AI-powered medical billing process. "AI is an ally, not a replacement for human insight and compassion," Carpenter adds. "AI tools augment human expertise and foster a more efficient, sustainable healthcare system."

Up Next: Revolutionize prior authorizations with artificial intelligence

  • AI Strategy
  • AI Use Cases
  • Patient-Centered Care
  • Provider Experience

Sources

  1. Improving Revenue Cycle Management with Artificial Intelligence [digital.smithsonianmag.com]
  2. AI Enhances the Healthcare Revenue Cycle [hcrevolution.com] 3. Artificial Intelligence in Healthcare: Opportunities & Challenges [mckinsey.com]
  3. AI in Hospital Revenue Cycle Management [beckerhospitalreview.com]
  4. Using AI to Minimize Burnout in Healthcare [healthcaredive.com]
  5. Artificial Intelligence (AI) not only recommends accurate, up-to-date codes for diagnoses but also verifies claims, automates submission, confirms insurance eligibility, and acquires prior authorizations from payers, thereby optimizing revenue cycle management (RCM) for healthcare providers and reducing errors.
  6. Stanford Health Care, recognizing the potential of AI to mitigate burnout among billing staff and improve service delivery, piloted an AI tool that generates draft billing responses tailored to individual patient queries, considering factors like insurance policies and aligning with the organization's brand and voice.
  7. In the AI-powered medical billing process, AI is an ally that augments human expertise and fosters a more efficient, sustainable healthcare system, while the human touch remains crucial in maintaining the compassionate care and patient-centered approach integral to the field.

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