Providers Can Reduce Administrative Burden and Improve Productivity With AI Tools to Mitigate Labor Shortages

By Noel Felipe, Senior Vice President, Revenue Cycle Practice Leader, Firstsource 

Labor shortages continue to be one of health care’s main storylines. Projections from the National Center for Health Workforce Analysis show shortages in a wide range of clinical positions, from anesthesiology to primary care clinicians to registered nurses from now until 2036. Mercer, a large human resources consultancy, projects a shortage of more than 100 000 health care workers by 2028, on top of increasing competition for talent in lower-wage positions. As demand for care grows alongside an aging US population, providers will likely face the challenge of delivering high quality outcomes with fewer human resources, even as they must excel under value-based care contracts.

An understaffed department is generally a recipe for dissatisfaction and reduced retention. With the growing use of artificial intelligence (AI) tools, however, providers can help clinical and administrative employees work more efficiently. Intelligent automation, analytics and machine learning and generative AI tools can greatly streamline burdensome administrative tasks across the organization. Some of these tools are being built into popular business software. Others are being purpose-built for health care settings. The tools can reduce the time spent on rote, repetitive work, email management, phone calls, data entry, note-taking, research and more. AI becomes a provider’s workforce multiplier, returning valuable time to employees so they can be more productive. In turn that can help mitigate the need to tap expensive labor pools.

Here's a quick look at some key places where providers can deploy AI tools today. 

• Patient registration. AI-enhanced registration tools can make it easier for patients to register digitally, with menu selections tailored in real time based on patient responses. AI tools can also help patients analyze the payment option most appropriate for them so that providers can set up payment arrangements during registration. That can help reduce resources required later for payment collection.
• Revenue cycle management.  Providers can intelligently automate much of their revenue cycle with AI tools, from claims preparation and submission to following up on claims status and generating appeals. Analytics tools can uncover root causes of payer denials so staff can make corrections and avoid future issues. That pattern analysis can also reveal payer errors, making appeals more successful. 
• Clinical notes. Ambient AI scribe tools can transcribe, then summarize conversations between physicians and patients for entry into medical records. Generative AI can also review existing records and prepare summaries for quick review by physicians.
• Preauthorization. AI can speed up preauthorization workflows. Generative AI tools can assist in completing preauthorization requests by scanning a patient’s medical record for a payer’s required data and attached required supporting documentation. AI tools also can make multiple calls at one time to follow up with payers on the status of preauthorization requests. 
• Proactive interventions. AI tools can review patients’ records, flag potential emerging issues and include the health system’s evidence-based treatment guidelines, all for review by the clinician. For example, analytics could uncover a member’s gradual weight gain and increasing A1C scores and alert a primary care physician to the patient’s growing risk for Type 2 diabetes even before the physician has reviewed the record. 
• Diagnostic assistance. The US Food and Drug Administration (FDA) has published a list of 950 AI and machine learning enabled medical devices it has authorized. Many of these assist diagnoses, especially with medical images. AI and machine learning algorithms are excellent at finding patterns in large data sets and can be trained to look for malignancies and abnormalities, literally acting as additional sets of eyes. 
• Care coordination. AI, machine learning and automation tools can help make referral appointments, arrange non-traditional services such as food delivery and transportation and follow up with patients by phone, text or chat. 
• Streamlining recordkeeping and administrative tasks. Generative AI can assist nurses, physicians and other clinicians in data gathering. Tools can be trained to extract specific information for regulatory and quality reporting and auto-populate fields. Software bots can be trained to fill out forms, while generative AI assistants can read, route and respond to emails so clinicians can focus on patient needs. 
• Enhanced patient engagement. Gen-AI tools can produce educational materials personalized to an individual patient’s specific situation. Instead of creating or assembling these materials, clinicians can spend more time helping patients understand their conditions. 

These activities represent just the start of how AI and related tools can reduce administrative burdens in provider settings. As generative AI trains on health care-specific language models and data sets, its capabilities will grow. As AI becomes as ubiquitous a business tool as spreadsheets and search engines, providers without AI tools will find it more difficult to attract and retain talent at all levels of their organization. Providers investing in AI will be equipping their clinicians and business professionals for optimal performance and job satisfaction while helping to insulate their organizations from talent shortages.