Machine Learning

Workforce Challenges and AI

The Semantic Auditor enables Health Information Management (HIM) and Revenue Cycle Management (RCM) professionals to address workforce challenges within the revenue cycle using AI, automation, and analytics.

COVID-19 has dramatically impacted healthcare workers around the world. Health systems are faced with the challenges of increased labor costs, employee burnout, and staffing shortages. Due to these challenges, 47% of healthcare workers in the US plan to leave their position by 2025. These pressing challenges have resulted in lower quality of care, job dissatisfaction, and professional mistakes in everyday work. As a result, the healthcare process is impacted due to inefficiencies in workforces. 

There are major opportunities to improve workforce challenges within health information management, which, today, is largely reliant on inefficient manual processes. 

This blog post will identify solutions to current workforce challenges that can be addressed by using AI, automation, and analytics, to ensure a healthier workforce and reduce the pressing challenges faced by healthcare professionals.

Workforce Pressures Rising

Within the revenue cycle, it is becoming harder and harder to find skilled coders & auditors. There are several factors impacting this process, including:

  • An aging demographic that is taking specialized knowledge with it;
  • Coding, as a task, has become more difficult with new standards and guidelines issued on a frequent basis; and
  • Digital transformation has increased the amount of documentation required to be reviewed

Beyond this, COVID-19 has brought about several accentuating factors that have accelerated this process.  A rise in remote-working placements has made in-person offices difficult to maintain and this has carried through in thereat resignation, which has made retention of great staff more difficult.

Advancements in Technology

Next-generation automation advancements have led to breakthroughs in Artificial Intelligence (AI) technology. Machine learning (ML) and Natural Language Processing (NLP), in particular, can enhance computer capabilities and ease workforce burdens. 

These advancements in technology within the healthcare industry can drive impact in everyday tasks involving coding and auditing teams. AI-powered auditing software, in particular, can help reduce workforce challenges by addressing shortages, burnout, and the heavy workload faced by HIM and RCM staff. 

Using AI to address Workforce Challenges

HIM and RCM teams frequently are caught up with administrative tasks that can reduce their focus on high-impact clinical documentation improvement or revenue integrity work. The implementation of an AI-powered auditing software can reduce the workload burden of low-value work that is time-consuming for HIM and RCM teams. 

As a first pass, AI-powered auditing can review coded and claims data to ensure coding accuracy and revenue integrity. From there, only high-value opportunities can be flagged for review by HIM and RCM teams. By delegating initial secondary reviews to AI, HIM and RCM professionals can focus on the most high-value work and get ahead of deadlines.  Beyond the revenue cycle, AI-powered auditing can also be used to enable specific use cases to create efficiencies and ​​interpret information based on specific data types. 

Automation is able to empower healthcare facilities to minimize human input, intervene in current processes, and allow for simpler completion of tasks. Moreover, automation and AI can help reduce burnout among healthcare workers as there is a push towards improving systems, software, and digital processes using automation. Financial tasks within leading health systems can be automated to perform tasks such as claims processing and prior authorization. As well, on the information management side, data entry and data analysis can be automated to empower staff to easily perform tasks effectively. HIM and RCM teams are then able to save time and drive efficiencies to complete work faster and to a high degree of completeness. 

New Tools and Analytics 

The use of analytics can establish workplace transformation that HIM and RCM workers can use to enforce decision-making processes. Analytics can be captured using high-quality data within healthcare systems to enable managers to make important decisions relating to training opportunities, measures of productivity, and hiring decision-making.  AI can be used to derive meaningful analytics by sourcing through various data sets to create high-quality data that health professionals can use to capture real-time operational visibility and address heavy workloads. As well, analytics can provide insight into any detected errors in coding and auditing using AI-auditing software to target errors and ease the workload burden for HIM and RCM professionals. 

Semantic Auditor is the Best Software to Address HIM and RCM Workforce Challenges

Semantic Auditor uses proprietary machine learning models, tuned to your unique patient population to complete secondary reviews and prioritization of all coded and claims data with reference to source clinical data. 

Providers are now able to streamline pre-bill coding and revenue integrity audits to reduce coding errors, limit denials, and optimize reimbursements. In turn, RCM and HIM professionals have greater operational visibility due to AI and automation capabilities taking a significant burden from their shoulders. 

Semantic Health’s technology is able to address the workforce challenges of workplace shortages, employee burnout, and heavy workload to create optimized and efficient coding and auditing processes in hospitals. Using AI, automation, and new tools and analytics, auditing software is able to streamline the current auditing process and produce better data quality to improve operational visibility and unlock future opportunities for workforce transformation.

About Semantic Health

Semantic Health helps hospitals and health systems unlock the true value of their unstructured clinical data. Our intelligent medical coding and auditing platform uses artificial intelligence and deep learning to streamline medical coding & auditing concurrent with patient admission, improve documentation quality, optimize reimbursements, and enable real-time access to coded data for secondary analysis.

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