How a Human-Centered Approach Builds the New HI Workforce

It’s no secret that artificial intelligence (AI) is developing at a rapid rate, evolving the future of efficient and effective workflows before our eyes. This evolution is not unique to healthcare, health information (HI), or the United States. It is happening worldwide.  

In this new paradigm, AI presents a variety of opportunities offering benefits for hospitals and health systems. But only if the healthcare workforce is prepared to meet these changes. 

The latest AHIMA workforce study revealed that 52 percent of respondents reported their organization plans to increase the use of AI and machine learning (ML) tools over the next 12 months. Additionally, 75 percent stated that upskilling the current HI workforce is necessary for the profession to succeed as the use of AI and ML increases.  

Investing in the skills and futures of HI professionals is essential for health systems to make the most of this changing technology landscape.  

An Organization-wide Culture of Learning Is the First Step 

A culture of innovation and learning is the first step to prepare the HI workforce for AI adoption. The commitment to growth pushes beyond human resources. It reaches into every corner of the organization and must be fully supported by senior leadership. Without a widespread culture shift that recognizes the value of innovation, healthcare organizations risk remaining stagnant amid technological advancements.  

Throughout the journey, there are two important terms to know: upskilling and career pathing. The initiatives are related, complementary, and collectively support an organization’s move to become a skills-based organization.  

Upskilling 

According to LinkedIn Learning, upskilling denotes an employee undertaking learning to expand their skill set. The additional skills gained will enhance the worker’s performance in their current role and potentially advance them along their career path.  

Career pathing 

Gartner defines career pathing as the process of aligning opportunities for employee career growth with the organization’s talent priorities. This process includes mapping careers based on vertical, lateral, and cross-functional roles. The most important aspect of career pathing is creating an inventory of every employee’s skills, interests, and career objectives.  

While the process can be overwhelming, start by infusing a commitment to learning throughout the organization, invest in career growth, and prioritize employee input. Embracing technology is a fundamental value in creating a learning organization. One of the best ways to engage teams in a learning process is to conduct a skills inventory.  

Build Your Team’s Skills Inventory

Since the skills needed tomorrow are much different from those of today, HI professionals need to be versed in data language, analytics, interpretation, and research like never before. One proven way to assess the current state and build careers for the future is through a skills inventory.  

This process can start small and build over time. For example, organizations should begin by identifying top roles or key positions for skills identification.  

Specifically for HI professionals, the following skills should be considered:  

• Perform clinical analytics predictive modeling 
• Conduct health record auditing and compliance reviews 
• Be proficient at coding classification systems (i.e., ICD-10)  
• Know CPT coding guidelines  
• Manage projects  
• Direct health information management 
• Carry out health policy research  

Each skill includes a definition and several proficiency levels. Employees review all possible skills and self-identify their capabilities. Some organizations use platforms such as Workday for employees to review skills, note their interests, and receive automatic notification of new openings and opportunities that align with their skills. 

Once the skills inventory process begins, Leadership should collectively look ahead to the needs of the future: 

• Imagine and define new careers that will emerge. 
• Predict core skills needed to support these new careers.  
• Compare future requirements to present-day skills inventory. 
• Identify gaps and implement internal learning platforms to help employees upskill and set new career paths. 

It is crucial for organizations to allocate time for employees to step away from their daily tasks and engage in these processes. Additionally, involving human resource (HR) professionals is key, as they are vital advocates for HI teams in the development of a skills-based organization. .  

Maintain Close Alignment with Your HR Team 

It is important to align closely with HR peers throughout the process. Maintain close alignment with these professionals to ensure full understanding of HI’s operational goals and the evolution of care delivery. This includes the evolving tools, workflows, and skills needed to deliver the work.  

Skills, role designs, and learning investments are mutually beneficial to the employee and the organization to support balance and growth. Without proper road mapping and alignment between HI and HR, it is easy to lose sight of upskilling’s value. Various and differing skill clusters are needed to operate different HI processes. This is especially true as the care delivery model changes through telehealth and virtual care. Emerging challenges across the healthcare organization can also impact the learning experience and investment for HI.  

Clinical Coding Teams Are First Focus for Upskilling in HI 

Internal coding teams are optimal candidates for upskilling and career pathing efforts, since they are already affected by technology change. This includes the use of AI, ML, and robotic process automation (RPA) in advanced medical record encoders and automated coding systems.  

For example, begin by analyzing complex data and systems to find patterns in billing and claims denial data that can be used to highlight areas of opportunity for improved coding workflows. By analyzing these patterns, coders can use this data to identify areas where rework is occurring in the revenue cycle process. Denial data also represents an area where there may be discrepancies in clinical documentation and coded data used for billing.  

Using data to target areas of greatest opportunity is an effective way to improve processes and achieve a return on investment through reduced denials.    

As the technology advances, simple coding patterns should be identified to align clinical documentation with coding of the clinical record. In advanced technology states, coder expertise shifts to validation of AI suggestions and focused work on complex cases where the system requires human intervention and expertise. The coding workflows are used to verify the recommendations using tools to check sources, edits, and references based on patterns of complexity in the data.   

While AI and ML streamline or eliminate some mundane coding tasks, these tools are not replacements for analysis and critical thinking skills offered by clinical coding professionals. AI is an assistant and a guide to the human worker. It relies heavily on large quantities of solid, clean data foundation coupled with HI professionals to train the models.  

A strong partnership between human coders and technology improves the system over time, bringing all information forward in a seamless end-user experience. Consider the history of medical record encoders to predict AI’s impact on the profession’s future state.  

Four Phases of Medical Record Encoder Evolution 

Past: Coders used coding books as their primary source. 

Last Two Decades: Encoder technology has developed significantly, integrating coding books, guidelines, and regulations directly into the software. This allows coders to search for terms and easily access the relevant sections of digital coding manuals, which include comprehensive coding source information. Additionally, the system consistently updates and references this source data..  

Today: Rules-based technology, including ML and RPA, enables coders to create and edit rules for the encoder to use. Global procedures are a good example of how encoders today use rules to guide coders to the correct code. Encoder technology is also integrated into the workflow of other systems, including electronic health records and clinical documentation integrity platforms, to reduce clicks and mitigate logging in and out of multiple systems.  

Future: In the next five to 10 years, AI will provide code recommendations to the coder as described above.  

Upskilling the Coder Workforce Is Necessary for the Future of Healthcare 

Investing in workforce training and education is crucial in healthcare, particularly due to rapidly evolving technology in clinical coding. To achieve success, the following strategies are recommended: 

1. Build a culture of learning: Establish a culture that values continuous learning and innovation. Encourage every department and employee to embrace personal and collective growth. 

2. Engage employees in your strategy: Coders’ expertise is essential for training AI systems to ensure accuracy. Involving them in the data process enhances system reliability and encourages acceptance of AI in daily workflows. 

3. Prioritize employee development with ROI in mind: Start with small, cost-effective initiatives, like conferences and online training, to promote career growth and skill advancement, aligning with organizational goals. 

By upskilling coders, health systems can effectively grow with emerging technologies, like AI, ML, and RPA, using their workforce as a key asset in adapting to technological advances. 

Amy Larsson, MBA, BSN, is vice president of TruBridge Encoder, a division of CPSI, where she is responsible for strategic growth, product management, and operations. Amy’s experience spans healthcare technology business operations, payment integrity, clinical coding, and product management with a diverse clinical background across large healthcare organizations,  

Lindsey Hall, BBA, AAHRD, is a people partner with CPSI where she serves as the human resources (HR) lead for multiple service lines including the TruBridge Encoder division. Lindsey has a diverse background in HR with specific skills in workforce development, employee engagement, and change management.