Causes of healthcare staffing shortages and how technology can help

by Experian Health 6 min read March 12, 2024

Causes-of-healthcare-staffing-shortages-and-how-automation-can-help-blog

There is growing concern that the healthcare industry needs more clinical and administrative staff to handle care demands. The crisis affects patients beyond treatment delays or lower care quality. Staff shortages in the revenue cycle create problems with patient engagement, billing, and collections. A recent Experian Health survey reveals unanimous concerns among providers about the challenges posed by workforce shortages. But what are the root causes of staffing shortages in healthcare? Is there a remedy for healthcare organizations struggling to find the talent they need? This article dives into the survey findings and the ways healthcare providers can address staffing shortages effectively.

Finding 1: Staff turnover is a significant cause of healthcare staffing shortages.

  • 80% of providers report turnover between 11-40%.
  • Nearly one in 10 say turnover is between 41-60%.

The causes of staff shortages were evident before COVID. A rapidly aging Baby Boomer population and limited availability of training in areas such as nursing led to predictions that looming staff shortages were on the horizon. The pandemic exacerbated the situation, leading to a mass exodus of workers and The Great Resignation. Some reports show healthcare lost 20% of its workforce, including 30% of nurses.

Today, the average hospital turns over one-quarter of its staff annually, an increase of more than 6% from the prior year.As a result, the State of Patient Access 2023 reported nearly 50% of providers say access to care is worsening.

Simultaneously, healthcare is bogged down with administrative tasks. Increasing evidence shows providers must turn to automation software to decrease human workloads and stretch small teams further.

These automated tools can:

Automation can improve the work-life balance of healthcare staff, potentially closing the revolving turnover door, one of the most significant causes of staff shortages. For example, IU Health implemented automated guided scheduling, which helped scale their operations, reduce scheduling errors and improve staff efficiency.

Finding 2: Finding and hiring staff is an undue burden for healthcare providers.

  • 73% of respondents said finding qualified staff is difficult.
  • 61% reported that meeting entry-level staff’s salary expectations is a challenge.

Healthcare organizations feel the staffing crisis at every level.A recent Medical Group Management Association (MGMA) poll cited the difficulties in hiring revenue cycle staff:

  • 34% of respondents stated hiring medical coders is their biggest challenge.
  • 26% stated billers were difficult to find.
  • One-third said finding schedulers and prior authorization staff is hard.
  • Other hiring challenges included revenue cycle management (RCM) managers.

When and if healthcare providers find staff, bringing them into the fold is costly.Experian Health’s staffing survey showed most organizations struggle to meet the salary expectations of even the least experienced members of their teams.

The causes of staff shortages can be remedied by leveraging new artificial intelligence (AI)-powered tools. Tools like AI Advantage™ can automate and transform claim denials management, a problem costing healthcare providers around $250 billion annually.

Experian Health’s State of Claims 2022 survey showed the most common causes of denied claims include:

  • Missing or incomplete prior authorizations.
  • Failure to verify provider eligibility.
  • Inaccurate medical coding.

AI Advantage reduces denial rates by scrubbing claims and flagging errors before submission. After claim submission, the software prioritizes the most high-value denials for correction to maximize revenue generation. Organizations like Schneck Medical Center use these tools to reduce denials by 4.6% each month. The facility also increased the speed of claims submissions. Tasks that used to take 12 to 15 minutes to rework now process in less than five minutes, lessening the need for hiring more staff and improving the workloads of their existing team.

Finding 3: Burnout is a top contributor to staffing shortages.

  • 53% of poll respondents said staff burnout is a key cause of the current staff shortage.
  • 48% said the new expectation for schedule flexibility and hybrid work models also contributes to the healthcare workforce shortage.

Burnout is one of the most significant causes of staff shortages impeding high quality care and wreaking havoc on the revenue cycle. The latest data shows the percentages of clinical and administrative burnout in healthcare is approaching or exceeding 50% in most job categories:

  • 56% of nurses report burnout symptoms.
  • 54% of clinical staff.
  • 47% of doctors.
  • 46% of non-clinical staff.

Cost-cutting and increasing care demands have led to increasing fatigue in healthcare staff. But technology exists to automate back office functions that could free up staff time. For example, organizations like Kootenai Health saved close to 60 hours of staff time in over 8 weeks by automating the presumptive charity process Patient Financial Clearance. Stanford Health used Collections Optimization Manager to cut 672 hours each month from overburdened back office staff.

The COVID pandemic also changed expectations about how and where Americans should work. Remote work became normal; three years post-COVID, 58% of the American workforce report working remotely at least one day a week. The same data also shows that when workers have the chance to work virtually, 87% take it.

Healthcare is not immune to the desire for more schedule flexibility. Becker’s Hospital Review states, “Many workers desire the ability to work remotely, even if they only get the option a few days a week. Flexibility allows people to maintain work-life balance—and in a high-burnout field like healthcare, balance can be crucial.”

Surveys show 31% of healthcare roles are remote full-time while 14% offer this flexibility part-time. The problem is that many healthcare positions cannot allow this flexibility—and the industry competes with others that do. To remain competitive, healthcare organizations must embrace technology to offer work flexibility.

Cloud-based digital technology is beneficial in areas like the revenue cycle. For example, automated technology from Experian Health can:

  • Use advanced analytics to streamline workflows.
  • Facilitate patient self-service.
  • Minimize staff time spent on manual tasks.

AI-powered automation tools can lessen staff burnout by allowing them to work smarter. These tools provide the workforce with the scheduling flexibility they desire.

Eliminate the causes of healthcare staffing shortages with better technology

AI and automation technology in healthcare can lessen worker fatigue, lighten workloads, and give administrative workers the schedule flexibility they demand. Experian Health offers healthcare providers better technology to improve the lives of their staff, increase patient satisfaction, and generate more revenue.

Download the survey or connect with an Experian Health expert today to learn how we can help your organization tackle the causes of healthcare staffing shortages effectively.

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Key takeaways: Revenue cycle teams can use automation to reduce repetitive work and apply AI where data-driven prediction, matching or prioritization can improve a workflow. Experian Health’s 2025 State of Claims survey found that 41% of providers now face denial rates of 10% or higher, while 68% say submitting clean claims is more challenging than a year ago. Patient Access Curator™ (PAC) uses AI to support front-end data validation and insurance discovery, while AI Advantage™ helps teams predict denial risk and prioritize denial follow-up. Artificial intelligence (AI) and automation can support administrative work in healthcare. In the revenue cycle, teams depend on accurate information, timely decisions and efficient follow-up to keep claims moving. In revenue cycle management, AI and automation can help organizations reduce manual checks, find data gaps, predict denial risk and prioritize work queues. These tools are most useful when they support staff judgment, payer expertise and compliance oversight. They can handle repetitive, data-heavy tasks so staff can focus on exceptions and decisions that need human review. In 2023, McKinsey & Company reported that research suggests effectively deploying automation and analytics could eliminate $200 billion to $360 billion of spending in U.S. healthcare. For revenue cycle leaders, the practical question is where to apply those capabilities first. The case for applying AI and automation in healthcare Revenue cycle teams juggle many daily tasks. Staff collect and verify patient information, confirm eligibility, identify the right payer, submit clean claims, monitor status, work denials and manage collections. Small data gaps at the beginning of the process can create downstream rework and delays. Rework also consumes staff time, adding to these operational pressures. As costs rise and revenue cycles tighten, there is increasing pressure to do more with less. Experian Health’s 2025 State of Claims survey found that 54% of providers say claim errors are increasing and 90% of claim denials are reworked with at least some human review before resubmission. Providers are also managing broader financial and administrative pressures. The American Hospital Association has reported that prior authorization requirements, claim audits, denials and other payer policies add administrative burden and cost for hospitals and health systems. These requirements also consume staff time to appeal denials and manage payer processes. AI and automation are different but complementary. Automation follows defined rules to complete repeatable work. AI models can identify patterns in data, predict risk and help teams decide where to focus attention. When used together, they can support more consistent revenue cycle workflows. How AI and automation can support revenue cycle workflows Revenue cycle management automation and AI are most useful when tied to a specific workflow and a measurable operational problem. The goal is to help teams act earlier, reduce avoidable rework and focus staff time where judgment is needed most. For example, automation can complete rule-based eligibility checks. AI can help identify claims with a higher likelihood of denial. In insurance discovery workflows, AI can also help identify coverage that wasn’t captured at registration. When these tools fit into existing workflows, they can support more consistent decisions and reduce manual work. Three practical applications include: 1. Improving front-end data quality with Patient Access Curator Patient and coverage information collected early in the revenue cycle can affect downstream claim outcomes. Incomplete or outdated demographic details, eligibility responses, coordination of benefits or Medicare Beneficiary Identifier information can create problems that lead to claim delays or denials later in the cycle. Experian Health’s Patient Access Curator helps prevent claim denials by validating demographics, eligibility, insurance discovery, coordination of benefits and Medicare Beneficiary Identifier data in seconds. PAC’s AI and machine learning capabilities help improve match accuracy, coverage sequencing and data confidence by writing the validated data back into the host system and sequencing payers before the claim is created. This automates work that would otherwise require manual coverage checks. 2. Using insurance discovery to find coverage not captured at registration When active coverage isn’t identified during registration, claims may be delayed or submitted with incomplete insurance information. Insurance discovery looks for coverage that may not have been captured during registration. Patient Access Curator includes insurance discovery as part of its front-end validation workflow. It can help identify and correct missing or incorrect insurance information so claims can be submitted with more complete coverage data. 3. Using AI to prevent and prioritize denials Even with strong front-end processes, some claims still require additional attention. AI can help claims teams decide which claims to review before submission and which denials to work first after payer response. Experian Health’s AI Advantage supports two denial management use cases:1. AI Advantage – Predictive Denials uses a client’s historical claims data and Experian’s knowledge of payer rules to identify claims with a high likelihood of denial before submission so teams can take corrective action.2. AI Advantage – Denial Triage uses AI to segment denials and identify those with the highest potential for reimbursement. This approach can help teams prioritize with more confidence. Rather than treating every claim or denial the same way, teams can use predictive models to focus on the work that needs the most attention. Potential benefits of AI and automation in the revenue cycle A high-performing revenue cycle depends on timely, accurate and consistent work. AI and automation can help providers modernize that work without losing the expertise of the people who manage complex payer and patient situations every day. When applied to the right workflows, these tools can help organizations: Reduce manual data searches that take staff away from higher-value work Improve front-end data quality before claims are created Identify missing or incorrect coverage information earlier Spot claims that may be at higher risk of denial Prioritize denied claims by potential reimbursement Reduce rework caused by inaccurate or incomplete information Give staff more consistent information for follow-up decisions A focused AI strategy starts with the workflow problem, uses data that is relevant to that problem and keeps staff in control of judgment-based decisions. A more proactive approach to revenue cycle management Revenue cycle teams can move from reactive work toward a more proactive approach: catch errors earlier, validate coverage before claims are created and prioritize the claims and denials that need the most attention. Experian Health offers revenue cycle solutions that use AI and automation in targeted ways to support front-end data quality, reduce rework and manage denials. Patient Access Curator supports registration and coverage validation, while AI Advantage supports denial prediction and triage. Learn more about Experian Health’s Patient Access Curator and AI Advantage.

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