How the healthcare workforce shortage affects revenue cycles

by Experian Health 6 min read December 6, 2023

How the healthcare workforce shortage affects revenue cycles-blog

The media has extensively covered the healthcare workforce shortage and its impact on patient care. It’s a chronic, dangerous problem that seems to worsen, despite the industry’s efforts to staff up. A recent Experian Health survey found severe and long-term implications for revenue cycle management and its impact on provider and patient care. 100% of revenue cycle leaders surveyed agree the pervasive healthcare workforce shortage impacts their facility’s ability to get paid.

The problem isn’t going away; most survey participants (69%) expect recruiting challenges to continue. Furthermore, nine of 10 survey participants admit to a double-digit turnover rate. However, the shortage of qualified labor is impacting healthcare in other areas beyond patient outcomes.

The report shows the bottom line is clear: The healthcare workforce shortage impedes the industry’s ability to get paid. How can providers solve this?

Experian Health’s survey, “Short Staffed for the Long-Term,” polled 200 revenue cycle executives to understand the impact of the hiring deficit’s impact on provider cash flow.

Survey Finding #1: Staffing shortages impede payer reimbursements and patient collections.

  • 32% of survey participants said patient collections is the revenue cycle channel most impacted by healthcare workforce shortage.
  • 22% said payer reimbursements are most affected by staff shortages.
  • 43% said both channels were equally impactful to the healthcare revenue cycle.

There was little disagreement in the survey around whether provider revenue cycle suffers from a lack of qualified staff. The debate centered on which reimbursement channel took the biggest hit.

Experian Health’s staffing survey revealed revenue cycle executives agree that collecting late patient payments is much more complicated now. The worker shortage impedes the ability to manage this process. In an era when many patients put off care due to high out-of-pocket costs, maximizing collections is more important than ever.

Short-staffed, overworked healthcare collections teams require the time and tools to optimize the collections process by identifying the accounts more likely to pay. Patient collections teams could also benefit from software that finds financial assistance that could ease self-pay burdens.

Collections Optimization Manager saves staff time by automatically determining the most suitable patient collections approach. The University of San Diego California Health (UCSDH) uses this software to segment patients by propensity to pay. It allows collections agents a more efficient, personalized approach to improve the revenue cycle and the patient relationship. From 2019 to 2021, UCSDH increased collections from $6 million to more than $21 million with this solution.

Patient Financial Clearance automates screening prior to service or at the point of-service to determine if patients qualify for financial assistance, Medicaid, or other assistance programs. Kootenai Health leverages the software, which increased the accuracy of determining patient financial assistance by 88%, and saved 60 hours of staff time through automation.

Together, these tools can ease the healthcare workforce shortage by optimizing and streamlining collections.

Survey Finding #2: The healthcare workforce shortage contributes to increasing denial rates.

  • 70% say escalating staff shortages increase claims denials.
  • 92% report new staff member errors are a significant factor in delayed or declined reimbursement.

Today, healthcare providers are seeing claim denials increase by 10 to 15% year over year. A lack of qualified revenue cycle staff costs billions annually in preventable revenue cycle errors. 35% of healthcare leaders admit losing more than $50 million yearly on denied claims. The complexities of the revenue cycle particularly challenge new staff; 92% of survey respondents say errors are common.

Denied claims ripple across the revenue cycle, tying up staff time and provider cash flow. Ultimately, it is patients and staff who suffer. When hospitals experience restricted cash flow, it can hamper their ability to effectively deliver the highest quality care. When staff stretch to their limit due to the healthcare workforce shortage, they may make more errors, burnout, or quit.

Automating the claims process is a necessity in this challenging environment. Tools like ClaimSource® and Claim Scrubber can catch errors before submission, reducing undercharges and denials.

Franklin Healthcare Associates, a 100-provider, four-location practice, used Claim Scrubber to reduce accounts receivable (A/R) by 13%. As claims volume grew, the practice decreases its full-time employee (FTE) requirements by leveraging this automated tool. It’s one clear example of how technology can stretch staff farther to improve the bottom line.

Survey Finding #3 Staffing deficits aren’t going away.

  • Close to 70% of respondents believe revenue cycle staffing levels will continue as a problem into the future.
  • Staff turnover is a contributing factor; 80% said their organization’s turnover revenue of cycle management staff is between 11-40%.

Experian Health’s survey confirms that healthcare teams struggle to find qualified staff. Staff turnover is a significant contributor to a revolving hiring door. One survey showed the average hospital turnover rate is 100% every five years. Traditional solutions to the problem include throwing more money into salaries, bonuses, or other perks. Overtime is a go-to remedy for the chronic healthcare worker shortage. But these approaches strain the provider bottom line. A recent Kauffman Hall survey shows:

  • 98% of healthcare providers have raised minimum wage or starting salaries.
  • 84% offer signing bonuses, and 73% offer retention bonuses.
  • 67% experienced wage increases of more than 10% for clinical staff.

The American Hospital Association (AHA) states, “Hospitals also have incurred significant costs in recruiting and retaining staff, which have included overtime pay, bonus pay and other incentives.” But what if recruiting isn’t the answer to the healthcare workforce shortage at all?

Artificial intelligence (AI) and automation software can help cut costs and lessen the workload of existing staff. The latest data suggest providers could save close to $25 billion annually (one-half of what they spend on administrative tasks) if they leveraged these tools.

Experian Health’s  AI Advantage™ uses powerful algorithms to automate manual claims processes to reduce denial and lessen the volume of tasks for revenue cycle staff. The software works in two critical areas:

  • Predictive Denials proactively cleans claims before they are submitted. The software flags claims at risk of denial, allowing manual intervention for a clean submission—with no denials.
  • Denial Triage manages denied claims by identifying the highest value reimbursements to maximize cash flow. Instead of chasing low-value claims or those least likely to pay, the software prioritizes where revenue cycle staff should spend their time for the greatest return.

Schneck Medical Center saw significant ROI from this software in just six months. AI Advantage helped the facility reduce denials by an average of 4.6% per month. Claims corrections that took up to 15 minutes in the past now take under five minutes.

Better software can do more than help hospitals get paid faster. Automating revenue cycle management processes frees up staff time. More time and less pressure mean fewer mistakes.

Automation can ease the impact of the healthcare workforce shortage

Two of the most pressing problems hospitals face today are the healthcare workforce shortage and revenue cycle impediments that keep them from getting paid. These challenges interconnect, and providers can solve them both with better technology to automate time-wasting manual functions.

AI and automation in healthcare can cut costs and reduce staff burnout. Deploying revenue cycle software to automate billing, claims management, and collections could save $200 billion to $360 billion in spending in this country. These numbers are real. But so are the numbers showing increasing claims denials, staff burnout, turnover, and difficulties recruiting in the healthcare field. Today, the answer for hospitals to get paid faster is to leverage modern technology to improve the revenue cycle.

Learn more about how Experian Health’s revenue cycle management solutions can help automate common processes, and download the new survey to see the latest healthcare staffing shortage stats.

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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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