Effects of healthcare staffing shortages and how to solve them

by Experian Health 7 min read January 8, 2024

Effects of healthcare staffing shortages and how to solve them

Today, U.S. healthcare providers struggle with three significant challenges affecting care delivery—each resulting from chronic healthcare workforce shortages. Ultimately, these challenges threaten the fiscal health of the country’s most critical care safety nets. Over 80% of the healthcare C-suite say the chronic staffing shortage creates significant risk for their organizations. The effects of healthcare staffing shortages are severe – Experian Health’s recent survey of revenue cycle leaders found these executives unanimously agreed that staffing shortages impact cash flow, patient engagement, and the work environment of their current staff.

Experian Health’s new survey, Short Staffed for the Long-Term, polled 200 revenue cycle employees to determine the effects of healthcare staffing shortages on patients, the workforce, and their facilities. What did these teams say about the healthcare workforce shortage and the state of care delivery? Find out by downloading the full report.

Healthcare providers experience a vicious cycle, and the effects of healthcare staffing shortages can be seen in many different areas. For example, it makes it harder for existing team members to register patients on the front end of the encounter. On the back end, revenue cycle staff face higher workloads and stress leading to preventable reimbursement claims errors and missed collections opportunities. Ultimately, that stress leads to staff turnover, exacerbating the healthcare workforce shortage. This article dives into three effects of healthcare staffing shortages and how providers can combat them.

Result 1: Short-staffed providers struggle with reimbursement and cash flow.

  • 70% of respondents who say staff shortages affect payer reimbursement also report escalating denial rates.
  • 83% report it’s harder to follow up on late payments or help patients struggling to pay their bills.

Costs are up, and cash flow is down. Claims denials are increasing by 15% annually. Reimbursement rates continue to decline even as denials rise and patient debt increases. These are the revenue cycle challenges healthcare providers face on top of the chronic healthcare staffing shortage. Healthcare organizations must look for new ways to improve reimbursements while engaging patients and staff to benefit everyone involved.

Experian Health’s Short Staffed for the Long-Term report noted two of the most significant revenue channels for healthcare providers, claims reimbursement and collections, are experiencing significant challenges.

Reimbursement denials tie up cash flow in an endless cat-and-mouse game of revenue collection. HealthLeaders termed 2023 as, “the year of reducing denials for revenue cycle.” Their statistics further reinforce Experian Health data correlating increasing denial rates with the healthcare staffing shortage.

Simultaneously, healthcare providers find it harder to collect from patients. High self-pay costs lead to lower patient collection rates. One study showed patient collections declining from 76% in 2020 to 55% in 2021. Providers desperately need a more patient-centered collections process that helps these customers understand their cost obligations and payment options. Integrating automated collections solutions can also help providers do more with less.

Healthcare stakeholders must collaborate to devise innovative solutions that prioritize workforce augmentation and streamline financial workflows. Technology can solve these problems by automating manual revenue cycle processes that lead to delayed reimbursements. New solutions that use artificial intelligence (AI) software can help in other areas (like claims denials) to save staff time and reduce workloads.

Result 2: A lack of staff directly impacts successful patient engagement.

  • Surveyed staff say 55% of patients experience engagement issues at scheduling and intake.
  • 40% say patient estimates suffer, leading to potential miscommunications in credit and collections.

Experian Health’s The State of Patient Access, 2023: The Digital Front Door reported patients and providers believe healthcare access is worsening. 87% of providers in the survey blamed the effects of healthcare staffing shortages. Earlier data from ECRI shows patients wait longer for care, and nearly 50% of providers say access is worse.

Over 100 academic studies in the past two decades confirm the correlation between poor patient health outcomes and industry staff shortages. Existing staff members may take on heavier workloads to cover gaps in patient care. The resulting fatigue can impact the quality of care delivery. When healthcare organizations are short-staffed, each team member may spend less time with patients, resulting in rushed assessments and potentially missed diagnoses.

Staff shortages can impact every phase of the patient journey, beginning with patient scheduling and potentially delayed essential medical services. On the backend, patients suffer when the pressure staff members feel to work faster causes preventable errors leading to healthcare claim denials. Collections suffer, as frustrations mount, and healthcare staff waste time on patients who are simply unable to pay.

The adverse effects of staffing shortages in healthcare weaken with technology to improve the patient experience at every stage of their encounter. Better technology lessens the burden of care for staff by automating mundane administrative tasks so every provider can focus on serving patients—not filling out forms.

Improving patient engagement starts at the beginning of the healthcare encounter. For example, patient scheduling software can create a seamless online experience that halves appointment booking time. More than 70% of patients say they prefer the control these self-scheduling portals offer, putting access to care back in their hands. Patient payment estimation software creates much-needed healthcare price transparency, improving satisfaction by eliminating financial surprises after treatment. These solutions, combined with automated revenue cycle management software, can streamline healthcare processes and improve patient experiences.

Result 3: Overwork is the norm as staff work environments decline and turnover increases.

  • 37% of survey respondents report issues with staff burnout.
  • 29% list the departure of experienced staff as one of their top challenges.

Whether in frontend care delivery or backend revenue cycle, overworked and stressed healthcare professionals are more susceptible to making mistakes, diminishing the overall quality of the patient experience. The attention to detail, a critical component in a complex, high-stakes business, may be compromised due to the strain on the existing staff.

When a healthcare organization is short-staffed, it increases the stress on the existing employees. In turn, this contributes to higher turnover rates. Job dissatisfaction and increased stress levels create a challenging work environment, perpetuating the cycle of staffing shortages. Recruiting and training new staff to fill these gaps further exacerbate the strain on existing teams.

One area that is critically impacted by staffing shortages is seen in claims management, as claim denials continue to increase, which cost American healthcare providers an estimated 2.5% of their gross revenues annually. Billions of reimbursement dollars logjam in the endless cycle of claims submissions, rejections, and manual mitigations. In 2022, the cost of denials management increased by 67%. Revenue cycle staff, stretched to their limits by staffing shortages, will likely continue to make preventable mistakes during patient intake and claims submission.

However, automating claims management with a solution like ClaimSource® can help lower denial rates and ease this burden.  This solution delivers increased operational efficiencies and effectiveness by prioritizing claims, payments and denials so that users can work the highest impact accounts first. Other solutions, like Claim Scrubber, can improve claim accuracy before submission, by submitting clean and accurate claims every time. These technologies enable healthcare providers to reduce claims denials while relieving some of the terrible pressure felt by their financial teams to work harder and faster. By automating clean claims submissions, healthcare organizations free up their teams to focus on taking better care of patients—and themselves.

Healthcare staffing shortages + manual revenue cycle = Unsustainability

What happens to a process that heavily relies on human labor—when there aren’t enough people to go around? In the case of the healthcare revenue cycle, it means staffing shortages heavily impact a hospital’s ability to collect revenue.

Medical Economics reports that 78% of providers still conduct patient collections with traditional paper statements or other manual processes. In an era of talent shortages, these manual processes bog down the entire organization with no relief in sight. Overwork leads to burnout, a significant problem in the industry that also contributes to staff turnover.

But this is exactly how digital technology can solve the healthcare staffing shortage. While AI and automation can’t help providers find the staff they need, it can eliminate manual tasks and reduce errors that lead to more work, staff burnout, and patient care disruption. McKinsey says automation can eliminate approximately half of the activities employees now perform. It could considerably improve the work environments for revenue cycle staff, allowing them to focus on high-value tasks, and engage patients in more caring and personalized experiences.

Experian Health offers providers proven technologies to increase revenue, improve patient care, and lessen the strain on existing staff, to combat the effects of healthcare staffing shortages. Contact Experian Health today to get started.

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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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