Navigating Financial Risk in Healthcare

Abstract

The COVID-19 pandemic exposed significant weaknesses in U.S. healthcare financial planning, including unpreparedness for patient surges, lost revenue from canceled procedures, rising supply costs, and staffing shortages. These conditions compounded financial risks and destabilized fiscal models used for forecasting, budgeting, and resource allocation. In 2020, U.S. hospitals lost an estimated $323 billion, with nearly half operating at negative margins (American Hospital Association, 2021). Financial shortfalls limited investments in capital, services, and expansion, directly affecting patient care. This paper examines how COVID-19 revealed systemic vulnerabilities, focusing on the dual risks of delayed access to timely, quality care and the diminished financial and operational capacity of hospitals to meet current and future care demands.

Context: Organizational and Stakeholders

To understand how the COVID-19 pandemic added financial risk to health systems, it is important to put the event into context. In December 2019, the first case of COVID-19 was identified, and in March 2020, the World Health Organization officially declared it a global pandemic (Centers for Disease Control and Prevention, n.d.). For the next 36 months, the pandemic was a disruptive and costly moment for the U.S. health system.

Hospitals saw a dramatic spike in cases caused by the coronavirus. Due to capacity issues, it is estimated that the cancellation of elective procedures caused losses of approximately $4 to $5.4 billion in net revenue per month for U.S. hospitals (Best et al., 2020). The high cost of treating COVID-19 put financial stress on hospitals, while the loss of elective care reduced revenue streams that facilities rely on to stay solvent.

These pressures revealed the intertwined nature of care delivery and financial solvency. Rural hospitals were especially impacted, with many closing or reducing services from the sustained revenue loss. Before the pandemic, underserved populations and health equity were already at risk due to negative operating margins. Between 2010 and 2019, 116 rural hospitals in the U.S. had closed (Bhatnagar et al., 2022).

Stakeholder Impact

During the pandemic, patients, providers, hospital administrators, insurers, government agencies, and other stakeholders were impacted by economic and care uncertainty. Hospital administrators managed volatile budgets, identifying emergency cost-saving opportunities, and seeking available state and Federal relief, such as the CARES Act, which offered $70 billion of relief to hospitals (American Hospital Association, 2020). And, managed supply chain disruptions on drugs and materials, which led to shortages and soaring costs. It is estimated that the demand for PPE (personal protective equipment) created a backlog of 4-6 months (Xu et al., 2020, para. 23).

The healthcare workforce faced an unprecedented increase in patient deaths, had to manage the unknown extent of transmission, and rely on untested treatment options. Those on the front lines experienced overwork and burnout, leading to staffing shortages, increased costs, and a reduction in care capacity (Burrows et al., 2023, paras. 1, 9, 10).

Insurers managed destabilized risk pools and payer mix due to job losses, shifting nearly 5.6 million people into the ranks of uninsured or to public coverage (Centers for Disease Control and Prevention, 2023, para 3). And, although they saw a short-term increase in underwriting income, by 2021, profit was eroded by an increased backlog of delayed procedures, leading to a loss for many insurers (Shrivasta, 2022, para. 20).

Economic Analysis of the Risk

The pandemic introduced profound fiscal uncertainty into the structure of the U.S. healthcare system. Income streams were unpredictable, labor and supply costs skyrocketed, and fixed operating expenses became a burden due to slowing cash flow. These shifts impacted financial models and exposed healthcare services beyond risk thresholds. 

Hospital Revenue and Financial Stability

Hospitals and local health systems rely on revenue generated from planned procedures for financial stability. During the pandemic, most of these were canceled due to spikes in pandemic care. It is estimated that U.S. hospitals lost $1.53 billion just from delayed pediatric procedures (American College of Surgeons, 2021, para. 3). 

In addition, by the end of 2021, expenses for supplies were nearly 16% higher compared to one year earlier (American Hospital Association, 2022, para. 3). These factors contributed to already strained hospital budgets. Based on 2018 data, many U.S. hospitals had a -4.4% operating margin with only 7.6 days cash on hand (Khullar et al., 2020, para. 3).

Patient Access and Outcomes

Since planned treatment during the pandemic was delayed, patients were not able to receive preventive care services.  The ability to obtain early treatment is critical to both patient and health system budgets. Timely treatment accounts for 89% of preventable hospitalizations and keeps costs in check. Studies show that residents in rural communities were especially impacted, accounting for a “32% of mortality differences between urban and rural residents” (Stansberry et al., 2023, Section 3.2). The challenge of demand forecasting is exponential when expensive long-term care becomes unpredictable.

System Readiness and Investment

Readiness is the hallmark of hospitals; they operate 24/7 and need to continuously offer a high level of treatment. Due to the increase in expensive treatment requirements, health systems faced delays or cancellation of investment in capital projects, technology, emergency preparedness, and staffing. Without funding to provide viable care options, long-term financial risk is introduced into the system. Since the pandemic, employment in U.S. hospitals is down approximately 100,000, and labor expenses have skyrocketed by 19.1% (American Hospital Association, 2022, para .4). 

Insurance Market

The pandemic exposed the risk caused by misaligned payment systems, care utilization, and imbalanced risk pools. Risk pools, the combination of high and low risk populations, were especially impacted. Temporary drops in claims volume and spikes related to COVID distorted actuarial assumptions. Pricing pressure was introduced by higher reinsurance and stop-loss rates, reducing the financial flexibility of insurers and increasing member premiums. Financial strain on local governments and private entities led to delayed payments, non-renewals, and reduced coverage (Gergen, 2020). 

Application of Risk Management Tools

To mitigate the impact of the financial risk posed by post-pandemic instability in U.S. healthcare systems, there are established economic tools that can inform long-term planning. The risk of inadequate funding and difficult-to-predict care burdens influences long-term planning.  When applied to real-world events like the pandemic, these models help healthcare leadership more accurately allocate resources and design resilient systems. There are three primary areas where models can minimize risk: Quantitative, strategic, and behavioral.

Quantitative Risk Assessment Tools

Quantitative models are statistical tools that analyze numerical data to simulate real-world scenarios. They can help predict outcomes such as patient volume, costs, and risk exposure. These include:

Expected Value and Standard Deviation

During the initial 17 months of the pandemic, the average cost per-patient hospitalization was $24,826, substantially higher than pre-pandemic costs (Gergen, 2020, paras. 2 and 28). The expected value principle can measure risk to help insurers correctly plan for fluctuations due to high-cost acuity patient populations (Hardy, 2006, pp. 2-3). 

Sensitivity Analysis

This approach can indicate how much the outcome of a predictive model can change if variables used for the model are not as expected (Thabane et al., 2013). In the case of the pandemic, sensitivity analysis can be used to identify which variables, such as early intervention, infection rates, and available resources, can minimize costly outcomes (Malik et al., 2022). 

Actuarial Forecasting Tools

Actuaries adapted post-COVID models to more accurately predict hospital volume by incorporating new risk variables such as vaccines and the effects of long-term COVID. They also recalibrate, stressing the limits of historical data by using scenario-based trends and working closely with epidemiologists to interpret medical data (Eaton, 2020). 

Strategic Planning and Risk Mitigation Models

Strategic planning to mitigate risk is an approach that health systems can use to align resources, investment, and care outcomes with long-term goals. These include risk pooling, insurance frameworks, and scenario planning.

Risk Pooling and Insurance

Risk pooling can help insurers limit fiscal exposure to avoid insolvency if another pandemic were to occur. By analyzing patterns during COVID-19, private insurance companies can partner with Federal entities to place limits on exposure, reconsider virus exclusions, and better define Federal backstops (U.S. Government Accountability Office, 2023).

Insurance Frameworks

Aligning payment models with risk helps insurers remain stable through shifts in the number of patients requiring care, timing, and type of care. By using pandemic data, insurers can adjust premium structures, expand reinsurance programs, and better coordinate private and public organizations to reduce volatility (Wharton University of Pennsylvania, 2021).

Scenario Planning

The COVID-19 pandemic introduced dramatic variables into the healthcare system and insurance market that were not adequately planned for. By integrating what was learned from spikes in patient care, supply shortages, and impact on the workforce, there is a higher likelihood of mitigating the effects of future events. This includes a deep analysis of the implications for people, care processes, and locations where care was provided (Rawson & Stevens, 2023, paras. 18-21).

Behavioral Concepts

Patient and population behavior can inform how incentives, market dynamics, and information can influence how decisions are made. These include moral hazard, adverse selection, and other factors that contribute to financial risk.

Moral Hazard

Moral hazard occurs when hospitals prioritize higher-margin services over the needs of the greater population. This can be financially stabilizing in the short term, but it can increase system-wide costs and impact patients' receiving quality outcomes. By analyzing moral hazard to reduce financial risk in health systems, the Federal government can evolve policies to reduce risk by linking financial support to compliance with public health behaviors. Insurance companies can structure incentives based on behavior in the face of social protection goals, and can provide incentives for companies to promote rapid testing and vaccination (Robertson et al., 2020).

Adverse Selection

Adverse selection reflects how information is shared and understood between the insurer and the insured and can lead to higher-risk individuals purchasing insurance, while lower-risk risk choosing less expensive options. The risk to insurers is to maintain the balance between those more or less likely to file a costly claim. Insurance companies can enhance post-COVID algorithms for stronger risk assessment and the reduction of selection bias. And, more competitively price insurance products based on high and low-risk applicants (Becker et al., 2020).

Managerial Recommendations

Healthcare leadership can be effective when managing financial risks and can adopt long-term strategies. Through accurate budget forecasts, risk sharing, oversight of access costs, and the use of public/private partnerships, risks can be minimized within health systems and payers. These include:

Building Real-Time Predictive Budget Models

In the era of AI-driven analytics, the post-COVID healthcare sector can minimize financial risk with real-time budget models that can rebalance approaches to care, staffing, and capital expenses. By aggregating changes across multiple health systems in enrollment, acuity, and cost, then applying it with scenario simulation, more accurate, actionable risk assessments can be formulated. By analyzing emergency room response, hospitals can not only optimize resources, but they can also better prioritize patient triage, reduce ambulance response times, and offer decision support tools to front-line workers (Chigboh et al., 2024, p. 124).

Expand Risk-Sharing Structures

The pandemic was a strong reminder of how the private and public sectors must work together to promote health safety across the United States. It is estimated that during the pandemic, through the CARES Act, the Federal government allocated over $100 billion in relief to hospitals and stabilized provider networks by reducing claim volatility (U.S. Congress, 2020). With a formal approach toward catastrophic events, risk corridors can be introduced to cap insurer losses, premiums can be kept more evenly distributed across high and low-risk consumers, and health systems can become more resilient to spikes in care. 

Strengthen Public Health Infrastructure

With virtual care becoming more and more common, it is essential to remain committed to the public health infrastructure. Telehealth can give access to underserved communities and lower costs between $147.4 - $186.1 per patient visit (Patel et al., 2023, para. 1), but it is not the answer to broader areas of risk for health systems. 

Brick-and-mortar hospitals with emergency capacity are critical for flexible care options. This includes the Federal government partnering with private health systems to stockpile items such as PPE, vaccines, and other items that were in short supply during the pandemic. 

According to the Annals of Internal Medicine, there are several areas to invest that can minimize risk to health systems and insurers, including taking action to address the shortage of public health workers, developing a national public health data infrastructure, investing in emerging epidemiology technologies, and better integration of public health services with primary care (Crowley et al., 2023).

Balance Access to Care with Incremental Revenue

Health systems work best when they offer flexible services based on the needs of local populations. When a hospital is able to reach this balance, they are more likely to expand its marginal revenue to remain fiscally solvent (Lee, 2021, p. 187). Achieving this is a product of using analytics to identify gaps in care and identifying scalable services to build on existing programs and approaches to population health management.

Enterprise Risk Management

Enterprise risk management (ERM) is an enterprise-wide methodology that integrates risk-based scenarios, financial planning, and real-time data (Etges et al., 2018, paras. 1-5). Health systems and insurers can proactively quantify risks across their organization with the objective of identifying areas of fiscal volatility and identifying gaps before they become a problem. In the case of what was seen during COVID-19, the impact of supply and staff shortages could have been minimized based on more accurate planning. 

Conclusion

The COVID-19 pandemic was a disruptive moment in healthcare in the United States that exposed weaknesses in healthcare financial planning, forecasting capacity, revenue stability, and access to care. Health systems faced risks that included lost income due to postponed planned procedures, rising costs, labor shortages, and delayed preventative care. 

As a result, the pandemic impacted financial models used by health systems and insurers for fiscal planning and could lead to an over-reliance on short-term profitable services over longer-term essential care. Although risk mitigation is an ongoing focus of hospitals, health systems, and insurers, these organizations must treat preparedness as a permanent strategy and not just a reaction to a severe health crisis.

Success will depend on the shared responsibility of key stakeholders who develop forecasts, plan care services, study underserved populations and health disparities, and create fiscal policy. Integration of data analytics, real-time decision making, public-private partnerships, and investments in public health infrastructure can reduce fluctuations in care and financial volatility. 

By embracing financial innovation, the U.S. healthcare system can build resilience, improve access, and be more likely to sustain long-term operations to be more capable of extending care during future crises.

References

American College of Surgeons. (2021, October 23). Hospitals sustained huge financial losses from lost revenues during COVID-19 pandemic as patients lost timely access to surgical services. https://www.facs.org/media-center/press-releases/2021/financial-losses-102321/

American Hospital Association. (2020, October). CARES Act Relief Funds Have Helped Hospitals and Health Systems, but Are Just a Fraction of Losses. https://www.aha.org/system/files/media/file/2020/06/aha-covid19-financial-impact-short-0620.pdf

American Hospital Association. (2021, March). Hospitals face continued financial challenges one year into the COVID‑19 pandemic [Fact sheet]. American Hospital Association. https://www.aha.org/system/files/media/file/2021/03/hospitals-face-continued-financial-challenges-one-year-into-covid-19-pandemic-fact-sheet.pdf

American Hospital Association. (2022, April 24). New AHA report highlights massive surge in input costs for hospitals and health systems. https://www.aha.org/2022-04-25-new-aha-report-highlights-massive-surge-input-costs-hospitals-and-health-systems

American Hospital Association. (n.d.). Population health management. AHA Center for Health Innovation. https://www.aha.org/center/population-health-management (accessed August 4, 2025)

Becker, G., Klotzki, U., McElhaney, D., & Srivastava, A. (2020, July 14). The post‑COVID‑19 pricing imperative for P&C insurers. McKinsey & Company. https://www.mckinsey.com/industries/financial-services/our-insights/the-post-covid-19-pricing-imperative-for-p-and-c-insurers

Best, M. J., McFarland, E. G., Anderson, G. F., & Srikumaran, U. (2020). The likely economic impact of fewer elective surgical procedures on US hospitals during the COVID-19 pandemic. Surgery, 168(5), 962–967. https://doi.org/10.1016/j.surg.2020.07.014

Bhatnagar, S., Harris, J., Hartnett, T., Hoagland, G. W., Ruff, J., & McDonough, D. (2022, May 4). The impact of COVID-19 on the rural health care landscape. Bipartisan Policy Center. https://bipartisanpolicy.org/report/the-impact-of-covid-19-on-the-rural-health-care-landscape/

Burrowes, S. A. B., Casey, S. M., Pierre‑Joseph, N., Talbot, S. G., Hall, T., Christian‑Brathwaite, N., … Perkins, R. B. (2023, September). COVID‑19 pandemic impacts on mental health, burnout, and longevity in the workplace among healthcare workers: A mixed–methods study. Journal of Interprofessional Education & Practice, 32, Article 100661. https://doi.org/10.1016/j.xjep.2023.100661

Centers for Disease Control and Prevention. (n.d.). CDC Museum COVID‑19 timeline. CDC Museum. Retrieved August 4, 2025, from https://www.cdc.gov/museum/timeline/covid19.html

Centers for Disease Control and Prevention. (2023, May). More than 1 in 3 adults delay or do not receive needed medical care because of cost. National Center for Health Statistics. https://www.cdc.gov/nchs/pressroom/nchs_press_releases/2023/202305.htm

Chigboh, V. M., Zouo, S. J. C., & Olamijuwon, J. (2024). Predictive analytics in emergency healthcare systems: A conceptual framework for reducing response times and improving patient care. World Journal of Advanced Pharmaceutical and Medical Research, 7(2), 119–127. https://doi.org/10.53346/wjapmr.2024.7.2.0050

Crowley, R., Mathew, S., & Hilden, D. (2023). Modernizing the United States’ public health infrastructure: A position paper from the American College of Physicians. Annals of Internal Medicine, 176(8), 1117–1119. https://doi.org/10.7326/M23-0670

Eaton, R. (2020, April). Actuaries in the time of coronavirus. Society of Actuaries. Retrieved August 3, 2025, from https://www.soa.org/globalassets/assets/files/resources/publications/essays-monographs/2020/covid-19/eaton.pdf

Etges, A. P. B. D. S., Grenon, V., Lu, M., Cardoso, R. B., de Souza, J. S., Kliemann Neto, F. J., & Felix, E. A. (2018). Development of an enterprise risk inventory for healthcare. BMC health services research, 18(1), 578. https://doi.org/10.1186/s12913-018-3400-7

Gergen, A. (2020, April 20). Eight COVID-related issues pools are facing today. Association of Governmental Risk Pools. https://www.agrip.org/blogs/agrip-news/2020/04/20/pooling-perspective-on-covid-19-april-20-2

Hardy, M. R. (2006). An introduction to risk measures for actuarial applications (Construction and evaluation of actuarial models study note No. C‑25‑07). Society of Actuaries. Retrieved August 4, 2025, from https://www.casact.org/sites/default/files/database/studynotes_hardy4.pdf  

Khullar, D., Bond, A. M., & Schpero, W. L. (2020). COVID-19 and the financial health of US hospitals. JAMA, 323(21), 2127–2128. https://doi.org/10.1001/jama.2020.6269

Lee, R. H. (2021). Economics for healthcare managers (5th ed., p. 87). Health Administration Press

Malik, A., Alkholief, M., Aldakheel, F. M., Khan, A. A., Ahmad, Z., Kamal, W., Gatasheh, M. K., & Alshamsan, A. (2022). Sensitivity analysis of COVID-19 with quarantine and vaccination: A fractal-fractional model. Alexandria Engineering Journal, 61(11), 8859–8874. https://doi.org/10.1016/j.aej.2022.04.029

Patel, K. B., Turner, K., Tabriz, A. A., & others. (2023). Estimated indirect cost savings of using telehealth among nonelderly patients with cancer. JAMA Network Open, 6(1), e2250211. https://doi.org/10.1001/jamanetworkopen.2022.50211

Rawson, J. V., & Stevens, J. P. (2023). Scenario Planning Approach to Adapting in the COVID Era. Academic radiology, 30(4), 572–578. https://doi.org/10.1016/j.acra.2022.11.032

Robertson, C. T., Schaefer, K. A., Scheitrum, D., Puig, S., & Joiner, K. (2020). Indemnifying precaution: economic insights for regulation of a highly infectious disease. Journal of law and the biosciences, 7(1), lsaa032. https://doi.org/10.1093/jlb/lsaa032

Shrivatsa, I. (2022, September). The impact of the COVID‑19 pandemic on health insurers (Chicago Fed Letter No. 471). Federal Reserve Bank of Chicago. https://doi.org/10.21033/cfl-2022‑471  

Stansberry, T. T., Roberson, P. N. E., & Myers, C. R. (2023). U.S. rural hospital care quality and the effects of hospital closures on the health status of rural vulnerable populations: An integrative literature review. Nursing Forum, 2023, Article 3928966. https://doi.org/10.1155/2023/3928966

Thabane, L., Mbuagbaw, L., Zhang, S., Samaan, Z., Marcucci, M., Ye, C., Thabane, M., Giangregorio, L., Dennis, B., Kosa, D., Borg Debono, V., Dillenburg, R., Fruci, V., Bawor, M., Lee, J., Wells, G., & Goldsmith, C. H. (2013). A tutorial on sensitivity analyses in clinical trials: the what, why, when and how. BMC Medical Research Methodology, 13, 92. https://doi.org/10.1186/1471-2288-13-92020

U.S. Congress. (2020). Coronavirus Aid, Relief, and Economic Security Act, Pub. L. No. 116–136, 134 Stat. 281. https://www.congress.gov/116/plaws/publ136/PLAW-116publ136.pdf

U.S. Government Accountability Office. (2023, June). COVID-19: Federal pandemic insurance options could help address business losses in future pandemics (GAO-23-106075). https://www.gao.gov/assets/d24106075.pdf

Wharton University of Pennsylvania. (2021, May). Framework for evaluating the role of insurance in managing risk of future pandemics. https://impact.wharton.upenn.edu/wp-content/uploads/2023/08/Framework-for-Evaluating-the-Role-of-Insurance-in-Managing-Risk-of-Future-Pandemics.pdf

Xu, Z., Elomri, A., Kerbache, L., & El Omri, A. (2020). Impacts of COVID-19 on Global Supply Chains: Facts and Perspectives. IEEE Engineering Management Review, 48(3), 153–166. https://doi.org/10.1109/EMR.2020.3018420