The Healthcare Workforce Shortage: Using Data & Analytics to Reduce Demands, Bridge Gaps, and Overcome Challenges

There’s a shortage of healthcare workers in the US and around the globe — a problem that’s forecasted to worsen in the coming decade.

The numbers are dismal: The Association of American Medical Colleges (AAMC) has calculated a potential undersupply of 124,000 physicians by 2034. By 2025, McKinsey estimates the US will be short 200,000 nurses. The mental health workforce is looking at vacancies of 510,000 by 2026. Healthcare systems are predicted to remain similarly thin on assistants, technicians, and therapists.

Even executive healthcare roles could be in jeopardy. In a 2022 study by consulting firm WittKieffer, 72% of executives admitted they’re considering leaving their current position.

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Why is There a Shortage of Healthcare Workers?

While this a multifaceted, complex problem, experts in healthcare commonly point to three key factors:

• Demographics — specifically, growth of an aging population that naturally experiences more chronic conditions and requires more trips to the doctor. Between 2019 and 2034, AAMC anticipates the population aged 75+ will grow by 74.0%.
• A dearth of qualified healthcare instructors due to lower pay and fewer incentives. Fewer instructors means fewer classes and, ultimately, fewer would-be healthcare practitioners filling the pipelines.
• Departures from the field of healthcare due to burnout. According to Managed Healthcare, nurses experience burnout at rates ranging from 15% to 45%. This leads “1 in 3 nurses to leave the bedside within their first two years.

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Ramifications

What does an America short on healthcare workers look like? We barely need to use our imagination — the answer, in many cases, is already apparent.

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1. Increasing Cost of Care

In his February 2023 testimony before congress, Dr. Leonardo Seoane of Ochsner Health stated that their 47-facility healthcare system currently has over 1,200 open nursing positions.

Shortages of this magnitude have forced Ochsner and other healthcare facilities to rely heavily on contract agency nurses — a reliance that’s much more expensive than hiring direct, full-time staff.

As a result, Ochsner has seen an 892% increase in staffing costs since 2019. For context, they currently contract with over 600 agency nurses.

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2. Reduced Quality of Care

With fewer nurses per facility, patients can experience longer wait times and lower quality of care.

With a high degree of staff turnover, as is the case with contract caregiving, inefficiencies, unpredictability, and other factors that contribute to poor patient outcomes are also more likely creep in.

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3. More Burnout, More Resignations

Mass exoduses from the healthcare workforce are proof of the physical and emotional toll caregiving places on healthcare workers.

Burnout has been responsible for a vicious cycle of resignations, under-staffing, heavier workloads, more burnout, and so on.

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Addressing Healthcare Workforce Shortages

As shortages in the healthcare workforce widen, workers and advocacy groups are escalating their calls for help, and public, private, and educational entities appear to be listening.

In their 2022 state of the state speeches, at least 20 governors proposed a range of policy fixes; in 2023, coalitions of health care workers and advocacy groups from more states are pressuring their lawmakers to follow suit.

At the national level, the US Congress (Senate Health, Education, Labor & Pensions Committee) recently (February 2023) gathered input from a hearing entitled, “Examining Health Care Workforce Shortages: Where Do We Go from Here?”

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Increasing Supply

Much of the support discussed thus far centers on investments to increase supply of healthcare workers, i.e., increasing incentives, improving work conditions, and funding

programs and process changes to increase educational opportunities for up-and-coming healthcare workers. These types of efforts have merit and are likely to make an impact.

However, the wide scope and complicated nature of healthcare workforce shortages necessitates a multifaceted approach from public, private, and educational entities — one that also takes demand into account.

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Reducing Demand

On its face, reducing demand for healthcare services seems implausible.

Aging Baby Boomers have arrived (the oldest of the generation are 77). And so has Covid-19.

Humans have always, and will continue to be, susceptible to an endless array of diseases, cancers, colds, and calamities — most of which aren’t easily stymied or cured.

While we can’t do much to reduce the numbers of sick or elderly, there is another path to reducing demand on the healthcare workforce.

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Advancements in Technology

Technology is a wonder, isn’t it?

In the late 1700s, British economist, Thomas Malthus, alarmed many with predictions that, before long, humans wouldn’t be able to produce enough food to keep up with growing populations.

What he didn’t see, however, was that technological innovations would one day make up for human shortcomings.

Beginning with steam engine, technology has significantly increased the pace of food production enough to support larger numbers of people than Malthus could have ever dreamed possible.

By successfully leveraging technology, automation, and other digital transformation initiatives, healthcare leaders have a shot at enabling their systems to accomplish the same — that is, to care for more people than we now dream possible.

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Data & Analytics to Address Workforce Shortages

Data & analytics and the advanced processes they support (machine learning, AI) help healthcare facilities reduce demand by creating meaningful efficiencies, often within weeks, that work to:

• Alleviate workloads, reducing stress and burnout
• Increase efficiencies, productivity, and job satisfaction, reducing churn
• Improve patient outcomes, lessening emotional stress on workers

Successful implementation and execution of data & analytics solutions serve as important models for other facilities to follow, as well as launching points for further innovation.

The following are just a few examples of data & analytics applications that facilities around the country are using to reduce demands on workers, bridge gaps in care, and overcome challenges from shortages in the healthcare workforce.

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1. Predictive Staffing to Reduce Scheduling Inefficiencies and Burnout

MercyOne Des Moines Medical Center is one of many hospitals that once struggled to schedule the right number of nurses to meet patient demand — until they found an innovative predictive analytics solution.

Using real-time data (from patient admissions, discharges, and transfers), hospital leaders can now better anticipate future demand and proactively plan and adjust incentive levels to successfully schedule the right number of nursing staff.

Real-time visibility also allows for more streamlined communications surrounding staffing needs.

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2. Real-Time Patient Flow Monitoring to Reduce Staff Workloads

The Children's Hospital of Philadelphia (CHOP) adopted a real-time patient flow management system to analyze data from various sources (electronic medical records, bed management systems, and patient tracking systems) and monitor patient movement throughout the hospital in an effort to reduce workloads.

With predictive analytics, the hospital has been able to forecast patient volumes, identify potential backups, proactively manage patient flow, and make optimal decisions about bed assignments, staffing, and resource allocation.

As a result, CHOP has been able to:

• Reduce patient emergency department wait times by 50%
• Decrease patient boarding¹ times by 60%
• Increase patient satisfaction scores
• Relieve staff from mundane tasks so they can focus on providing higher-quality care to individual patients who need it.

CHOP's success has led other hospitals and healthcare facilities around the world to adopt its patient flow management system.

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3. Automation, Monitoring, and Training to Improve Productivity

The Mount Sinai Hospital in New York City is improving productivity in operating rooms with a real-time surgical analytics system that uses data collected on different stages of surgeries, including preparation, anesthesia, surgery, and recovery.

With the application of predictive analytics to identify suboptimal activities in the surgical workflow (i.e., steps that take longer than expected), data experts are able to suggest changes that reduce surgical timeframes.

As a result, Mount Sinai Hospital has been able to:

• Reduce the average length of surgical procedures by 25%
• Increase the number of surgeries in a given day
• Reduce the workload of surgical staff
• Improve staff job satisfaction

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4. Resource Optimizing Solutions to Reduce Friction at Work

Data & analytics can also help healthcare facilities make optimal use of their resources, including equipment, supplies, and even operating room and bed utilization.

The University of California San Francisco (UCSF) Medical Center implemented a real-time location system (RTLS) that collects data from RFID tags attached to equipment and staff ID badges. Using predictive analytics to explore usage data, the solution shows staff which resources are in high demand, which may be underutilized, and where resources are being deployed.

Staff can now place equipment in optimal locations according to their usage. This helps UCSF Medical Center reduce waste, improve process efficiencies, and relieve staff from manual tracking and resource scheduling.

As a result, UCSF Medical Center has:

• Reduced time spent on searching for equipment by 50%
• Reduced time spent on non-clinical tasks overall by 20%
• Improved job satisfaction for several of its workers

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5. Telemedicine to Improve Patient Outcomes

As patients, many of us have experienced great efficiencies from access to telemedicine.

But telemedicine is also alleviating workloads for physicians and nurses too, allowing them more time to focus on in-person patient care.

The Mayo Clinic, a healthcare system in the US, uses data analytics to track its use of telemedicine, videoconferencing, and other communication technologies.

Their system identifies the types of appointments most suitable for telemedicine, and then recommends telemedicine appointments for those patients.

The system also identifies healthcare providers who’ve been particularly effective at providing remote care and matches patients with those providers.

As a result, the Mayo Clinic has:

• Reduced their number of in-person appointments by 40%
• Increased the number of telemedicine appointments by 25%
• Reduce overall workloads of existing staff
• Provided high-quality care to patients, regardless of their location

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6. Cost Optimization to Reduce Churn

Reducing unnecessary equipment or supply purchases and streamlining processes helps create a more sustainable and attractive work environment for healthcare workers. For instance, facilities can:

• Reduce their financial burdens, which helps them remain financially sustainable — a factor that builds trust with staff and increases the facility’s appeal as an employer.
• Redirect savings toward investments in staff training, development, compensation, and retention programs — all of which help improve the work environment and retain healthcare workers.
• Invest savings in technology and resources that help providers deliver better quality care. This also helps attract and retain healthcare workers passionate about providing high-quality care.

The Montefiore Health System in New York is one facility that uses data & analytics to optimize their supply chain and medical supply costs.

With data from various sources, including purchasing, inventory levels, and usage patterns, data experts at Montefiore use predictive analytics to identify shortages and surpluses and better forecast demand.

This information helps the purchasing department to reduce excess inventory, avoid stockouts, adjust purchases, and keep inventory at optimal levels.

As a result, the Montefiore Health System has:

• Reduced supply chain costs by 15%
• Improved inventory turnover by 25

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7. Optimizing Recruitment and Retention to Attract Healthcare Workers

Analytics is also used to identify patterns in staff turnover and develop strategies to improve recruitment and retention.

For example, The University of Pittsburgh Medical Center (UPMC) in Pennsylvania implemented a workforce analytics system that collects data from various sources, including job postings, candidate resumes, and employee surveys, and then uses predictive analytics to identify characteristics of successful hires as well as factors that influence employee turnover.

This has allowed UPMC to optimize recruitment and retention strategies by targeting job postings to specific candidate demographics, offering training and development programs, and providing appropriate employee incentives and benefits.

As a result, UPMC reduced employee turnover by 20% and increased employee satisfaction scores.

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Conclusion

The care and well-being of humans is an essentially human-centered endeavor. Healing requires human touch, empathy, and compassion that only fellow humans can provide.

It is by virtue of our very humanity, however, we’re limited in our capacity to care for each other. The current shortages in our healthcare workforce are testament to that. We simply don’t have enough humans willing or able to keep our healthcare systems functional.

This is where digital transformation must come in. Technology serves its highest and best purpose when it improves the human condition, enhances quality of life, and meets human needs.

Data and analytics is already helping healthcare leaders around the nation and the world manage patient care more efficiently, relieve workloads, and recruit and retain healthcare workers — but there’s potential for so much more.

As a leading service provider of digital transformation services, Wimmer Solutions is ready to partner with your healthcare facility to help you bring in the power of data & analytics.

Learn more by booking a call with a Wimmer Solutions representative today.

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¹ This refers to the amount of time patients must wait for a bed after they’ve been admitted to the hospital

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