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Reimagining workforce in 2024: The rising role of clinician big data

As the prospects of healthcare workforce shortages loom large, organizations will increasingly use big data to combat burnout and improve human resource initiatives.


By Axuall CEO Charlie Lougheed for Health Data Management. This article is part of the December 2023/January 2024 COVERstory: 2024 Predictions.


It’s easy to see the future when you can appreciate what’s happened in the past. In healthcare, looking at the transformation of patient data makes it clear what needs to happen and what will happen in the future with clinician data.

Traditionally, data and analytics have been an area where healthcare has played catch-up with other industries. It wasn't until about a decade ago that patient "big data" came onto the forefront, ushering in new ways to identify correlations, manage populations and measure outcomes. We're now entering a new era of healthcare analytics in which clinician big data joins industry efforts to address some of the most significant healthcare challenges, like workforce shortages and clinician burnout.

Workforce shortages

When you think of supply chain management in healthcare, most people think about personal protective equipment and prescription drugs. However, the fact is that this pales in comparison to the growing supply chain problems in the healthcare workforce. The Association of American Medical Colleges estimates a workforce shortage of 124,000 physicians by 2031. There’s expected to be an even more significant shortage among nurses; the U.S. Bureau of Labor and Statistics estimates a shortage of 200,000 nurses by the same year.

Addressing this workforce supply chain problem is critical for the well-being of our health systems, but even more so for patients receiving and paying for care. There is no choice but to address this issue. In 2024, we’ll see a concerted effort to appropriately access and use extensive, up-to-date clinician data as a building block for creative solutions to tackle this problem. 

Burnout

Unmanageable workloads because of staffing shortages among physicians, advanced practice providers, nurses, technicians, allied health and home aides significantly contribute to rising burnout rates. A recent Medscape survey found that more than half of physicians experience burnout. While these daily demands continue to compound, medical professionals face a problematic decade ahead as our population of individuals 65 and older surpasses 56 million, lifespans increase and chronic conditions continue to rise.

While no one has a crystal ball, the status quo is unsustainable. We'll start to see clinician big data used more to help solve some of healthcare's most pressing issues. Utilizing clinician data, like patient data in the past decade, will give health systems the tools to understand why clinicians feel burnout. More importantly, it will determine what strategies will create a work environment best suited for healthcare workers.

How will clinician big data solve these problems? It can’t do it by data alone. Big data by itself is “big noise” if not properly curated. But in the upcoming year, this data, combined with artificial intelligence that can analyze and predict, will be incorporated more by health systems. Major problems like workforce shortages and burnout that seem unfixable will become attainable problems to solve, albeit incrementally at first. Clinician big data does that in the following ways.


  • Provide the tools for pinpoint recruiting. Clinician big data makes understanding hiring needs before a staffing shortage becomes a reality. When a health system can visualize real-time workforce trends and gaps, it can analyze and adapt accordingly — for example, by hiring a specialist based on the trending patient encounters, clinician practice patterns and provider referrals in the surrounding area. This insight enables health systems to anticipate and meet patient demands and ensure appropriate physician workloads.

  • Ensure high clinician engagement and satisfaction with streamlined onboarding processes. In a world where Internet advertisements seem to already know what you’re thinking, there’s no reason that clinician credentialing, a requirement to keep patients safe, takes weeks or months to complete and often delays clinicians from doing what they’re trained to do, treat patients. Health systems will tap into existing data sources to improve and speed up onboarding processes to hire quickly and efficiently based on priority needs and patient demands.

  • Future-proof our most valuable healthcare resource: clinicians. Health systems can use real-time clinician big data, not anecdotes, to inventory clinicians across demographics, license types, service lines, facilities, markets, procedures, practice affinity and patient populations to mirror location-specific supply and demand.

In light of the stakes, there has never been a greater need to apply data to address these challenges in the U.S. healthcare workforce, like shortages and burnout. However, until recently, the data relative to a practitioner's credentials, skills, capabilities, utilization factors, stress level and placement potential is scattered across hundreds of sources and often out-of-date and incomplete.

This makes it difficult for healthcare leaders to meet credentialing and privileging regulations, quickly deploy appropriate resources, and optimize their workforce. In 2024, health systems will begin to optimize and utilize clinician data at scale to address the biggest challenge facing healthcare today – the supply and demand gap.

Charlie Lougheed is the CEO and co-founder of Axuall.

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