Clinician big data has the power to transform healthcare organizations, but its potential remains largely untapped. According to a report by the World Economic Forum, hospitals generate 50 petabytes of siled data each year, 97% of which remains unused. The healthcare industry is missing an important opportunity to better understand care patterns and usage and provide supported decision-making through analysis of clinician data.
Using clinician data as a strategic foundation for success has never been more important. The healthcare industry faces major staffing shortages, exacerbated by the pandemic. From 2021 to 2022, more than 145,000 U.S. healthcare providers retired, including 71,309 physicians. These clinicians essential to medical practice include nurses, physician assistants, physical therapists, social workers, and more. On the nursing side, the U.S. Bureau of Labor Statistics predicts that more than 275,000 additional nurses will be needed by 2030.
In response, organizations have begun to refocus on recruiting clinicians, but the number of applicants remains limited and rapid and efficient onboarding and placement remains a challenge. Long-standing industry standard approaches are no longer sufficient. There are only a limited number of schools that can recruit clinicians, and there are also only a limited number of clinicians who are willing to accept the current state of the environment. Healthcare industry leaders are redoubling their retention efforts and increasing the capabilities of existing employees within their facilities. Facing ongoing financial performance pressures, these leaders recognize that delays in onboarding can cost them about $6,000 per day in lost revenue per physician practice. I’m leaving it. Clinician big data is key to optimizing the existing workforce and essential for engaging clinicians in smarter, more efficient healthcare delivery.
Rethinking data use in healthcare
When “big data” is referred to in the medical field, it is often referring to patient data. Over the past decade, patient data has advanced dramatically, improving outcomes and reducing costs. However, as workforce shortages and burnout threaten medical progress, it is time to focus on the vast amount of clinician “big data” available to health systems.
Intentional changes that recognize this potential are needed to facilitate the application of clinician data in healthcare settings. This cultural shift to embrace big data is already happening in many other industries and has the potential to solve many of healthcare’s most pressing workforce problems.
Improving the efficiency of the healthcare worker supply chain
Leaks due to management inefficiency are common. It is estimated that 15% to 30% of all healthcare spending is administrative costs. For example, workforce optimization focused on network development, clinician recruitment, credentialing, and enrollment has traditionally been a manual and time-consuming task. Leveraging clinician big data can significantly improve these processes and employee operations.
Here’s how the collection and secure curation of clinician data, and subsequent analysis, provides a proactive means to understand and optimize your workforce.
- It’s time for health systems to hire more data scientists. Health systems will need to combine advances in big data networks, AI, and predictive models with individuals trained to leverage these technologies and integrate them into organizational decision-making structures.
- Workforce analytics for large data sets provides insight into complex and distributed workforces across departments, facilities, and even, to some extent, competitors’ facilities by leveraging claims data sets. . Understanding supply and demand trends across clinician groups and geographic locations reveals important ways to leverage and strategically expand your existing workforce.
- “Clinician phenotyping” is the process of studying employees by comprehensively assessing their qualifications, experience, and behaviors to predict performance, burnout, and attrition. This will become increasingly important in managing healthcare costs and outcomes.
- Innovative organizations can leverage large data networks to automate and streamline manual processes that drain valuable resources across clinicians and administrators alike. By injecting data into the application process for privileges and enrollment, health systems can hire talent faster and more securely, saving time and money.
The conclusion is
In an industry experiencing catastrophic attrition and labor shortages, organizations that streamline clinician processes can gain a competitive advantage. Based on their understanding and analysis of the information provided during enrollment, these health systems attract and retain top talent and ensure that they perform at their best in the right environment. The more you understand any situation, the better you will be able to meet its challenges. There has never been a better time to collect and analyze as much data as possible about the clinician population to address the need to close the gap between supply and demand for talent in healthcare.
About the author
Charlie Lougheed is CEO and co-founder of Axuall, a workforce intelligence company based on a national real-time clinician data network. This will enable healthcare organizations to create more efficient care networks while reducing onboarding time by more than 70%.
Lougheed co-founded and co-funded Explorys (now IBM Watson Health) in 2009 as a spinoff from Cleveland Clinic. Explorys has become a leader in healthcare big data and value-based care analytics reaching hundreds of thousands of healthcare providers and his more than 60 million patients across the United States. Having amassed the world’s largest clinical dataset, his Explorys provide payers, life sciences, and pharmaceuticals with real-world evidence and insight into product planning, research, health economic outcomes research, and safety. We have provided services.
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