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Combatting the Clinician Shortage Through Robotic Process Automation


As the clinician shortage continues, leaning on technology to streamline inefficiencies is essential.

Healthcare systems contain multiple burdensome tasks and strict regulations that require a substantial amount of resource allocation. This inefficiency can lead to high costs of operations, and slow processes, especially when it comes to credentialing, onboarding and deploying clinician workforces. The pandemic, coupled with an aging population with increasing numbers of people with chronic, long-term conditions, has created a perfect storm to disrupt the healthcare market.

In fact, the U.S. could face a shortage of up to 124,000 physicians by 2034, which means the supply and demand gap between patients and clinicians is continuing to widen. In an industry that is already facing staffing shortages and supply chain problems, how do we combat this issue? Technology, likeRobotic Process Automation (RPA) and data analytics is a great place to start.

Diving in: What is RPA?

To put it simply, RPA is software technology that’s easy for anyone to use to automate digital tasks. RPA can sound like a threatening term for health administration teams, but in reality, this technology should be looked at as their friend, rather than their enemy. These bots enable teams to reduce the time and effort associated with data collection, freeing their time to focus on data analysis and coordination. This is increasingly important in an age of worsening staffing shortages among administrators. Hiring paper-pushes is getting more challenging, in part because the younger generations are seeking data jobs that align better to career growth and stability.

The True Power of Data Analytics

Workforce intelligence is one of the most meaningful solutions that currently exists to enable leaders to better manage their most important asset, human capital. Automation, when combined with workforce intelligence, enables leaders to plan their care networks, providing visibility into where resource supply and demand are today and in the future, especially when combined with market data. Not only does it streamline the recruiting process, but it also makes it easier for clinicians to apply for positions or privileges. This further improves patient access to care, while also dramatically increasing the bottom line by preventing leakage, reducing burnout, and improving financial performance.

While this automation isn’t a new concept in healthcare, its potential to help alleviate some of the stress on the healthcare system today has become much more prevalent. By combining RPA with big data analytics, the two can eliminate much of the manual intervention that currently holds administratorsback from the truly important activity that requires critical thinking and allows clinicians to get in the field faster and spend more time with patients. The widespread adoption of this technology could empower MSPs and healthcare executives to collaborate, analyze, plan, and deploy resources where they’re most needed in a way that’s never been possible before – all while automatically meeting credentialing and privileging regulations at the same time.

Looking Ahead

The integrated use of analytics is a core factor in giving health systems the opportunity to build better networks, all while empowering healthcare administration teams with better, more complete, and more timely data -- that also complies with industry standards and aligns with existing workflows. The early adopters of big data and analytics, combined with the power of RPA, are set to enjoy a significant advantage over the competition and reap the benefits in the long run.

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