How Data and Analytics Uncover Credentialing Inefficiencies and Improve Hospital Operations

Apr 7

By: Jacob Byrlen, COO Radiant Healthcare

Credentialing is the backbone of any hospital’s workforce management. Critically, it ensures clinicians are qualified, compliant, and ready to deliver care.

For many large hospitals, however, this important process is mired in inefficiencies caused by outdated systems, manual workflows, and data that is both fragmented and overwhelming,

These inefficiencies create administrative headaches, delay onboarding, increase costs, and jeopardize compliance.

The good news is that data and analytics offer a solution. By uncovering hidden inefficiencies, hospitals can optimize their credentialing workflows and improve outcomes.

In this article, we'll explore how data turns credentialing into less of a burden and more of a strategic advantage.

How Analytics Uncover Credentialing Inefficiencies

Data analytics offers hospitals a unique advantage: the ability to see the entire credentialing process with clarity and precision.

With detailed insights into their workflows and performance metrics, it is easier to identify inefficiencies, pinpoint bottlenecks, and focus on improvement areas.

Here's how this can be achieved in practice.

Workflow Mapping

Workflow mapping is a critical tool in healthcare credentialing because it provides a clear visual representation of each step in the process.

With these maps, hospitals can uncover inefficiencies such as redundant steps, delays, or unnecessary handoffs that slow down clinician onboarding.

For example, a hospital may discover that the HR department and the credentialing team are verifying a clinician's medical license. When this task is consolidated under one team, the hospital eliminates duplication and saves valuable time and resources in the process.

Bottleneck Identification

Data also pinpoints where the credentialing process consistently stalls and impacts patient care or provider onboarding. For instance, analytics could reveal that background checks—which should take five days—are averaging ten days due to slow vendor responses.

With this information, a hospital could renegotiate vendor contracts or implement automated follow-ups to reduce delays. Other effective interventions include resource reallocation and automation.

Error Detection

Manual data entry is one of the most error-prone areas of credentialing. What’s more, around 5% of healthcare providers have data in their records that is indicative of suspension, exclusion, or disbarment.

Analytics can detect inconsistencies or missing information and alert teams early in the process. This proactive approach reduces the need for rework, which results in additional processing and resubmission-related costs.

Importantly, it also avoids potentially costly compliance issues and a scenario where unqualified providers consult with patients.

Performance Tracking

Analytics dashboards bring clarity and control to the credentialing process by offering real-time visibility into workflows, task completion rates, and individual team performance.

These tools empower teams and hospital leadership to identify slow-moving processes, underperforming areas, and other inefficiencies that may otherwise go unnoticed.

Performance tracking adds value to the credentialing process in a few key ways:

Real-time insights. Dashboards allow teams to monitor tasks in real time. If a particular step falls behind schedule, managers can take immediate action or investigate the root cause of the delay.
Identifying resource gaps. Data could reveal that one team is consistently slower than its counterparts. In response, leadership could provide targeted training, adjust workloads, or adopt tech-based solutions to balance the workload.
Measuring process efficiency. Tracking KPIs such as average processing time, error rates, and committee review cycles helps organizations stay aligned with operational goals. Utilizing milestones across the credentialing process to promote transparency is also crucial.

Predictive Analytics

Hospitals can also analyze historical data to forecast potential issues before they occur. For example, if analytics shows a seasonal spike in license expirations, credentialing teams can allocate extra resources or send automated reminders to clinicians well in advance.

Predictive analytics applies techniques from data mining, statistics, modeling, and artificial intelligence to predict risk. In the process, it helps personnel improve clinical outcomes and make smarter decisions.

Data Integration

Hospitals often struggle when fragmented credentialing data is spread across multiple systems. Analytics platforms integrate this data and offer a unified overview that eliminates duplication and ensures accuracy.

Such a platform could reveal that multiple departments are unknowingly requesting the same licensure verification, for example.

Transform Credentialing with Radiant Healthcare

Radiant Healthcare specializes in helping hospitals leverage analytics to uncover inefficiencies and implement targeted solutions. With a combination of expertise and advanced tools, Radiant enables hospitals to:

Visualize workflows to identify bottlenecks, redundant steps, and areas for improvement.
Monitor credentialing progress to make sure tasks stay on track, and
Automate repetitive tasks and streamline processes like document verification and expiration tracking.

If you’re a hospital experiencing credentialing difficulties, we’re here to help. Schedule a consultation with Radiant today to discover how data-driven solutions can transform your credentialing process and improve operational performance.

References

https://www.99mgmt.com/blog/how-much-do-physician-credentialing-services-cost

https://www.namssgateway.org/Article/real-metrics-real-impact-how-credentialing-drives-patient-safety-and-quality

https://www.qgenda.com/blog/five-best-practices-for-using-workflows-part-five-track-and-set-milestones/