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Incremental Revenue Generation in Health Systems

On average, health systems have reported generating an impressive $1,223 in incremental revenue per provider, per month specifically for ambulatory care services. This statistic serves as a beacon of the financial benefits that can be harnessed through improved operational efficiency and reduced clinician documentation requirements.

The Burden of Documentation

As healthcare providers strive to alleviate the documentation burdens on clinicians while bolstering financial performance, advanced AI tools integrated directly into clinical workflows are emerging as vital assets. These technologies significantly enhance operational and revenue outcomes by streamlining documentation processes and minimizing administrative tasks for healthcare providers.

Insights from KLAS Research

The value of AI-powered solutions is further evidenced in a recent KLAS Research report focusing on Suki’s AI clinical intelligence platform across three notable U.S. health systems:

1. FMOL Health: A nine-hospital system located in Baton Rouge, Louisiana, serving regions in both Louisiana and Mississippi.
2. McLeod Health: A seven-hospital network based in Florence, South Carolina, which caters to twelve counties in northeastern South Carolina.
3. Rush University System for Health: Comprised of three hospitals based in Chicago.

These organizations successfully deployed Suki’s technology within ambulatory care settings, facilitating clinical note creation and evaluation and management (E/M) coding seamlessly within their existing electronic health record (EHR) workflows.

Why These Findings Matter

The analysis from the KLAS report reveals compelling benefits. Clinicians utilizing the Suki platform have successfully reduced after-hours documentation activities by an impressive 35% to 65%. This significant reduction indicates a notable alleviation in documentation burdens, allowing healthcare providers to reclaim precious time within their regular working hours.

Moreover, the study highlighted the direct financial implications associated with enhanced coding performance. Participating health organizations averaged $1,223 in additional revenue per provider each month. Remarkably, this was achieved without imposing additional productivity demands or altering existing clinical schedules.

Operational Enhancements and Patient Flow

Alongside improvements in revenue and documentation metrics, the report underscored operational enhancements related to patient access and throughput. The three health systems experienced organic increases in patient volume, attributed to the gains in clinical efficiency and workflow performance realized after implementing the Suki platform.

Testimonial from Dr. Bryon Frost

Dr. Bryon Frost, Chief Medical Information Officer at McLeod Health, emphasized the transformative impact of Suki’s AI capabilities. He stated that the technology adeptly captures comprehensive clinical encounters in real time, accounting for interruptions and multi-party discussions while automatically generating structured notes for clinician review.

“This end-to-end flow minimized manual input and entirely eradicated the need for laborious post-visit encounter reconstruction,” said Frost. “A key differentiator for us has been the intrinsic workflow flexibility and user-friendliness.”

Clinicians have the option to utilize Suki as a standalone application or directly within Epic Haiku, aligning with their preferences and clinical environments. This uniformity across various settings alleviated friction, shortened the time required for adoption, and enabled clinicians to experience substantial time savings without increasing cognitive load.

Building on Success

Following this success, McLeod plans to extend its deployment of ambient clinical intelligence solutions to inpatient providers, aiming to extend similar documentation relief to hospital-based teams. “We are also gearing up for the implementation of ambient nursing documentation, empowering nurses to automatically capture documentation during care delivery,” Frost added, highlighting the shift towards reducing administrative burdens and increasing direct patient interactions.

A Broader Perspective

Dr. Frost stressed that healthcare organizations should perceive incremental revenue without additional productivity expectations as an indicator of improved system efficacy rather than a signal for clinicians to exert more effort. “At McLeod, the return on investment (ROI) derived from ambient AI was not a result of increased volume or compressed schedules,” he noted. “It stemmed from improved documentation processes.”

At a systemic level, enhancements in documentation accuracy and coding not only optimize individual patient encounters but also have the potential to fundamentally transform how care is delivered throughout the organization. When clinical documentation reliably reflects true medical decision-making, risk, and complexity, it establishes a solid foundation for operational, financial, and clinical decision-making.

The Role of AI legalese decoder

In navigating the complex world of healthcare documentation, AI legalese decoder can play a pivotal role. This tool helps in demystifying complicated legal language, ensuring that healthcare providers fully understand documentation protocols, compliance issues, and financial implications associated with AI implementations. By clearly translating technical jargon into plain language, the AI legalese decoder empowers healthcare professionals to make informed decisions, minimizing legal risks while maximizing operational efficiency.

Dr. Frost anticipates that as AI becomes more intricately woven into clinical operations, these capabilities will foster sustainable care delivery models. “Our system will become less reliant on extraordinary efforts and overtime, focusing instead on accurate data, clinician engagement, and intentional capacity usage,” he concluded. “This is the essence of a truly clinician-centered, scalable care model.”

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