How to Overcome Coding and Documentation Challenges as Outpatient Volume Grows

How to Overcome Coding and Documentation Challenges as Outpatient Volume Grows

Over the past few years, the convergence of numerous trends has resulted in a steady decline of inpatient hospital services. Thanks to technological and procedural advances, a growing tendency of consumers to avoid hospitals and the transition to value-based payment models, more care is shifting to outpatient settings.

Programs and incentives are requiring healthcare providers to invest heavily in this area as a result.

Inpatient services and “heads in beds” used to be the primary source of revenue at many hospitals, but those days appear to be receding. According to a Deloitte Insights investigation of hospital revenue trends, inpatient revenue experienced a compound annual growth rate of 6% from 2011 to 2018, while outpatient revenue grew 50% more (or an average of 9% annually over the same period). The rapid growth in outpatient volume has blurred the lines between inpatient and outpatient departments, but certain obstacles stand in the way of effective collaboration.

Coding and Documentation Challenges

In the outpatient treatment environment, the revenue cycle department increasingly relies on coding and documentation to support the claims and payment process. With large increases in patient volume and a high turnover rate, however, the accuracy of this documentation can pose a problem. Single coders are often expected to review documentation, coding, and risk at the same time, and physicians can’t return to each completed chart to answer queries because outpatient visits last an average of just eight to 40 minutes instead of possibly days in the inpatient setting.

To effectively overcome these challenges, leaders need to implement four critical steps:

  1. Give coders the right tool(s)
    Coding and RCM managers need to give coders the tools to identify documentation gaps, potential coding accuracy improvements, and risk-score opportunities. Computer-assisted coding, or CAC, is becoming the norm for complete and accurate documentation in any healthcare environment, but artificial intelligence such as natural language processing will turn it into a transformational tool that eliminates all-too-prevalent gaps in patient documentation and offers a 360-degree view of the patient.

  2. Rely on targeted physician education
    The right tool doesn’t just let coders make immediate improvements. They should also be able to use findings to make pinpoint physician education recommendations that help reduce documentation gaps in the future. Educating physicians and improving their documentation will ease the burden on coders and keep them from repeatedly correcting the same mistakes.

  3. Combine or coordinate disjointed revenue cycle management departments
    As outpatient services begin to drive increased revenue, it’s vital for healthcare providers to respond by combining inpatient RCM with outpatient RCM. A broad view of utilization and revenue can help identify populations that need more value-based care, improving the health of patients and keeping providers financially solvent.

  4. Emphasize outpatient risk scoring to support value-based programs
    Value-based care is rapidly gaining momentum, but providers will need to improve documentation and risk-scoring practices to ensure they’re delivering high-quality care. AI-powered CAC platforms with features such as real-time transcription enable the formerly disparate CDI and HIM departments to assemble data and look for documentation inefficiencies and risk-scoring procedures that don’t accurately reflect patient health and mortality rates.

The future of healthcare is about documenting delivery and results — for both the financial health of providers and the quality of patient outcomes. Recognizing the power of AI to improve healthcare and optimize revenue streams, EZDI combines robust CAC and CDI capabilities in an intuitive, cloud-based platform that can double the productivity of staff and arm management with the kind of real-time analytics that allow them to take targeted action. As a result, the platform pays for itself almost overnight while charting a path toward greater organizational growth.



By designing a next-generation clinical NLP engine supporting advanced documentation and coding functions, EZDI turned their vision to reality. Their CAC and CDI solutions received tremendous feedback, providing system accuracy and ease of use. EZDI removes the data complexity and highlights what matters for healthcare professionals.

EZDI is a provider of AI-based mid-revenue cycle management solutions to Hospitals and Health Systems.

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