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By AGS Health
October 25, 2022
Clinical documentation has a long history in medicine, dating back to the papyrus records of ancient Egypt nearly 4,000 years ago. This method of clinical documentation, however, was solely for didactic purposes. It wasn't until the twentieth century that the idea of using clinical documentation to improve patient care became systemic.
Manual record-keeping is nearly extinct, even though clinical documentation is still essential in healthcare. Electronic health records (EHRs) have allowed physicians and healthcare providers to access a unified source of complete patient information and case histories via various platforms, including smartphones and tablets.
The last ten years have unquestionably been the most transformative in terms of clinical documentation. The U.S. Centers for Medicare and Medicaid Services (CMS) sanctioned the 'pay-for-performance' initiative in 2012, marking a watershed moment in healthcare history. This paved the way for the transition from a volume-based model to a value-based care model for the industry. The change, however, has not been easy for healthcare institutions. It has led to issues with value-based reimbursements, such as hospital-acquired complications (HACs) and audit issues stemming from insufficient documentation.
Hospitals must prioritize accurate clinical documentation for the value-based care model to succeed. A strong clinical documentation improvement (CDI) program improves patient care quality by increasing coding accuracy and improving communication between siloed departments. The result is better data in the hands of physicians, which influences treatment – improving both the safety and quality of care.
However, legacy CDI programs tend to be plagued by unstructured information and data duplication, which prevent CDI’s primary objective: accurate documentation. Furthermore, leadership is under constant pressure to demonstrate the ROI of their CDI systems, and legacy systems frequently fail to deliver the benefits that justify their costs.
The need to transform becomes more evident when considering the survey results of industry-leading rating firms, such as Leapfrog and U.S. News & World Report. The annual Leapfrog Hospital Survey demonstrates unequivocally that the healthcare industry must embrace the transition from legacy to more modern, technology-enabled documentation methods.
These surveying bodies profile hospitals based on how they leverage CDI to elevate patient safety and quality of care. Clinical processes and indicators are among the survey parameters, which are again influenced by documentation. A hospital's clinical expertise and financial standing are heavily influenced by its performance in these rankings. A strong CDI program enhances a hospital's reputation and credibility.
What exactly constitutes a quality CDI program? Its ability to reliably produce accurate, complete, and compliant documentation.
When documentation is complete and accurate, it produces tangible results, such as process optimization measures that maximize revenue. It can also be leveraged to measure outcomes objectively. This leads to accurate hospital profiling and public reporting, which increases the visibility of the hospitals’ capabilities.
Accurate documentation of HACs, patient safety indicators (PSIs), and risk-of-mortality (ROM) affects quality measures that influence a hospital’s bottom line. Both Medicare and CMS use these metrics to determine reimbursements.
With insurance companies increasingly adopting a payment model based on Medicare Severity Diagnosis Related Groups (MS-DRGs), accurate documentation has become essential. Failure to meet these requirements will negatively impact reimbursements. Effective CDI has helped hospitals recover millions in improper insurance payments through initiatives such as the CMS's Recovery Audit Contractor (RAC) program.
There are countless advantages of a robust CDI program. Yet, hospitals and healthcare institutions can face numerous challenges when implementing technologically enhanced CDI practices. One challenge is the initial investment. Hospital leadership must be convinced of the benefits and ROI of any new program before moving forward. Furthermore, helping physicians engage in the CDI program is crucial to successful implementation.
Since the benefits of CDI are linked to performance-based outcomes, measuring ROI is only visible at the end of the value chain. This makes it difficult for leadership to track or showcase the immediate results of their CDI program transformation.
Regarding response time, physicians frequently put coder and CDI staff requests on the back burner. As a result, cases are more likely to be delayed, which has a negative impact on healthcare institutions' quality-based KPIs.
Furthermore, a team of clinical documentation specialists (CDSs) within the care facility is necessary to implement a robust CDI program. There is a shortage of qualified personnel because CDI is not part of organized learning in medical school and has only recently emerged. As a result, hospitals need extensive training programs, which adds to the implementation cost. This can appear to be a barrier to growth in a highly competitive environment.
Another challenge is the expansion of CDI to include other service lines such as outpatient and emergency departments. According to a, survey by the Association of Clinical Documentation Improvement Specialists (ACDIS) only 10% of hospitals currently have an outpatient CDI program in place. Extending CDI to these services can require time and money, which can be challenging for hospitals with limited resources. Additional barriers to implementing outpatient CDI include:
The siloed nature of departments like Health Information Management (HIM), Quality Management, and Case Management makes it difficult for hospitals to rely on legacy documentation processes to overcome challenges. The digitization of records has helped to alleviate some of the problems, but obstacles persist. For example, healthcare professionals with access to EHRs can work remotely with CDI, making work schedules more flexible. However, remote CDI impedes the process of collaboration between these siloed departments. Working remotely makes it difficult for HIMs and CDSs to form relationships with physicians, further obstructing collaborative efforts.
So how do we continue to improve CDI? CDI in the 21st century is no stranger to digitization and technology. Most hospitals are now using technology to supplement their CDI programs. However, because CDI directly impacts revenue and efficiency, it is necessary to improve its technological capabilities. Natural language processing (NLP), for example, is an AI-enabled technology that promises to revolutionize documentation improvement.
Typical digitized medical record systems rely on predefined codes and data sets that are useful for performing simple repetitive tasks. However, these tools fall short when completing tasks like coding and documentation. Despite widespread digitization of many healthcare systems, the clinical documentation process remains inefficient due to this manual process. The disparity in information and operational silos is revealed by shallow analytics captured on spreadsheets. On the other hand, NLP can identify key characteristics in the documentation, extract large amounts of clinical evidence quickly, and improve interdepartmental collaboration throughout the CDI process.
While EHRs have undoubtedly aided in the automation of patient record processing, they also result in redundant data, low-quality records, and a slew of errors that wreak havoc on the CDI process.
As a result, NLP-powered CDI is far more efficient than CDI powered by traditional technologies. For instance, a standard CDI approach takes an average of 17 minutes for a cardiology entry, whereas an NLP-powered CDI model takes just over 5 minutes. This ability to quickly extract critical documentation notes can help overcome the challenges of implementing a robust outpatient CDI program.
An EHR data depository can be transformed into structured data using AI and NLP. This allows medical coders to quickly sift through massive amounts of data to find relevant information, resulting in intelligent case prioritization. Electronic query templates (EQTs) are an excellent example of this type of automation. They accelerate the process of clarifying documentation in medical records and ensures accurate code assignment. Because these tools are easy to use, stakeholders can code accurately, regardless of their knowledge of clinical documentation. This could be a key characteristic in increasing physician engagement.
Most important, AI-enabled NLP can help create a single, unified information platform - removing silos and promoting free information exchange among stakeholders across departments. These solutions can improve the overall operational efficiency of the healthcare system by encouraging intra- and inter-departmental collaboration.
“The average return on investment for AI applications is $9.87 on every dollar spent.”
“The average return on investment for AI applications is $9.87 on every dollar spent.”
However, deploying AI-based tools to improve the CDI framework has more benefits than just consolidating data across various parameters and automating complex processes. The availability of advanced data analytics is one of the most essential aspects of AI in CDI. Through dashboards and reports, AI tools provide the CDI staff with valuable insights. This can make gaining physician buy-in and collaboration with HIM and CDI personnel much more accessible. More importantly, the numbers and insights extracted can provide CDI and HIM staff with recommendations and prioritize various actions by defining the most immediate goals of the department.
Clinical data analytics can pinpoint insights based on existing healthcare data, allowing doctors to prioritize patients who require immediate treatment. They can also detect areas where coding and documentation auditing could be improved, resulting in a higher CDI overall.
With CDI serving as a beacon of progress for the healthcare industry, providers must adopt solutions incorporating AI, NLP, and analytics. AGS Health’s industry-leading expertise in these technologies has led to healthcare organizations achieving higher quality documentation.
Our solutions include AI-based and integrated Computer-Assisted Coding, CDI, Coding Compliance, Quality Measures, and Enterprise Analytics. Our clients have implemented them and noticed improvements in hospital reputation and higher levels of patient care. Our CDI solution, which is powered by NLP, can help you achieve effective intra-departmental collaboration, as well as more accurate medical coding and billing, allowing you to provide better care to your patients.
AGS Health is more than a revenue cycle management company–we’re a strategic partner for growth. By blending technologies, services, and expert support, AGS Health partners with leading healthcare organizations across the US to deliver tailored solutions that solve the unique needs and challenges of each provider’s revenue cycle operations. The company leverages the latest advancements in automation, process excellence, security, and problem-solving through the use of technology and analytics–all made possible with college-educated, trained RCM experts. AGS Health employs more than 10,000 team members globally and partners with more than 100 clients across a variety of care settings, specialties, and billing systems.