This article is published in collaboration with Nuance.
It’s no secret that artificial intelligence (AI) has changed the way modern society operates. Between algorithms predicting the content individuals are most likely to engage with on social media, to virtual assistants providing real-time customer support, AI has quickly made its mark across industries and use cases.
However, with promises ranging from added convenience to increased personalization and better outcomes, it can be difficult to pinpoint the direct implications of AI in different healthcare environments and roles. This ambiguity has even led to the misconception that AI will replace jobs such as clinical documentation integrity (CDI) professionals.
But to capitalize on this rapid innovation within healthcare, it is critical that leaders see AI as an extension of their teams. Here are five key ways that AI can multiply the impact and effectiveness of CDI teams.
1. AI enhances productivity.
Generally, technology has been known to improve CDI team productivity. For example, according to ACDIS’ 2022 Industry Survey, over 22 percent of respondents noted an immediate productivity improvement after implementing electronic queries, with nearly 40 percent noting an improvement after an adjustment period. Layering AI onto the existing CDI workflow can further bolster productivity.
For example, with prioritization technology, CDI specialists (CDSs) can eliminate the time-consuming and manual process of discerning which cases to review first. AI proactively scans patient records and automatically identifies documentation with the greatest opportunities for improvement, allowing team members to manage their time more effectively for the greatest impact.
Moreover, because the specific documentation opportunities have already been flagged for the specialist, CDSs know which cases should be their priority and what it is they are looking for. With sophisticated AI, CDSs can quickly review AI findings, access clinical evidence and related reference material in a centralized location, and then apply their clinical expertise accordingly.
2. The technology can promote provider engagement and collaboration.
Optimizing clinical documentation involves collaboration across various stakeholders. Without the proper level of physician engagement, CDI teams are limited in their ability to affect change.
Moreover, research shows that the administrative burden of clinical documentation is a large contributor to physician burnout, making the challenge of physician engagement even more daunting. AI, however, can help mitigate these obstacles by delivering documentation guidance at the point of care via computer-assisted physician documentation (CAPD).
Rather than having to revisit the details of a patient’s case days later due to a retrospective CDI query, physicians are made aware of impactful guidance in real-time, allowing them to streamline their workflow by making quick adjustments to their documentation.
For example, CAPD may identify that the provider documented a patient’s respiratory failure but neglected to specify what type–a distinction that can have important ramifications for patient care, quality outcomes, and reimbursement. The AI will flag this to the provider, allowing them to quickly add it to the note while the case is still top of mind. Additionally, the AI may find evidence for an undocumented diagnosis based on other information in the chart. The provider can review the AI findings and supporting evidence, make a clinical assessment, and move on to their next task.
While there will always be a need for queries, the powerful combination of AI-powered CAPD and CDI technology on both sides of the workflow can be extremely helpful in mitigating provider query fatigue and improving the relationship between teams.
3. AI amplifies case coverage and impact.
The combination of enhanced productivity and provider engagement can have important implications for the overall outcomes driven by CDI teams.
With the help of AI streamlining the CDS workflow, CDI teams can expand their case coverage without the need for additional resources. As teams have increased bandwidth to review cases, the overall quality of clinical documentation is likely to improve, benefiting both quality and financial outcomes.
The same holds true for CAPD technology, which on its own has been shown to improve important metrics such as case mix index, CC/MCC capture, and observed over expected mortality. As value-based reimbursement models gain traction and quality data becomes increasingly accessible to the public, improving quality outcomes such as these will only continue to gain importance.
4. It encourages ongoing education.
With regular, automatic updates through the cloud, CDSs can rest assured that the latest coding standards and guidelines are incorporated into the AI. Because medical insights and guidelines are constantly evolving, this is essential for CDI teams to stay up to date.
Moreover, some AI-powered CDI tools centralize access to clinical and coding references, so CDSs can further streamline their workflow and access support more easily. For providers using CAPD, continuous exposure to AI-backed documentation guidance can also be extremely helpful in cementing better documentation practices, such as increasing specificity and ensuring that all CCs and MCCs are captured in the patient’s chart.
5. AI enables program tracking and optimization.
The use of analytics and reporting dashboards that often accompany AI tools can further augment CDI effectiveness. CDI leadership can leverage analytics to track everything from query volume to physician response rates and program impact on reimbursement and quality outcomes.
By breaking down multifaceted and cumbersome data into intuitive dashboards and reports, managers can pinpoint areas for improvement and continuous program optimization. With CAPD analytics, physician leaders can gain visibility not only into AI’s impact on key metrics, but also on usage and adoption amongst physicians.
Leaders also have transparency into the most common query types, allowing them to focus on the most pertinent topics for ongoing physician training. Lastly, given physicians are largely attuned to data, analytics can be leveraged to showcase how physicians are performing against their peers, which can help drive increased engagement in the CDI process as well.
Indeed, AI has the power to transform the way CDSs operate and the outcomes that healthcare organizations achieve. While AI technology comes in many forms, CDI prioritization and workflow tools as well as physician facing CAPD solutions are effective ways to drive impact.
Deb Wagner is director of product management for Nuance.
Trusted by 77 percent of U.S. hospitals, Nuance Communications is a technology pioneer with market leadership in conversational AI and ambient intelligence. Here is a link to learn more about AI-powered solutions that can help you achieve your goals.