The next generation of CDI is here: Advanced technologies enable automated case prioritization, code sequencing and more

Diagnosis sequencing is key to improving hospital ratings and rankings by industry groups like U.S. News & World Report, Leapfrog Group and Vizient. Manual processes for identifying high value cases, ensuring diagnosis integrity and sequencing diagnosis codes, however, are time consuming for clinical documentation integrity (CDI) and coding (HIM) teams.

Becker's Hospital Review recently spoke with Shawn Dickinson, CDI product content specialist at 3M HIS, about advanced technologies that can capture the complete clinical picture of patients through automated prioritization of cases, as well as coding rules and sequencing.

Note: Responses edited for length and clarity.

Question: With the current budget and staffing challenges facing hospitals, how can CDI and health information management (HIM) teams drive greater efficiency, quality ratings and rankings?

Shawn Dickinson: Health care organizations continue to see decreases in available, qualified candidates to fill open positions in documentation integrity programs. They also recognize that existing and potential patients have greater visibility into institutions' ratings and rankings. Negative ratings can translate into reduced patient populations.

In response, CDI specialists and HIM coding professionals can implement systems that leverage technology powered by artificial intelligence (AI). These solutions eliminate the need for staff to complete certain basic tasks and enable teams to focus on more complex cases.

The 3M™  360 Encompass™ System assists with case prioritization. It uses a scoring system to help reviewers zero-in on high impact cases by automating the selection process. Recently, 3M has introduced advanced code sequencing which incorporates quality measures used for ratings, such as patient safety indicators (PSIs). This functionality can help documentation specialists and HIM professionals optimize their reviews and coding sessions. It also allows new, less experienced staff members to join and collaborate with case selections and sequencing.

Q: As CDI programs expand in more significant ways to improve documentation and coding quality, what is one change you see CDI teams making to improve quality scores?

SD: Over the years, clinical documentation specialists have started working more closely with quality and HIM departments to understand a hospital's potential for quality improvement. Historically, quality departments and HIM departments have worked together in a retrospective process, reviewing cases that were flagged with quality indicators on that diagnosis and also looking at the present on admission (POA) statuses at the time of final coding.

Today, many CDI specialists have expanded roles and can join collaborative efforts with coding and quality to improve those outcomes and scores. They can review and query the providers when needed, both concurrently and retrospectively. When it comes to quality outcomes, CDI specialists can identify potential documentation clarification opportunities and address them with physicians before patients are discharged.

Organizations are also expanding the role HIM plays by looking at potential opportunities for documentation earlier and implementing concurrent coding. Concurrent coding is nothing new, but it has been expanded and reworked so it is more relevant and complements the work of CDI specialists. Successful programs usually have one platform where the CDI, HIM and quality teams can all collaborate on prioritized cases seamlessly together.

Q: How can technology help remove the guesswork from identifying cases with the biggest impact on quality?

SD: It's essential to have a customizable system that targets important metrics like DRG codes, length of stay outliers and conditions tracked by proprietary quality methodologies. Historically, documentation specialists have had to manually review cases. This is a time consuming process, and many cases are simple without a need to improve documentation.

Today, AI technology allows specialists to see key case information before initiating the overview process. This enables them to focus on the most important cases. Concurrent review shouldn't wait until after patients are discharged and the final conversion of diagnostic statements into ICD-10 codes occurs.

Coding professionals play a big role in making sure that work done concurrently by CDI specialists is reflected in the final code. They are tasked with ensuring that the code set is accurate and reflects the documentation in the chart. As part of the coding process, they must remember the coding guidelines, as well as the facility's specific sequencing rules and other organizational requirements. This is not only time consuming, but it can also be stressful for employees who are trying to meet their production goals. There isn't a lot of time to focus on the quality implications of diagnosis codes.

3M's AI technology supports advanced code sequencing, which incorporates quality measures into the code sequencing logic. Medicare, for example, only accepts 25 diagnoses on a claim per visit. That's prime real estate for coders and CDI organizations to ensure they are reflecting the patient's outcome accurately. With advanced code sequencing, we make sure quality metrics are within the top 25 codes. Automated processes ensure other focus codes are reflected in the outcomes with advanced code sequencing. This reduces the effort of manually moving individual codes.

Q: Is there a correlation between improving quality ratings and prioritization of cases for CDI review?

SD: I believe there is a correlation, but it's not just with documentation specialists and prioritization alone. Enhancing the visibility of cases through prioritization allows review by specialists and concurrent coders to ensure documentation is clear and concise through provider clarifications. Once conditions have been clearly documented, the software should also sequence conditions that are converted into ICD-10 diagnoses and procedure codes in a meaningful way. That tells the patient story and reflects an accurate financial profiling and quality outcome. As documentation integrity programs expand and take on a more prominent role in quality and integrity, manual diagnosis and code sequencing have increased. Products with sequencing technology that incorporate quality metrics reduce the need for manual processes and also reduce human error.

Q: What does AI need to do to make meaningful contributions to CDI?

SD: The simple answer is that AI must continue to adapt to an ever-changing market and industry standards, while providing ease of use and desired outcomes for the end users and also for health care organizations. As AI advances and more products are released, the role of a robust documentation integrity program can expand as well. Increasing the visibility of cases and sequencing the diagnoses in a meaningful way reduces the need for human touch on basic processes. This allows users to focus more on complex cases.

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