Over the past few years, Artificial Intelligence (AI) has managed to become one, if not, the most powerful technological tool for Healthcare organizations pursuing efficiency and competitive advantage. As a result, certain areas such as Clinical Documentation Improvement(CDI), if chosen not to expand its reach into new areas of expertise, expect to be severely affected by the transformational force that AI is poised to become in Healthcare.
As healthcare organizations continue to use increasingly complex health data, the traditional CDI finds itself at a crossroads to keep up with ensuring that these data be captured and appropriately documented.
Concurrently, the physician’s buy-in is getting more complicated since some physicians feel that CDI programs are becoming annoyingly demanding, add more work, and serve only the hospitals. Across the country, the frustrations grow the same in every program:
- Increasing documentation requirements for physicians consume time away from patient care
- Severity of illness and complexity of care are not adequately documented, and often missed by CDS.
- Increasing of Denials claims
- Post-discharge queries from CDS are ineffective, costly, and disruptive.
-Quality improvement and revenue opportunities are often missed
To address these challenges, Healthcare organizations have implemented the use of computer-assisted coding (CAC) programs integrated with machine learning algorithms. 44% of healthcare organizations in the US are already using artificial intelligence (AI) in one form or another. It helps improve productivity and accuracy, suggest queries and codes, streamline workflow, generate automated queries, and provide real-time feedback to the physician about inaccurate documentation while the note is being created.
The results are quick and spectacular. According to a Black Book survey, on average hospitals have seen $1.6 million in financial improvements stemming from average case-mix improvements due to AI-driven CDI initiatives between Q3 2018 to Q3 2019. Furthermore, ninety percent of hospitals said they have noticed documentation quality improvements and increases in the case-mix index within just six months.
On the other hand, as these AI platforms system gain experience, their ability to learn and act alone without CDS assistance becomes more threatening to the industry. They are leading to better precision, greater efficiency and outcomes; thereby, the relevance of a CDI program is increasingly fading away.
Now, what is next for the CDI Industry?
As traditional CDI works are gradually becoming automated, we need to be honest about it. We should revisit the industry’s mission, as we know it. Indeed, in the very near future, do you think healthcare organizations’ leadership will still consider paying for an expensive CDI program to achieve the following mission statement?
“Ensure complete documentation of the findings, diagnosis, and treatment in the patient health record to reflect the severity of illness and capture accurate codes and statistical data for research, reimbursement, and clinical measures.” (AHIMA)
Cerner, Epic, and 3M are certainly working hard to make sure they don’t need to.
Revenue Integrity departments need to eventually expand the reach of their CDI programs into new areas of expertise. We should use CDI-based research skills and in-house data analytics to demonstrate the continued value of the industry. Evaluation of the impact of changes in clinical definitions using our in-house Data; implement other cross-departmental collaboration programs, especially with Quality Team, to help address length of stay issues, and expected mortality improvement using our encoder data. Data analytics and Data transparency advocacy can be and should be the foundation of future CDI programs.
Some institutions have already started re-shaping certain branches of their program in data collection, education, research, cross-functional works collaboration with other departments. They collect, clean, organize, and communicate data. However, I am afraid that they are missing the step where miracles can and will happen: “Analyzing the data for prediction and anticipation purposes.”
The CDI Specialist will undoubtedly need training and new skillsets adjustable to this eventual reality. But the bottom line is, with the pool of talents, transferable skills, and clinical expertise in the industry, we may already have the necessary weapons to act towards fulfilling different missions within our organizations and redefine the industry for decades to come.
MJ
