Utilizing AI in Medical Record Review and Summaries

Over the years, basic AI has become an integral part of our daily lives. Algorithms and data learning by software is a part of life: we use AI to search the internet, ask our phones for directions, speak to text, entertainment streaming apps, image recognition to unlock a device, ride share apps, chat bots, email filtering, and much more. AI has revolutionized the way we function in daily life. By integrating basic AI tools, law firms not only increase their operational efficiency but also enhance the accuracy of their work. Algorithms do not have human bias, fatigue, and have far less of an error rate than humans.

Before the introduction of case management software platforms, electronic document storage, calendaring software, and similar tools, law firms were only operating at a fraction of their potential, and they spent an excessive amount of time just trying to keep their cases on track. Technology has been a game-changer for the legal profession, revolutionizing the way things are done today. Moreover, all of these systems make use of some level of AI. The use of AI to summarize medical records marks another remarkable shift towards efficiency within the legal profession.

Basic AI does not replace the need for lawyers but rather enhances their capabilities by handling routine and time-consuming tasks. For example, AI-powered software can quickly review thousands of documents relevant to a case, reducing the workload on legal staff. This allows lawyers to focus on more strategic aspects of case preparation and client communication. This level of support is achieved through Natural Language Processing (NLP) and machine learning, enabling the software to understand human language and learn from the data it analyzes.

When handling injury cases, the medical records play a crucial role as they provide essential evidence. It's vital to fully comprehend the nature of the injury, treatment, prognosis, and various aspects of pain and suffering to effectively present the case. Reviewing and interpreting medical records for case preparation can be quite challenging and requires meticulous attention to detail. This is where artificial intelligence steps in: leveraging AI for the summarization of medical records offers a sophisticated solution to a traditionally labor-intensive process. AI systems, powered by sophisticated algorithms, are capable of deciphering complex medical terminology and extracting critical information from dense documents. A well-trained AI system can effectively identify and extract key data points such as diagnoses, treatment histories, and prognoses, which are essential for building a strong case.

One of the standout benefits of employing AI in the preparation of medical record summaries is the significant reduction in errors. Traditional methods of data extraction and analysis, heavily reliant on manual labor, are inherently prone to human mistakes due to fatigue, oversight, or simple misinterpretation of complex medical jargon. With trained AI algorithms, one can expect consistency, precision, and speed that human reviewers can find challenging to match over long periods.

Not all AI is The Same. You must be aware of the inadequacies of AI that is not specifically trained to review medical and billing records. General AI that simply reads text does not encompass necessary components of the records such as the medical coding intertwined in an electronic medical record or scanned images. Look for AI that can interpret medical coding and can read text within a scanned image such as ChartSquad’s AI. Further, AI analysis is only as good as the records it is provided. Incomplete medical records will result in flawed or incomplete AI summaries. You must be sure the entire Designated Record Set is provided. Utilizing a service such as ChartSquad to ensure the record set is complete prior to feeding the data into the AI will reduce the risk of an incomplete medical record summary.  In addition, ChartSquad’s AI will identify missing information or incomplete data. 

Ethical Concerns

Some find it difficult to stomach the idea that technology can compete with years of experience and attention to detail in a task that has traditionally required human legal expertise. Lawyers rely on medical experts to explain the medical data and rely on their legal expertise to present this explanation to the opposing side and/or jury. Some may feel it would be unethical to rely on an AI system to handle such a paramount aspect of the case.

Accuracy

Studies show that AI record review is far more accurate and comprehensive than human medical record review. For example, ChartSquad’s AI is 98% accurate whereas human error rates span from 20% -75%.  Now, I am not suggesting that anyone rely on AI 100%. You must review what the system has provided, ensure it is accurate and complete, and you must be able to digest the information, or you will not be prepared to present the case. 

In contrast, some are hesitant to trust AI replacing critical thinking of a human. As Pamela Bixler, owner of Bixler Services, and a paralegal with over 15 years in civil litigation states: “Yes, humans make mistakes too but in comparison to AI, the benefits outweigh the risk. A human can offer a high level of scrutiny and creativity, critical thinking to cross-check records, and use their professional judgment in the field to assess the importance of the data being summarized in relation to the case. And, case law has demonstrated that this process is both protected and highly valued by the courts because it employs the concepts of competence and diligence.” Again, AI is as good as the information that is fed to it. In Bixler’s professional opinion, “If AI is working with fragmented data sources, lacks contextual understanding, or uses narrowly focused algorithms, it can struggle to integrate information and produce a reliable chronology. For attorneys in the personal injury field and insurance adjusters, relying on an incomplete chronology is as problematic as having a client who is a poor historian.”

Time

AI summaries can be completed in minutes, whereas the human record review takes hours, even days to complete. Medical practitioners spend an average of 20 hours reviewing a typical 1,138-page patient record, while legal staff take an average of 40 hours. One of the biggest complaints lawyers hear from their clients is the TIME the case is taking. These people need money, medical care, and most importantly, they need to move on with their lives. Dragging a case out by NOT using technology would be the greater ethical concern here. 

Cost

Typically, a lawyer will pass the cost of a medical record summary to the client as a case cost. As fiduciaries, we must be aware of our obligation to our clients in how we spend their money. A nurse paralegal or RN medical record summary costs on average 85 cents per page. So for 1,000 pages of records, the cost is $850.00. The cost greatly increases with physician or doctor reviews. ChartSquad AI summaries are 35 cents per page ($350 for 1,000 pages).

While I will always believe systems make for optimal operation in a law firm, not all cases are complex and may not require a full medical record summary, or even a chronology. Utilizing this technology should be determined on a case-by-case basis. In addition, you must be cautious with those AI systems that are not adequately trained to handle medical records. Be sure you ask the right questions when deciding what platform you incorporate into your practice:  simple Adobe can read text. Medical record summaries are not that simple. Make sure you are asking for samples and review the capabilities of the AI program. Qualified and well-trained AI is an asset. There will come a time when every firm is using AI in it’s practice to better understand and present their client’s injuries. Fear of this progression will only hold your practice in the past. It is time to embrace AI and discover the possibilities!