AI medical chronologies efficiently organize and analyze medical records, identifying key events to support accurate case evaluations.
Sifting through medical records is no easy task and requires a great deal of expertise and effort. However, many personal injury lawyers have to do it every day.
Preparing accurate and precise medical chronologies is vital, but it also comes with logistical challenges. While there are services to help prepare these records, they can be expensive, especially when a practice is just starting out.
Luckily, technology continues to evolve to help personal injury firms of any size prepare medical chronologies efficiently and accurately. Artificial intelligence (AI) tools are the latest tech innovation and are being adopted as the next stage of law firm automation—but are they a good fit for your personal injury practice?
In this article, we’ll cover how AI is being used to help manage medical chronologies, the potential benefits, the limitations, the ethical considerations, and what you should consider when using AI in your firm.
A medical chronology breaks down a patient’s medical records and the health impact, summarizing important points in an easy-to-follow timeline. That includes:
While the final results are extremely useful in the courtroom, assembling them can be challenging. There are several key challenges lawyers face when managing medical chronologies.
Creating a patient’s medical records summary involves sifting through an incredible amount of data. Additionally, no two doctors take notes the same way; they often use different systems, and there are various codes to interpret for insurance. That can mean you are left with a big job ahead of you.
Centralizing all of your documents in one database makes the job a bit easier, but you still have to comb through the data to pull out the records that are pertinent to your case.
Creating an accurate medical records summary is a time-consuming process—especially if you are using manual processes. Without a centralized document hub or electronic database to filter and search for relevant records, you or your staff could spend hours sifting through potentially years worth of documents.
Obtaining a medical chronology is time-sensitive—you need to get the facts as quickly as possible to capture relevant details. However, with the amount of information you need to parse, getting speedy results can be at odds with getting accurate results.
Reading medical records requires an expert's eye. You need to understand the information and translate it into layman’s terms as well.
If the facts in your chronology aren’t accurate, it can be detrimental to your case. Even an innocent error can have a major impact on your client.
Accurate medical chronologies require hiring and training expert in-house staff. These staff members are invaluable but managing that workload may require even more hiring and training as your business grows.
Alternatively, you can outsource the task to experts, but these services can be costly. . Either way, you are left with higher operating expenses that can impact your bottom line.
Medical chronologies are a vital tool for building a winning claims case. They allow you to present a concise record of an incident and act as evidence to present to a judge or insurers. A good medical summary can help you win a case, but it must be unbiased and accurate.
AI medical chronologies seek to create a medical summary in a fraction of the time. Using the latest generative AI models like ChatGPT, these AI algorithms comb through hundreds of pages of documents to produce general summaries and chronologies of key events.
AI models are generally trained to identify different categories within the various documents, such as diagnoses, medical events, medications, treatments, and more.
Across multiple industries, AI is finding ways to streamline operations, especially those that involve a great deal of data. That’s why it has been such a popular topic of conversation.
Leveraging AI medical chronologies comes with a few distinct benefits.
An AI can automate the organization and summarization of medical records, massively boosting your lawyers’ productivity. Even if you don’t use AI to summarize the records themselves, the organizational tools alone are potentially transformative for small to mid-sized personal injury firms.
Once an AI has analyzed a client’s medical records, you can also ask it questions in plain language to retrieve information for case preparation. For instance, you could ask an AI to do things like:
When it provides an answer, you can also ask it to show you the relevant document(s) to check for accuracy and find additional details.
Analyzing medical records can be confusing, even for experts. An AI can take a bird’s eye view of a diverse set of medical records at once, consistently extracting information and documenting its findings.
Using AI enables lawyers to make an in-depth analysis of medical histories, key events, diagnoses, and treatments. Additionally, AI tools can spot small pieces of data that would be easy to miss when reviewing documents manually, ensuring higher accuracy.
A concise and well-organized AI medical records summary gives lawyers, healthcare providers, and insurance companies a clear view of events that supports informed decision-making.
AI is also exceptionally good at identifying patterns, correlations, and critical details within medical data, giving concerned parties a more detailed view of events.
Once a medical summary is prepared by an AI, you can quickly pull out relevant information from it for use in case management and strategy. You can ask AI questions, and it will query the entirety of the medical record for answers, not just the summary, so you can make adjustments and glean new information.
Having an unbiased and structured view of medical data also strengthens legal arguments and makes it easier to collaborate with medical experts when presenting medical evidence.
AI may sound too good to be true—and in some cases, it is.
As advanced as these tools are, today’s AI is unlike the ultra-intelligent virtual beings we see in the movies. Instead, it’s better to think of them as extremely sophisticated tools that your experts can use to speed up their summary process. However, it will not replace your human staff anytime soon.
While AI is incredibly good at some things, it is not foolproof, and it is extremely important to be aware of those limitations to use it effectively and ethically.
AI algorithms do their best to summarize information, but if the information it is being trained on contains biases or can’t find an answer, it can lead to what is known as “AI hallucinations.”
Generative AI works by identifying and reproducing patterns in data. If those patterns are incorrect or have gaps, it may incorrectly predict an outcome. In other words, there’s a chance that it will produce inaccurate conclusions. Also, an AI is not a person; it lacks real-world context to ground its assumptions in common sense.
In other words, even if a summary looks good at first glance, make sure to read through it extensively to check it for accuracy. Also, ask the AI to cite its sources within the medical data to ensure you understand how it’s drawn its conclusions.
As many of us know, doctors sometimes use their own language and terminology that wouldn’t make sense outside of the medical field. Unfortunately, AI can struggle to interpret it as well.
This is particularly true in the case of nursing intervention. Nursing intervention includes minor (but important) aspects of patient care, such as dressing wounds, measuring vital signs, talking with patients, or giving medication.
Clinical notes may be hard to parse, causing an AI to provide an incomplete summary of nursing interventions or leave them out entirely.
While some medical records may seem sterile or clinical, they still contain a great deal of subtlety and nuance, which can be difficult for AI to understand. AI may also lack the ability to put certain information in context.
For example, two doctors may provide an opinion on a patient’s injuries. Even if they both generally agree on the facts, the wording may differ enough that the AI incorrectly interprets the doctors as fundamentally disagreeing.
An AI treats all data equally, for better or for worse. When used for medical summaries, an AI will review all of a patient’s data, creating ethical concerns that it may access and use records that are not relevant.
Depending on how the AI is trained, it may exhibit biases that would violate ethical rules surrounding fairness and equity. Additionally, an AI is considered a subcontractor of a business associate under HIPAA rules, making any privacy breach subject to the law, whether intended or not.
If you’re considering using AI in your practice, it’s important to use legal-specific tools that are designed with regulatory and ethical considerations in mind.
Generating medical summaries is far from the only use of AI in the legal industry. For example, many other forms of automation and legal AI tools are being employed in personal injury firms to improve efficiency, decrease costs, and improve client satisfaction.
AI can assist in drafting complex legal documents like briefs, contracts, and summaries. You can even give an AI an example of your writing style to use as a baseline.
However, if you are not using an AI to create the drafts themselves, it’s still very useful as an editing tool. AI can also provide suggested edits for readability, and legal-specific AI tools can even run citation checks by looking through relevant documents.
AI can be used to streamline the discovery process by efficiently processing, organizing, and analyzing many electronic documents at once. A legal-specific AI tool can comb documents and produce summaries, allowing you to quickly find the relevant information for your case.
Once an AI has organized documents into a database, you can then search using keywords or in plain language. When an AI provides answers or summaries, it can also link directly to the relevant documents so you can check its accuracy.
Personal injury lawyers build winning cases by citing relevant case law and conducting extensive legal research. However, combing through sources using keyword research alone can be hit-and-miss.
Using an AI research assistant allows you to search for specific information across a much wider range of sources. The benefit of AI-assisted search is that they are designed to understand the intention behind a search instead of trying to exactly match search terms alone.
When used correctly, AI can transform how personal law firms operate. Along with smart law firm automation, AI is helping firms of all sizes stay competitive and better serve their clients’ needs.
CASEpeer is dedicated to furthering innovation for personal injury firms by thoughtfully using the latest tech innovations, like CASEpeer IQ. With a centralized source of data with the ability to quickly search and sort relevant information, you’ll significantly cut down the effort it takes to create accurate medical chronologies.
CASEpeer is actively advancing innovation for personal injury firms through the development of CASEpeer IQ, a suite of generative AI tools integrated into its practice management software. Designed to leverage a centralized source of data, CASEpeer IQ technology aims to simplify the process of searching and sorting relevant information, significantly reducing the effort required to create accurate medical chronologies.
CASEpeer IQ will also help you achieve better client outcomes with features like:
Join the waitlist for CASEpeer IQ today and be among the first personal injury firms to transform how your firm handles case management!
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