AI Can Review Medical Records. But Can It Understand What Matters in Your Case?
Artificial intelligence is changing the way attorneys research, prepare, and manage cases. From summarizing documents to identifying information within thousands of pages of records, AI offers opportunities to improve efficiency and reduce administrative workload.
But when litigation involves complicated medical issues, an important question arises:
Can artificial intelligence recognize the difference between what a medical record says and what that information actually means?
The distinction matters. In medically complex litigation, relying on an inaccurate interpretation can affect case evaluation, discovery, expert preparation, and litigation strategy.
When AI Gets It Wrong: A Lesson from the Courtroom
The legal profession has already witnessed the consequences of relying on AI-generated information without independent verification.
In the 2023 federal case Mata v. Avianca, Inc., attorneys submitted legal research containing nonexistent judicial decisions generated by ChatGPT. The citations appeared legitimate but could not be substantiated. The court ultimately imposed monetary sanctions.
The underlying problem was not simply that artificial intelligence produced incorrect information. It was that the information was relied upon without adequate verification.
The same concern extends beyond legal citations.
If AI can produce a convincing reference to a case that does not exist, what happens when it produces a convincing interpretation of a medical record that is clinically incorrect?
An inaccurate legal citation may be identified through legal research. An inaccurate clinical interpretation may require specialized medical knowledge to recognize.
Medical Records Require More Than Summarization
Medical records are not simply collections of facts arranged chronologically.
They contain clinical observations, diagnostic findings, treatment decisions, medication orders, changes in patient condition, and documentation created by multiple healthcare professionals.
Understanding those records requires more than locating keywords or organizing information by date.
Consider a hypothetical patient who undergoes surgery and subsequently develops an elevated heart rate, decreasing blood pressure, reduced urine output, and changes in mental status.
An AI-generated summary may accurately identify each of these findings.
But identifying individual findings is not the same as evaluating their clinical significance.
A qualified clinical reviewer may recognize that the combination and progression of these findings warrants closer examination for possible deterioration, including consideration of the patient's underlying condition, medications, treatment, and timing.
The reviewer must also determine what the records establish, what remains uncertain, and whether additional information is needed.
A summary tells an attorney what was documented. Clinical analysis helps explain why the documentation may matter.
Five Risks of Relying Exclusively on AI for Medical Case Review
1. Missing the Significance of Subtle Clinical Changes
Important developments may occur across multiple nursing notes, vital-sign records, laboratory results, medication administration records, and provider documentation.
A clinical reviewer can examine how these findings relate to one another over time, rather than treating them as isolated entries.
2. Misinterpreting Medical Terminology or Abbreviations
The meaning of a medical term can depend on the specialty, clinical setting, and surrounding documentation.
An AI system may generate a plausible explanation while overlooking the context necessary for an accurate interpretation.
3. Confusing Documentation with Clinical Appropriateness
A medical record may confirm that an intervention occurred. That fact alone does not establish whether the intervention was timely, indicated, appropriately performed, or consistent with the circumstances.
Evaluating these questions requires consideration of relevant clinical standards, available information, and the patient's condition.
4. Overlooking What Is Missing from the Record
Sometimes the absence of expected documentation raises important questions.
A clinical reviewer may identify gaps in assessments, monitoring, communications, or follow-up documentation that warrant further investigation.
However, missing documentation does not, by itself, prove that care was not provided. That distinction is essential to an objective evaluation.
5. Presenting Uncertain Conclusions with Unwarranted Confidence
Generative AI can produce polished, authoritative-sounding statements even when the underlying interpretation is incomplete or incorrect.
In litigation, a persuasive explanation is not necessarily a medically supportable one.
Attorneys need conclusions that can be traced to reliable records, applicable clinical literature, and appropriate professional judgment.
What AI Can Do Well
Artificial intelligence does have a place in modern legal practice.
Depending on the tool and appropriate safeguards, it may assist with:
• Organizing large volumes of documentation
• Extracting dates and identifying recurring terms
• Creating preliminary timelines for verification
• Locating potentially relevant documents
• Supporting administrative tasks and research workflows
These capabilities may save time, but the outputs must be checked against the underlying source material.
Confidentiality is another consideration. Attorneys must evaluate how any technology handles sensitive client information and protected medical data before using it.
The goal is not to reject technology.
The goal is to use technology without surrendering professional judgment.
Where a Legal Nurse Consultant Adds Value
A Legal Nurse Consultant brings clinical training and healthcare experience to the interpretation of medically complex cases.
An experienced nurse reviewer can assist attorneys in understanding the significance of clinical findings, identifying questions for further investigation, developing medical chronologies, researching relevant standards of care, and preparing for discussions with medical experts.
This role is particularly valuable when determining which details deserve additional attention and which conclusions cannot yet be supported.
A Legal Nurse Consultant does not replace the attorney's legal judgment or the testimony of appropriately qualified expert witnesses. Instead, the consultant provides a clinical perspective that helps the legal team evaluate and prepare medically complex matters.
The Bottom Line: Efficiency Is Not the Same as Expertise
Artificial intelligence can accelerate the review of information, but speed alone does not establish accuracy.
When a case turns on medical decisions, patient deterioration, clinical documentation, or standards of care, attorneys need more than an automated summary.
They need a reliable interpretation of the medical evidence, grounded in clinical experience and supported by the records.
AI can help find the information. Clinical expertise helps determine what the information means.
At Know More Legal Nurse Consulting, we combine more than 20 years of clinical nursing experience with a careful, objective approach to medical record review and litigation support.
Our goal is to help attorneys understand the medical issues within their cases, identify areas requiring further investigation, and make more informed decisions.
Have a medically complex case that needs a clinical perspective?
Contact Know More Legal Nurse Consulting to discuss how our services can support your practice.
Craig Chittenden, RN, CLNC®
(661) 699-7386
Sources and Further Reading
This article is provided for general educational purposes only. It does not constitute legal advice, establish the applicable standard of care in any particular case, or replace case-specific professional evaluation.
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