How traumatic brain injury lawyers are using AI: Implications for rehab clinicians

There are two types of brain injury professional: those that embrace Artificial Intelligence and those that will be left behind

Warren Collins, Catastrophic Injuries Lawyer at Penningtons Manches Cooper LLP takes a peak at AI

The intersection of artificial intelligence and traumatic brain injury (TBI) litigation is rapidly evolving, creating new opportunities and challenges that directly impact the work of rehabilitation clinicians.

As AI tools become increasingly sophisticated, TBI solicitors and barristers are leveraging these technologies to build stronger cases, analyse complex medical data, and ultimately secure better outcomes for their clients.

Understanding how legal professionals are incorporating AI into their practice can help rehabilitation professionals better prepare for their role in legal proceedings and ensure their clinical documentation supports the best possible outcomes for patients.

AI-Powered Medical Record Analysis

One of the most significant applications of AI in TBI litigation involves the analysis of voluminous medical records.

TBI cases often generate thousands of pages of medical documentation spanning A&E visits, hospital admissions, rehabilitation records, neuropsychological evaluations, and ongoing treatment notes.

Traditionally, legal teams would spend countless hours manually reviewing these records to identify key information, inconsistencies, or gaps in care.

AI-powered document review systems can now process these extensive medical records in a fraction of the time, identifying patterns, flagging important clinical findings, and creating comprehensive timelines of care.

These systems use natural language processing to extract relevant information about cognitive assessments, functional improvements, medication changes, and therapy progress.

For rehabilitation clinicians, this means that every detail documented in clinical notes may be scrutinised and analysed by AI systems, emphasising the critical importance of thorough, accurate, and consistent documentation.

Advanced AI tools can also identify subtle correlations between different aspects of care that might be missed by human reviewers.

For example, an AI system might correlate specific therapy interventions with functional improvements, or identify patterns in cognitive testing scores that support or contradict claimed disabilities.

This capability allows solicitors to present more compelling arguments about the effectiveness of rehabilitation interventions and the ongoing needs of their clients.

Predictive Analytics for Case Outcomes

TBI solicitors are increasingly using AI-driven predictive analytics to assess case viability and potential compensation values.

These systems analyse historical case data, including injury severity indicators, treatment outcomes, demographic factors, and legal precedents to predict likely case outcomes.

Machine learning algorithms can process information about Glasgow Coma Scale scores, length of coma, post-traumatic amnesia duration, neuroimaging findings, and functional assessment results to estimate potential damages.

This predictive capability has significant implications for rehabilitation clinicians. Solicitors may use AI insights to determine which aspects of a patient’s rehabilitation needs to emphasise in their legal strategy.

For instance, if AI analysis suggests that cognitive rehabilitation outcomes are strong predictors of compensation values in similar cases, legal teams may place greater emphasis on neuropsychological evaluations and cognitive therapy progress notes.

Rehabilitation professionals should be aware that their clinical assessments and progress documentation may be weighted differently based on these AI-driven insights.

Enhanced Expert Witness Preparation

AI is revolutionising how TBI solicitors prepare expert witnesses, including rehabilitation professionals who may be called to give evidence about treatment needs, prognosis, and functional outcomes.

AI systems can analyse an expert’s previous reports and court testimony, identify their areas of expertise, and even predict how they might respond to specific lines of questioning based on their published research and past statements.

For rehabilitation clinicians who serve as expert witnesses, AI tools can help legal teams prepare more targeted questions that highlight the expert’s specific knowledge and experience.

These systems can also identify potential weaknesses in expert testimony by analysing consistency across different cases or comparing statements to current literature.

This means that rehabilitation experts must be more prepared than ever to defend their clinical opinions with current, evidence-based research and maintain consistency in their professional statements across different legal proceedings.

Neuroimaging and Diagnostic Analysis

Advanced AI applications in TBI litigation include sophisticated analysis of neuroimaging studies and diagnostic test results.

Machine learning algorithms can now detect subtle abnormalities in brain scans that might be missed by traditional radiological review, potentially identifying structural damage that supports claims of cognitive impairment or functional limitation.

Some AI systems can correlate neuroimaging findings with functional outcomes, helping solicitors demonstrate the relationship between observed brain damage and specific deficits in activities of daily living, work capacity, or cognitive function.

This technology can also identify patterns in diagnostic testing that support or challenge claims about the severity of cognitive impairment or the likelihood of recovery.

For rehabilitation clinicians, this development underscores the importance of comprehensive diagnostic evaluation and the need to understand the relationship between neuroimaging findings and functional outcomes.

Clinicians should be prepared to explain how imaging findings correlate with observed functional limitations and how these relationships inform treatment planning and prognosis.

Document Generation and Preparation of Court Pleadings

AI is also transforming the actual writing and preparation of legal documents in TBI cases.

Natural language generation systems can draft initial versions of legal pleadings, summarise medical records, and even prepare questions for examination of witnesses based on analysis of clinical documentation.

These tools can synthesise information from multiple sources to create comprehensive arguments about injury severity, treatment needs, and long-term prognosis.

Whilst AI-generated documents still require human review and refinement, they allow legal teams to produce more comprehensive and well-researched materials in less time.

This capability means that rehabilitation clinicians may find their documentation and assessments incorporated into legal arguments in ways they might not have anticipated, further emphasising the need for clear, professional, and defensible clinical records.

Implications for Rehabilitation Practice

The increasing use of AI in TBI litigation has several important implications for rehabilitation clinicians.

First, the quality and comprehensiveness of clinical documentation becomes even more critical, as AI systems will analyse every aspect of the medical record. Clinicians should ensure their notes clearly describe functional limitations, treatment goals, progress towards those goals, and long-term prognosis.

Second, rehabilitation professionals should stay current with legal developments in TBI litigation and understand how their clinical work may be interpreted in legal contexts.

This includes understanding the difference between clinical improvement and legal concepts of recovery or achieving maximum medical improvement.

Finally, clinicians who may serve as expert witnesses should be prepared for more sophisticated legal preparation processes and should maintain consistent, evidence-based opinions that can withstand AI-assisted scrutiny of their professional statements and testimony.

The integration of AI into TBI legal practice represents both an opportunity and a responsibility for rehabilitation clinicians to maintain the highest standards of clinical practice and documentation whilst serving the best interests of their patients in both clinical and legal contexts.

AI is not replacing lawyers or clinicians – but it is empowering those who know how to use it wisely and ethically.

About Warren Collins

Warren Collins is a solicitor-advocate at Penningtons Manches Cooper LLP in London.

He has been practising catastrophic personal injury litigation for more than 30 years with a special interest in traumatic brain injuries and spinal cord injuries cases for Claimants.

He is Chief Assessor to the Law Society’s Personal Injury Accreditation Scheme and also a regular writer and speaker on innovative handling of litigation.

He has a special expertise in transatlantic injury litigation.

He is a leading member of the American Association for Justice where he serves as co-chair of the International Practice Section and is the only UK solicitor member of the US based National Trial Lawyers Top 100. He can be reached at warren.collins@penningtonslaw.com