- PBR Insights
- Posts
- AI Driven Knowledge Curation in Physical Rehabilitation
AI Driven Knowledge Curation in Physical Rehabilitation
Dennis Colon
April 02, 2024
Within the specialized field of Physical Rehabilitation, effective knowledge curation becomes instrumental in discovering and disseminating valuable information. With so much information being published daily on blogs and personal websites by both licensed and unlicensed professionals about topics related to injury and health prevention, it becomes challenging for patients to access quality and accurate information. Now, more than ever, physiotherapist, with direct access emerging in multiple states across the U.S. and the world, need to consider how AI can help leverage our clinical decision-making and patient education efforts. Whether we like it or not, AI is here, and it's here to stay. Intentionally integrating AI into Physical Rehabilitation practices provides the opportunity to transform the patient-to-provider relationship and significantly advance care strategies on both sides of the equation. This article aims to shed light on the significance of knowledge curation in the context of physical rehabilitation and assess the evolution facilitated by AI.
Table of Contents
Defining knowledge curation in Physical Rehabilitation
In the realm of physical therapy and rehabilitation medicine, knowledge curation entails discovering, organizing, and presenting the most pertinent multi-systemic data – spanning neurological, cardiopulmonary, musculoskeletal, pediatrics, geriatrics, oncological, wound care, orthopedic, and sports rehabilitation – to cater to the needs of the audience. It's a way to cut through the noise and deliver the best, most reliable, and valid knowledge to both patients and providers. Developing knowledge curation strategies will not only help clinicians establish trust as a reliable source but also provide reliable information to practitioners and patients seeking guidance. Knowledge curation is the intentional product of integrating patient-provided information (e.g. intake details), practitioner domain expertise, best practice insights and trends across the industry, and ever-evolving research content. Practitioners who lack awareness and access to information in any one of those domains may be less effective in producing outcome-based care strategies for patients.
Limitations of manual knowledge curation
In our collaborative exploration across professional sports, private practice, and direct patient interaction, we've encountered a noteworthy challenge stemming from the diverse array of questions patients bring. These questions often originate from sources such as social media, blogs, posts, and videos. While it's important to note that not all information is inherently negative or erroneous, a significant portion lacks essential context and fails to present a balanced view of specific management approaches.
Consider cryotherapy as an example, particularly prevalent in sports. Many patients today firmly believe that icing is counterproductive to injury recovery. Despite the topic's unclear data and studies suggesting cryotherapy's potential to prevent secondary muscle injuries, with various mechanisms explained here, noteworthy figures like LeBron James - arguably the most durable player in NBA history - continue to utilize icing after every game. Our stance on cryotherapy isn't strictly for or against; rather, to emphasize the critical role of context in its application.
Yet, manually curating this information is a time-consuming process. In a world where a practitioner’s ability to focus full-time on one patient is unrealistic. To address this challenge on a broader scale and to expand one’s knowledge beyond the hands-on experiences one may have, leveraging AI in ethical and intentional ways becomes imperative. The integration of intelligent data mining and knowledge curation capability algorithms allow for the selection and delivery of personalized, relevant data, thereby saving time and effort within the physical medicine and rehabilitation community.
The 5 most noteworthy limitations of manual knowledge curation in physical therapy rehabilitation are the following:
1. Variability in Information Quality: The manual approach to knowledge curation often leads to inconsistencies in the quality and reliability of curated information. This variability, driven by the subjective interpretation and preferences of individual therapists, can result in divergent treatment practices and potentially uneven patient care standards.
2. Challenges with Multilingual Research: The global nature of physical therapy research, encompassing publications in various languages, presents a significant barrier in manual curation. Therapists may find it difficult to access and interpret valuable insights from non-English sources, leading to a potential oversight of critical international research and developments. Additionally, not all practitioners have access to the latest research insights.
3. Limited Integration of Interdisciplinary Knowledge: Manual curation methods may fall short in effectively integrating relevant findings from allied disciplines such as pharmacology, biomechanics, neurology, and psychology. This limitation can hinder the development of comprehensive treatment strategies that fully address the multifaceted needs of patients, especially in instances where the provider is less experienced or has less access to a diverse base of interdisciplinary practitioners.
4. Resource-Intensive Process: The manual process of curating and synthesizing knowledge demands considerable time and effort. This requirement can be particularly challenging for smaller clinics or individual practitioners, who might lack the resources to extensively review current literature, leading to a reliance on possibly outdated or limited information. Additionally, healthcare providers are often constrained by the need to focus on billable time, leaving them with limited capacity to engage in the extensive research, synthesis, and curation of knowledge that is essential for informing patient care strategies. This time constraint further exacerbates the difficulty in staying abreast of the latest developments in physical therapy.
5. Difficulty in Combating Misinformation: In an age where misinformation can proliferate rapidly, especially through unvetted digital channels like blogs and social media, manually discerning and filtering out inaccurate content is increasingly challenging. Physical therapists are required to exercise critical evaluation skills extensively, a task that becomes more daunting considering the vast amount of information that needs to be sifted through.
AI emerges as a potential solution to navigate the vast landscape of information and provide the necessary context for informed decision-making.
Benefits of AI in Knowledge Curation
One of the foremost benefits of integrating AI into knowledge curation within physical therapy is its remarkable ability to elevate both efficiency and scalability. This advantage transcends mere process optimization, extending to the broadening of the information spectrum accessible to therapists. AI enhances this capability by cross-referencing patient-provided information with a wide array of research and other data sources, ensuring a more comprehensive understanding and personalized approach to treatment. By efficiently processing and analyzing extensive datasets, AI enables therapists to quickly access a diverse array of information, ranging from cutting-edge research to tailored patient data. Additionally, AI's capacity to adjust and expand its curation capabilities in response to the dynamic demands of physical therapy ensures that both practitioners and patients consistently receive the most pertinent and current information. Such scalability and efficiency are vital in the rapidly evolving landscape of physical therapy, where access to updated and relevant knowledge is crucial for delivering superior patient care.
The 5 benefits of leveraging AI to enhance patient care in a Physical Rehabilitation environment include the following:
1. Enhancing Decision-Making with AI-Driven Support: Embracing AI-driven decision support systems presents a significant opportunity to enhance knowledge curation in physical therapy. Such systems could effectively curate and analyze patient data alongside other proven sources, providing therapists with tailored, evidence-based recommendations, and enriching their knowledge base for more personalized patient care.
2. AI-Enhanced Patient Engagement and Education: The implementation of AI in creating patient engagement tools and educational content is a promising strategy for knowledge curation. These tools could curate personalized rehabilitation exercises and informative content, fostering a deeper understanding and involvement of patients in their treatment by providing clear traceability to science and trends.
3. Automated Curation of Latest Research with AI: Utilizing AI to automate the curation of literature reviews and analysis represents a major step forward in knowledge management for physical therapists. By efficiently updating practitioners with the latest research and clinical findings, AI can enhance the overall quality and depth of knowledge in the field and solving longstanding issues concerning the use of interdisciplinary literature and practices.
4. Predictive Modeling for Treatment Strategy Optimization: Implementing predictive models offers a unique opportunity for knowledge curation in physical therapy by forecasting patient outcomes and presenting recommended plans for care. This approach can help curate and align treatment strategies with the most effective outcomes, enriching the therapists' knowledge pool with data-driven insights. It is important to recognize the ethical boundary in this use case and ensure a human-in-the-loop strategy when reviewing or accepting AI-developed care strategies.
5. AI in Curating Tailored Professional Development: Leveraging AI for personalized professional development is a key opportunity for knowledge enhancement in physical therapy. AI can curate specific learning resources and courses, tailored to the individual needs and growth areas of therapists, thus broadening their professional knowledge and skills.
Ethical Concerns in AI-Powered Knowledge Curation
AI knowledge curation, despite its transformative potential, grapples with ethical challenges that demand careful consideration. One significant issue is algorithmic bias, wherein the algorithm may unintentionally perpetuate non-useful (or completely made up) information. AI hallucinations are well-documented across a variety of domains, including in legal instances at some of the highest courts. For instance, if historical data on musculoskeletal health predominantly focuses on a specific demographic, the algorithm might generate knowledge that inadvertently neglects other relevant perspectives.
Furthermore, the risk of filter bubbles presents a concern in limiting patients' exposure to diverse viewpoints and perspectives in the realm of musculoskeletal health and human performance. For example, if AI algorithms primarily recommend knowledge aligned with popular beliefs or treatment modalities, patients might miss out on alternative, evidence-based approaches. For this reason, the training data set upon which an AI model is created for the purpose of curating patient care must be carefully analyzed and scrutinized.
The implementation of AI in physical rehabilitation raises data privacy concerns, as accessing sensitive patient data becomes crucial for feeding AI algorithms. For instance, utilizing patient records to personalize a treatment plan and potential referral recommendation may conflict with privacy regulations, necessitating a meticulous approach to data handling and consent mechanisms. In order to solve data privacy concerns, AI systems must ingest only sanitized patient data (removed of personally identifiable information) and its efficacy thereafter clearly examined. Similarly, the AI technology infrastructure must be accredited from a cybersecurity perspective to ensure the safekeeping of patient information, ensuring that it is incapable of data exfiltration and coercion.
Lastly, the powerful capabilities of AI tools, particularly in automating repetitive tasks, prompt concerns about workforce displacement. This applies not only to physiotherapists but also extends to physical therapy assistants and front desk personnel at healthcare facilities. For example, if AI efficiently handles appointment scheduling and administrative tasks, it may impact the job roles traditionally carried out by human staff, raising questions about job security and adapting to evolving healthcare workflows. Due to the previously discussed ethical concerns with AI, it is important to recognize the persistent criticality of having a human-in-the-loop on healthcare activities, ranging from those performed by the provider and the supporting staff. Sparking this critical conversation is the motivation for this article today – how do domain-competent AI models change an industry?
While the human element remains indispensable in healthcare, a nuanced strategy for the micro and macro-scale implementation of AI becomes imperative.
Striking a balance between harnessing the benefits of AI and addressing ethical considerations is crucial for a comprehensive and effective integration in the field physical therapy.
Take Home Points
Effective knowledge curation in physical therapy is crucial for disseminating valuable information, especially in the era of information overload from blogs and personal websites.
Physiotherapists, with direct access emerging globally, must consider integrating AI into rehabilitation practices for clinical decision-making and patient education.
Knowledge curation involves discovering, organizing, and presenting multi-systemic data across various specialties, establishing trust and reliability for both patients and practitioners.
Manual knowledge curation faces limitations such as variability in information quality, challenges with multilingual research, limited integration of interdisciplinary knowledge, resource-intensive processes, and difficulty combating misinformation.
AI offers benefits like enhanced efficiency, scalability, and personalized information delivery, addressing challenges in manual processes, and contributing to improved patient care in physical rehabilitation.
Ethical concerns in AI-powered knowledge curation include algorithmic bias, the risk of filter bubbles, data privacy issues, and potential workforce displacement, requiring a nuanced implementation strategy in healthcare.
References:
