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AI as a “force multiplier” in building capacity to assist amputees?

  • Nicholas Mellor
  • Jun 19, 2023
  • 4 min read

Updated: Apr 28

Amputees often face a long and unpredictable journey from stabilisation to rehabilitation. This is never more so than at the start of the journey, when the medical priority may be to keep them alive. However, decisions made in those first few hours can have a huge impact further along the line. The idea that rehabilitation should begin at hour zero, maybe a challenge for a paramedic evacuating a patient or a frontline medical team at the limits of their capacity, but it needs to be in the mind of the frontline surgical team as they seek to save a limb.


Every patient is different following their own rehabilaition pathway with different degrees of mobility, confidence and complications to deal with. Operational artificial intelligence can help alert the team as to the critical risk or issues affecting the patient's longer-term rehabilitation. Being able to analyse patient data in real time to predict complications and facilitate early interventions, potentially reducing complications and improving recovery rates, could be transformational in conflict-affected regions where medical resources are strained.


Such data can provide care insights which can improve the integration of emergency response team's interventions into the longer term care for trauma patients. This can be especially significant with patients dealing with limb loss or amputation, and AI based alerts can encourage practitioners to take a more holistic approach to patient care, bringing in specialists to help address risk factors or actual complications in a more timely fashion.


Tracking information, during this journey or “longitudinally”, can help predict when these people will be unwell or ready to move on to the next stage of their support.


This information can also be shared with both the patient and the management team and carers to help provide a more consistent level of support in stretched health systems that may be struggling to meet urgent demands or trying to provide more comprehensive support to a system where services were "isolated" around traditional medical specialisations.


Cera Care

One organization following this approach is Cera founded by Dr Ben Maruthappu and now one of Europe's largest providers of digital healthcare at home.

Cera caregivers and nurses collect patient symptom information and health data during home visits, using artificial intelligence algorithms to predict deterioration before it happens, initiating early health interventions to prevent deterioration. The approach helped them:

· decrease in hospitalization rate by an unprecedented 52%

· up to 80% of hospitalizations were predicted seven days in advance

· reduction of patient falls by ~17%

· reduction of urination problems by ~47%

· reduction of infections by ~15%

· helped improve medication and prescription adherence in elderly patients by 35%.

The Veterans Health Administration (VHA)

In the United States, the Veterans Health Administration (VHA) is using operational artificial intelligence to improve the quality of care for veterans in a variety of ways.


The VHA employs AI models to forecast which veterans face elevated risks for conditions such as suicide, hospital readmission and deteriorating health. This predictive capability enables healthcare providers to intervene proactively before situations escalate into crises, potentially saving lives and improving health outcomes.


Administrative processes have been streamlined through AI systems that enhance appointment scheduling, diminish waiting periods and optimise resource distribution across VHA facilities. This increased efficiency allows healthcare practitioners to dedicate more time to direct patient care rather than administrative responsibilities, improving the overall care experience.


For diagnosis and treatment support, the VHA has deployed AI systems that analyse medical imaging, laboratory results and electronic health records to assist clinicians. These tools function as supplementary opinions to help identify potential issues that might otherwise be overlooked, thereby enhancing diagnostic accuracy.


Personalised care has been advanced through AI algorithms that analyse patient data to help customise treatment plans according to individual veterans' needs, medical histories and responsiveness to different interventions. This tailored approach leads to more effective treatments with fewer adverse effects.


Remote monitoring capabilities have been expanded through AI working in conjunction with Internet of Things (IoT) devices to observe veterans' health from a distance. This approach is particularly advantageous for rural veterans who may reside far from VA facilities, ensuring they receive appropriate care despite geographical challenges.


Mental health support has been bolstered by AI-powered tools that help screen for and monitor conditions such as PTSD, depression and suicide risk. This enables earlier intervention and continuous assessment, which are crucial for effective mental health treatment.


Limb loss or amputation can have a significant impact on a person's physical and mental health and often requires a multidisciplinary approach to treatment and care.


Health and care system integration can help ensure that these patients receive comprehensive and coordinated care across multiple healthcare providers and settings.


PTSD Resolution

This briefing looks at PTSD Resolution's experience of using AI to support their veteran services.


Below are a few examples of how operational AI can accelerate the integration of health and care for patients affected by limb loss or amputation:


Prosthetic Limb Design and Customization: Artificial intelligence can be used to analyze data from patient assessments, medical images, and other sources to create a personalized design and fit for a prosthetic limb. This can improve patient outcomes by ensuring that the prosthesis fits well and functions effectively right from the start. This becomes more important with the distributed care model https://www.lsngroup.org/post/shaping-the-future-of-amputee-care-innovation-and-accessibility-in-prosthetic-services ,



where the clinics may have fewer specialists and rely on remote experts to make the best use of the team's skills and local resources.


Artificial intelligence has the potential to accelerate the integration of health and care for patients affected by limb loss or amputation by supporting the personalized design and customization of prosthetic limbs, physical therapy and rehabilitation, pain management and mental health support.


However, it is important to ensure that AI is implemented responsibly and ethically, and that patient privacy and safety are maintained throughout the process.

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