R-U-Ontrak.
Building continuous improvement models in health and social challenges by applying AI to lived experience data.
About
Us
Our Story
We firmly believe that harnessing lived experienced data and leveraging AI can unlock invaluable insights, serving as the foundation for continuous improvement models across diverse domains.
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Unlike conventional methods where AI is applied to existing datasets, we adopt an innovative approach by generating our data to develop models. This entails assisting individuals in navigating complex processes effectively.
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Embracing this challenge excites us, as it presents a tremendous opportunity to create a global impact that can be far-reaching and transformative.
Who We Are
We bring together a remarkable team of individuals who have demonstrated thought leadership, accomplished investing, visionary approaches to problem-solving, empathetic design skills, and decades of experience in multi-site and multi-disciplinary practice management. Our mission is to develop a framework that will bring tangible change to people around the world.
Drawing from extensive lived experience and a keen focus on driving better outcomes through technology and treatment model application, we tackle significant challenges and drive positive change globally. Our deep commitment to helping others fuels our efforts to revolutionize the well-being of individuals and communities, with people at the heart of everything we do.
Utilizing lived experience data, we create a profound impact, shaping a future where health and social support are transformed for the better. Together, we form a dedicated team, united in the pursuit of a more compassionate and empowering world.
Our Vision
Continuous improvement becomes achievable when you possess a comprehensive understanding of the current processes and hold the conviction that making certain adjustments will lead to enhancements.
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At the heart of our vision is a belief in the versatility of our model, inspiring us to apply it across diverse domains worldwide.
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Our core objective is to positively impact the lives of countless individuals around the globe, enabling them to live their best achievable life. With this vision in mind, we are dedicated to implementing continuous improvement models in as many areas as possible. These models, empowered by a combination of lived experience data and AI, aim to revolutionize outcomes in as many countries as possible, making a profound difference in the well-being of people worldwide.
Our Ask
We are currently seeking Providers and Researchers who specialize in various fields, including:
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Sports injury with a focus on concussion recovery,
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Neurological conditions with an emphasis on Parkinson's disease management,
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The aging process with a focus on falls prevention,
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Workplace injury rehabilitation,
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Social challenges with a focus on domestic violence, homelessness, and reducing recidivism,
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Veteran's health,
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Women's health, and
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Indigenous health.
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Our main goal is to collaborate with experts like you to develop research projects centered around understanding the lived experiences of individuals navigating complex areas like those mentioned above. We aim to capture de-identified lived experience data to build comprehensive datasets that will enable us to apply algorithms and establish continuous improvement models.
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In pursuit of our objectives, we are committed to securing grants to fund the research projects and are particularly interested in initiating collaborations in Australia, the US, the UK, Ireland, Canada, and New Zealand.
By joining forces, we can make significant strides in improving outcomes and developing more effective interventions in these critical areas of study.
Our Platform
Our Platform has three main areas:
The App
At the heart of our approach is the belief that individuals should be in charge of managing their journey from an event to their desired goal.
The R-U-Ontrak app serves as an invaluable aid in this process, empowering users to set personalized goals and milestones, track essential actions, respond to provider questions, and foster communication with providers, friends and family.
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By providing a user-centric experience, we prioritize individual empowerment and accountability.
Users have the flexibility to manage their journey according to their unique needs and circumstances, while our app acts as a constant companion, supporting them at every step.
Through this comprehensive approach, we foster a sense of ownership and control, ensuring users feel engaged and motivated throughout their journey towards achieving their desired goals.
The Website
Our model places a strong emphasis on fostering communication and engagement among providers, their clients, and other relevant stakeholders. By utilizing our website platform, providers can easily share their goals, actions, milestones, and questions with the people they serve.
The website facilitates seamless sharing of text messages between providers and their clients, as well as between different providers involved in the process. This open communication channel promotes collaborative efforts and ensures that everyone involved is on the same page.
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Ultimately, our overarching goal is to enhance outcomes by facilitating better communication, engagement and information sharing. By promoting transparency and cooperation, we aim to optimize the delivery of services and empower people to actively participate in their own journey. The result is a more holistic and effective approach that benefits all stakeholders involved.
Lived Experience Data & AI
At the core of our approach is the lived experience data we collect from individuals who have achieved important outcomes in health and social challenges, enabling them to live their best achievable life.
This unique data source forms the bedrock of our "picks and shovel" model, empowering us to adapt and apply our approach effectively to a wide range of use cases. With this flexibility, we confidently address various challenges, ushering in positive change across multiple domains and sectors.
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By accumulating substantial data from those who have attained significant outcomes in health and social challenges, we gain profound insights into their journey, transcending borders and communities. This wealth of understanding empowers us to catalyze positive transformations on a global scale, making meaningful impacts in diverse contexts.
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The lived experience data, combined with AI-powered analysis, drives us towards a future where continuous improvement is guided by real-life outcomes in health and social well-being, ensuring individuals worldwide can live their best achievable life. We are committed to harnessing the power of these insights to drive positive changes, celebrate successful outcomes, and empower individuals to achieve their aspirations in health and social well-being.
Our Areas of Focus
Sports Injury Recovery with a focus on Concussion recovery
The combination of AI and lived experience data has the potential to revolutionize sports injury recovery, with a particular focus on concussions. By integrating AI with vast datasets of lived experience, we can gain invaluable insights into the complexities of concussions and collaborate with providers to develop innovative therapies and treatment protocols tailored to individual needs.
This data-driven approach optimizes recovery programs, shortening downtime and facilitating a safe return to play or daily activities for athletes and individuals worldwide. Ultimately, the integration of AI and lived experience data in sports injury recovery holds the promise of a future where athletes receive personalized, empathetic care, ensuring more efficient, effective, and compassionate recoveries.
Neurological Conditions with a focus on Parkinson's disease management
The integration of AI and lived experience data has the potential to transform the management of neurological conditions, with a specific focus on Parkinson's disease. By analyzing diverse lived experience data, personalized treatment plans can be tailored to optimize symptom management and enhance the quality of life for those living with Parkinson's. Furthermore, the aggregation of lived experience data into comprehensive datasets can drive groundbreaking research and lead to the development of innovative therapies and potential disease-modifying treatments.
By building AI-powered virtual assistants, we can provide invaluable resources and personalized coping strategies, offering essential support to patients and caregivers. This data-driven and compassionate approach to neurological condition management holds great promise, ensuring more effective care and improved well-being for individuals with Parkinson's and other related conditions.
The Ageing Process with a focus on Falls Prevention
The amalgamation of AI and lived experience data offers a powerful opportunity to develop and implement effective fall prevention programs for aging individuals, significantly reducing the risk of falls. By analyzing diverse lived experience data from those participating in fall prevention programs, valuable insights into the risk factors and patterns surrounding falls can be gained, enabling AI algorithms to identify predictive indicators and tailor fall prevention initiatives that cater to individuals' unique needs and circumstances. These targeted programs may include personalized exercise regimens, home modifications, and educational resources, all aimed at promoting greater safety and independence for at-risk individuals. Furthermore, the aggregation of data from these participants in ongoing fall prevention programs will fuel research efforts, providing valuable insights into program effectiveness and identifying areas for improvement, thus advancing our understanding of fall-related risks in aging populations. Leveraging the power of AI and lived experience data in this iterative approach to fall prevention will not only create a safer environment for aging individuals but also foster continuous improvement, leading to a more impactful and sustainable impact on reducing fall risks and enhancing the overall well-being of the aging population.
Workplace Injury Rehabilitation
By analyzing diverse lived experience data from individuals who have experienced workplace injuries, valuable insights into the factors influencing recovery outcomes can be gained. AI algorithms can pinpoint patterns and risk factors, enabling the development of personalized recovery plans for injured workers. These targeted interventions may encompass specialized physical therapy, psychological support, workplace accommodations, and gradual return-to-work programs, all aimed at expediting the healing process and restoring productivity. Leveraging the power of AI and lived experience data, these tailored rehabilitation programs can be designed to cater to each worker's unique needs and circumstances.
By harnessing data-driven insights, healthcare professionals can optimize treatment plans, leading to more effective and efficient recovery outcomes. This approach not only benefits the injured workers by facilitating their return to work and improving their well-being but also has potential cost savings for employers by reducing absenteeism and worker's compensation expenses. The integration of AI and lived experience data in workplace injury rehabilitation has the potential to transform the way we address and support injured workers, fostering a safer and more productive work environment.
Social Challenges with a focus on domestic violence, homelessness and reducing recidivism
The integration of AI and lived experience data holds tremendous promise in addressing social challenges, including domestic violence, homelessness, and reducing recidivism rates. By analyzing diverse lived experience data, valuable insights into the underlying factors and patterns associated with these complex issues can be gained, paving the way for more effective interventions and support systems. AI algorithms can assist in tailoring support services for survivors of domestic violence, providing counseling, legal aid, and emergency shelters that better meet their specific needs and facilitate a safe escape from abusive situations. Additionally, the aggregation of lived experience data contributes to a deeper understanding of the diverse challenges faced by individuals experiencing homelessness, helping to identify effective pathways and support systems that foster long-term housing stability. Furthermore, AI-driven analysis of recidivism rates can inform evidence-based rehabilitation programs for previously incarcerated individuals, designing personalized interventions that address the root causes of criminal behavior and promoting successful reentry into society while reducing the risk of reoffending. By harnessing the potential of AI and lived experience data in tackling these social challenges, we can pave the way for more compassionate and effective approaches, prioritizing the well-being and empowerment of individuals facing these issues and fostering a more inclusive and supportive society for all.
Veteran's Health
By analyzing diverse lived experience data from injured veterans, valuable insights into the challenges they face during recovery can be gained. AI algorithms can identify patterns and risk factors specific to veterans, allowing for the development of personalized rehabilitation plans that consider the physical and psychological impact of their military service. These tailored interventions may encompass trauma-informed care, specialized physical and mental health support, peer support networks, and assistance in transitioning to civilian employment or other post-military pursuits, all aimed at promoting successful recovery and reintegration. Leveraging the power of AI and lived experience data, these personalized rehabilitation programs can be fine-tuned to cater to each veteran's unique needs and experiences.
By harnessing data-driven insights and considering the lived experiences of other veterans, healthcare professionals and support organizations can optimize the effectiveness of rehabilitation strategies. This holistic approach not only benefits the veterans by providing comprehensive support for their physical and mental well-being but also recognizes the sacrifices they have made in their service to the country. By embracing the transformative potential of AI and lived experience data in veteran rehabilitation, we can honor their service by ensuring they receive the specialized care and support they need to thrive in their civilian lives.
Women's Health
By analyzing diverse lived experience data from women who have experienced conditions like endometriosis, menopause, and polycystic ovary syndrome (PCOS), valuable insights into the factors influencing their health outcomes can be gained. AI algorithms can identify patterns and risk factors, enabling the development of personalized treatment plans for affected women. These tailored interventions may include specialized medical management, lifestyle adjustments, and psychological support, all aimed at improving symptom management and overall well-being. The integration of AI and lived experience data in women's health offers an empowering opportunity to revolutionize healthcare for women dealing with these conditions. This data-driven approach fosters a more proactive and personalized treatment paradigm, recognizing the unique experiences and challenges faced by women in their health journeys. Moreover, the aggregation of lived experience data into comprehensive datasets can fuel research efforts, leading to a deeper understanding of these health issues and potentially uncovering novel insights that may contribute to the development of innovative therapies and interventions. Through this transformative synergy of AI and lived experience data, we can pave the way for improved health outcomes and a better quality of life for countless women worldwide.
Indigenous Health
The integration of AI and lived experience data in Indigenous health, particularly focusing on chronic disease management, holds immense promise in revolutionizing healthcare for these populations. AI algorithms can identify patterns and risk factors related to chronic diseases prevalent in Indigenous communities, such as diabetes, cardiovascular conditions, and respiratory illnesses. This data-driven approach enables the development of personalized and culturally sensitive treatment plans, taking into account the unique needs and experiences of Indigenous individuals, with a specific focus on addressing the challenges posed by chronic diseases. By harnessing the power of technology and lived experiences, healthcare professionals can design more targeted interventions and prevention strategies. This comprehensive approach aims not only to improve health outcomes but also to address systemic health disparities and inequities that Indigenous communities may face. Additionally, the aggregation of lived experience data into comprehensive datasets can drive research efforts, leading to a deeper understanding of chronic diseases in Indigenous populations and potentially uncovering novel insights that may contribute to the development of effective public health policies and programs. Through this transformative integration, we can work towards a future where Indigenous communities receive the specialized and culturally appropriate care they need to combat chronic diseases and promote better health and well-being.
Why
Us
A Unique Approach
We have a "picks and shovel" model which can be applied in a myriad of areas.
Our technology includes an app for a person to manage their holistic process to achieve an important goal, ie return to work following an injury. Through the app they can communicate with their team who are assisting them and in some circumstances they may have a coach working with them. Within the app a person can spin up their team to help them manage their process.
We also have a website for their providers to share goals, actions, milestones, questions and to communicate with them and to communicate with their other providers.
We have adopted a goal framework and when a person achieves their goal we will ask them to share their de-identified lived experience data with us so we can pool the data, apply our ai algorithms and build continuous improvement models that can be shared with people, their providers to improve outcomes globally.
Years of Experience
Over the course of more than 8 years, we have been devoted to researching and refining our transformative model. Building and rigorously testing our technology to engage with people and providers, we have honed its effectiveness.
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Our commitment extends beyond research, as we actively engage with people, providers, payers, researchers, not-for-profits, and governments across various countries. This comprehensive approach enables us to understand the dynamics in a wide range of areas, providing us with unparalleled insights.
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These insights grant us an unfair advantage as we forge ahead in building the models that drive our pursuit of transformative solutions. With this distinct advantage, we are well-equipped to make a profound impact on health and social support, enhancing the well-being of individuals and communities worldwide.
Research Driven
In order to build the models we are seeking to deliver we plan on working with people, providers and researchers.
Our approach is simple and repeatable.
We will identify an area of focus, identify researchers who are capable of delivering the appropriate research framework, identify providers who wish to deliver models that will be informed by lived experience and we will seek funding from organisations who believe that addressing a particular area is important.
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With a "picks and shovel" model this can be repeated in the same area in multiple countries at the same time.
We Need Outcomes
At the heart of R-U-Ontrak's mission is achieving positive outcomes for individuals by supporting them in reaching their significant health or social challenge goals. Through the utilization of diverse lived experience data and AI-driven continuous improvement models, we work to empower people in attaining their best possible results. When individuals successfully achieve their goals and contribute their de-identified data, we can pool this valuable information, apply AI algorithms, and build robust continuous improvement models. This iterative approach allows us to identify patterns, effective strategies, and best practices that lead to successful outcomes.
By focusing on helping individuals achieve their goals in the first place, we ensure that the data we collect is representative and meaningful, enabling us to create solutions that have a meaningful impact on improving health and well-being. With an unwavering commitment to enhancing outcomes through continuous improvement models, R-U-Ontrak strives to make a significant and positive global impact on people's lives, contributing to better health and well-being for all.
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