Digital Health & AI in Oncology, Delivering Improved & More Personalized Care-The HSB Blog 7/28/23
Our Take:
Digital health technologies in oncology have emerged as a promising and transformative force in cancer care. By leveraging the power of digital and communication technologies, these innovative tools are reshaping the landscape of cancer diagnosis, treatment, monitoring, and patient support. Artificial Intelligence and data analytics have emerged as essential companions in the fight against cancer. Telemedicine and remote patient monitoring have broken barriers in delivering quality care, especially for patients residing in remote areas. Digital health technologies in oncology will play a critical role in revolutionizing cancer care and research. Embracing innovation and technology will lead to improved treatments and better patient outcomes worldwide.
Key Takeaways:
The single most effective lever in cancer treatment is early detection with the five-year survival rates for the top five cancers being anywhere from 4 to 13 times higher at Stage 1 versus Stage 4 (World Economic Forum)
US health-care spending for medical services and prescription drugs related to Cancer is projected to reach US$246 billion by 2030 (Jrnl. National Cancer Institute)
In 2019, there were approximately 23.6 million new cancer cases and 10 million cancer deaths globally, representing a 26% increase in new cases and a 21% increase in fatalities vs. 2010 (World Economic Forum).
The number of clinical trials employing a digital health device as part of the intervention has grown from 8 in 2000 to over 1100 in 2018—a 34.8% CAGR (Jrnl. National Cancer Institute)
The Problem:
Implementing digital health solutions in oncology requires acceptance and training among healthcare providers. For digital health solutions to be effective, they need to be seamlessly integrated into existing clinical workflows. Physicians may be reluctant to fully embrace new technologies, and a lack of training can lead to underutilization or misuse of digital health tools. Disrupting or burdening healthcare providers' routines may hinder the adoption and acceptance of these technologies particularly given the challenges or workforce demand and burnout.
In addition, digital tools, such as AI-driven diagnostics or decision-support systems, heavily rely on data accuracy and algorithm reproducibility. While technology can help reduce errors, it can also introduce new types of errors. In the context of oncology, incorrect or incomplete data entry, system malfunctions, and user errors can lead to misdiagnosis errors and adverse patient outcomes. The inaccurate predictions or misinterpretations of diagnostic information could lead to serious consequences for patients, including delayed or inappropriate treatments.
Like other AI and ML models, AI and ML algorithms used in oncology may suffer from bias if the training data is not diverse and representative. Moreover, any breach or mishandling of patient information could have severe consequences, leading to potential legal and ethical issues. As digital health technologies collect and process sensitive patient data, ensuring data privacy and security becomes paramount.
By addressing these obstacles, the oncology community can maximize the benefits of these innovative tools and advance the field of cancer treatment.
The Backdrop:
Digital health technologies in oncology have emerged against the backdrop of a rapidly evolving healthcare landscape, characterized by increasing cancer incidence rates, growing complexity in cancer treatments, and the need for personalized, patient-centric care.
The demand for accessible and convenient healthcare services has grown, especially in specialties like oncology, where patients often face a shortage of providers, travel burdens and frequent follow-ups. As noted in , “Digital health for optimal supportive care in oncology: benefits, limits, and future perspectives”, “The terms digital health, telehealth, and eHealth are interchangeable and are defined as the provision of healthcare services supported by telecommunications or digital technology to improve or support healthcare services.” Perhaps most importantly, the authors note, “eHealth solutions can be part of each step of the healthcare process (i.e., prevention, diagnosis, decision-making, treatment/intervention, and follow-up).”
Along those lines, the digital transformation of healthcare has fostered a broader degree of collaboration between oncologists, researchers, technology companies, and patient advocates. As noted in “Maximizing the Value of AI in Cancer Care”, “the use of AI and ML to collect and analyze real-time patient experience data in oncology is revolutionizing how we approach cancer care, guiding treatment decisions and ultimately improving patient outcomes.” This not only accelerates already existing multidisciplinary approaches to care, but facilitates a greater exchange of knowledge and progress in care protocols.
Not surprisingly, the exponential growth of computing power, data storage capacity and analytics, including predictive analytics, has paved the way for sophisticated digital health tools and AI algorithms applicable to oncology. These tools can process vast amounts of patient data, including genomic profiles, imaging data, and clinical records and apply them to improve treatment protocols. For example, in “Is AI-enabled radiomics the next frontier in oncology?”, the authors look at “Radiomics uses AI-driven analytics to extract meaningful data from traditional imaging modalities such as CT, MRI or PET scans.” The technology “then curates, annotates and analyzes that quantitative data to deliver a wealth of information that cannot be observed visually in an image.”
The convergence of technological advancements, the need for personalized medicine, and the emphasis on patient-centered care have set the stage for digital health technologies to dramatically transform cancer care. As these technologies continue to evolve and overcome challenges, they hold the promise of transforming oncology, improving treatment outcomes, and positively impacting the lives of cancer patients worldwide.
Implications:
Telemedicine and remote monitoring technologies enable continuous tracking of patients' health status, treatment response, and side effects. This allows healthcare providers to intervene promptly when necessary, ensuring better management of patients' well-being. Digital health technologies prioritize patient needs and preferences, allowing for more personalized care and treatment plans. Patients can be given higher quality information and have greater involvement in their treatment decisions, helping to reduce patient anxiety during treatment and thereby improving satisfaction and overall well-being.
Digital health tools, including AI-powered imaging analysis and risk assessment algorithms, aid in early cancer detection. Timely identification of cancer can lead to earlier interventions and potentially better treatment outcomes. As highlighted in “Digital Health Applications in Oncology: An Opportunity to Seize”, these types of prediction tools “could be used to influence clinician decision making along the cancer spectrum, such as after chemotherapy, after colorectal cancer surgery, or in discharge planning. Such ML-based predictive algorithms may be used to “nudge” clinicians toward value-based care streams for high-risk patients or to default patients into population health management programs to improve advance care planning and/or reduce unplanned utilization.”
The rapid evolution of digital health technologies fosters a culture of continuous innovation in oncology. As new tools and applications are developed and integrated into clinical practice, the field advances further, leading to ongoing improvements in cancer care. Interestingly, these include helping eliminate waste and overtreatment near the end of life. For example, in “Delivering Affordable Cancer Care in the 21st Century: Workshop Summary” the authors noted that "unrealistic expectations and misaligned financial incentives are contributing to the overuse and misuse of interventions in cancer care”. The paper highlighted that “overuse is particularly problematic in individuals with advanced cancer, noting a high rate of treatment with chemotherapy close to the end of life, more time spent in the emergency room and the hospital, and less time in hospice care." Clearly this is one area where more objective data and analytics could be used to help explain and justify less invasive and costly end of life treatments.
The opportunities for digital health technologies in oncology are expansive, offering new avenues for personalized, data-driven, and patient-centric cancer care. By leveraging these technologies effectively, healthcare providers can make significant strides in improving cancer outcomes and leading to improved outcomes and higher satisfaction for patients.
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