Cancer is a major public health problem, accounting for nearly 10 million deaths and over 19 million new cancer cases worldwide in 2020. The WHO estimates that the number of new cancer cases will rise to nearly 29 million in 2040. This alarming statistic is indicative of the enormous focus and investment that will flow into oncology worldwide.
What are the goals of digital health technologies in the cancer patient’s journey?
Innovative digital health solutions have the potential to revolutionize every step of the cancer patient journey. The approach is a shift to data-driven solutions aimed at complementing manual intervention and judgment in areas critical to patient outcomes. The cancer patient journey and related potential digital health goals look like this:
- Symptom awareness and screening
Early recognition of cancer symptoms, adherence to cancer screening, and potential genetic testing is of great importance in optimizing cancer treatment outcomes. Wider awareness of comprehensive information among doctors and patients can be promoted through advisory and educational campaigns using digital technologies.
- Improving the accuracy and speed of cancer diagnosis
Treatment begins with finding. People diagnosed earlier with cancer are not only more likely to have better treatment outcomes but, importantly, improved quality of life during treatment and potentially improved life after cancer compared to those , diagnosed later. Accurate diagnosis and faster initiation of treatment can also significantly reduce the cost and complexity of cancer treatment.
Applying AI to biomarker data has the potential to revolutionize cancer diagnostics by improving the accuracy and speed of diagnosis, as AI enables efficient analysis of complex data from multiple modalities.
- AI-based imaging solutions in cancer diagnosis
In many cases, the diagnosis of cancer is made through imaging techniques such as X-rays, CTI, MRI, PET and others. AI-based software is rapidly being adopted to support clinicians in cancer diagnosis, staging, tumor monitoring, complexity assessment, surgical procedures and pathology, among others.
Product examples of AI-based imaging solutions in cancer diagnosis
- AI-based biopsy solutions in cancer diagnosis
AI-driven precision pathology is another component with great potential to significantly increase the accuracy and speed of diagnosis. Digital biopsy solutions transform the entire biopsy process, including image analysis, case management, image digitization, interoperability, reporting and sharing among cancer diagnostics.
Product examples of AI-based biopsy solutions
- Digital PCR solutions for liquid biopsy in cancer diagnosis
Non-invasive cancer diagnosis solutions are a growing alternative to invasive cancer biopsies. The technique uses body fluids such as blood samples, urine, saliva, feces and sputum instead of tissue for diagnosis. Such techniques allow the quantification of multiple genetic markers and multiple tests from a single sample, making the diagnostic process simpler.
Product examples of liquid biopsy solutions
- Digital outcome prediction for cancer treatment decision
When choosing an appropriate oncology treatment plan, it is important to consider which therapy is particularly promising in each individual case. Predictions based on clinical and molecular cancer data of whether a tumor is likely to respond have great potential to optimize the decision-making process for clinical cancer treatment in the future.
Product examples of predicting digital treatment outcomes
- Digital solutions for patient management and monitoring
The treatment phase in oncology is usually characterized by repeated therapies that are often accompanied by strong and unpleasant side effects. The use of digital health technologies can make a huge contribution to empowering patients and reducing the burden of treatment. At the same time, such solutions allow clinicians to improve patients’ personal treatment plans for optimized outcomes and maintaining an acceptable level of quality of life.
Patient management and monitoring solutions consist of telemedicine devices, tracking sensors and patient reporting portals. Telemedicine serves as a lifeline for the care that cancer patients need. Real-time biometrics or vital signs data collected by wearable sensors provide clinicians with the necessary insight into a patient’s health status and quality of life. Patient management portals are digital solutions where patients report their problems in real time, get help and treatment advice. There are also self-care apps that help patients manage their diet, exercise, sleep, medications and mental health.
Examples of products for cancer patient management and monitoring solutions
Product examples of cancer self-management solutions
- Digital solutions for symptom management after cancer
Ideally, cancer progression for the patient can be prevented or the cancer can even be eliminated. However, even after successful cancer treatment, there are post-cancer symptoms that need to be managed. Chronic fatigue is one of the most common problems among cancer survivors, affecting social, occupational and general functioning of individuals and can lead to a significantly reduced quality of life.
Product examples of post-cancer symptom management solutions
Summary and perspective
The digital future of oncology throughout the patient journey has great potential. Digital health solutions targeting effective cancer symptom awareness/screening combined with technologies that improve accuracy and speed through data-driven diagnostics, support individualization and tailoring of treatment decisions, and provide continuous patient monitoring data to optimize treatment plans promise significant reductions in cancer death rates.
In addition, cancer management technologies have the potential to improve treatment experience, safety, and patient-clinician interactions and may lead to improved patient quality of life during and after cancer treatment.
However, despite some promising digital health solutions related to oncology today, it is still in its infancy as a field. A coordinated effort will be required to build a viable path to clinical validation, integration and adoption of these digital health solutions in routine clinical practice.
Editor’s note: The author claims no business relationship with the companies mentioned in the article. He is also not aware of any financial ties between the companies and Novartis within his role at Novartis.
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