Digital Health: An Imperative Tool for Pharma
The role of digital tools, such as mobile devices/apps, wearables, virtual assistants, and artificial intelligence (AI), in healthcare is quickly expanding. Pharmaceutical companies are increasingly integrating digital health into all services offered, including for treatment, follow-up, and prevention purposes. Additionally, they are shifting their focus from only providing drug-specific patient apps to developing more complex tools such as digital biomarkers to track various subjective or objective outcomes. As a result, digital health will likely play a major role in all aspects of healthcare in the future. However, for digital health to reach its full potential, there are still obstacles to overcome. In this article, we will explore some of the current and future uses of digital health and its benefits to both patients and pharma. Further, we will discuss the challenges to address before these tools can become widespread and the means to overcome these barriers.
Digital Health Today
Digital health tools serve multiple purposes. Basic health-related smartphone apps and wearables such as food diaries, exercise trackers, and heart rate monitors can help create awareness and improve general health. The ultimate hope is that these tools will minimize the risk of chronic lifestyle-related conditions such as diabetes and cardiovascular disease. However, public health efforts, for example, delivered via digital communications, are needed to ensure that these apps reach their target audience.
Several targeted apps and sensors based on specific health conditions or treatments are also available. These include disease tracking, diagnostic, and medical-grade imaging apps. Collectively, these are known as mobile health (mHealth) tools. In theory, mHealth can allow acute disease diagnosis and chronic disease management to take place outside the clinic or hospital. As examples, mHealth may include blood pressure monitoring, skin cancer screenings, and infectious disease diagnoses in the near future. With almost 600 studies published on digital health apps, there is now clinical evidence supporting their efficacy.
Digital Health Tomorrow
Other growing areas of digital health include AI and the Internet of Medical Things (discussed here). AI has shown some promise in diagnosing various cancers and interpreting imaging and diagnostic test results. Further, AI may also make medicine more specific by drawing distinctions easily missed by humans. For example, it may help promptly identify urgent vs. less urgent stroke cases and fast- vs. slow-growing cancers. In turn, this would enable high-risk patients to receive treatment more quickly. Although it will likely not be a substitute for human physicians, AI may greatly aid in establishing differential diagnoses and providing second opinions.
Benefits of Digital Health Tools
In addition to the potential benefits for improving human health and for preventing and managing diseases, there are multiple other benefits of digital health. For Pharma, digital health and AI can be leveraged throughout the lifetime of a patient’s condition. This includes at pre-diagnosis, diagnosis, treatment, monitoring, and remission. By minimizing the need for clinic visits and expensive diagnostic tests at all these stages, digital health can help cut costs significantly. In fact, according to a recent report from the IQVIA Institute, the use of these apps in only five patient populations – diabetes prevention, diabetes, asthma, cardiac rehabilitation, and pulmonary rehabilitation – has the potential to save the U.S. healthcare system approximately $7 billion each year. Now, imagine if similar apps could be developed and implemented for all patient populations?
Moreover, by providing more targeted results based on various digitally-obtained biomarkers, digital health will also allow manufacturers to share the risk with the payers by pricing the products according to health outcomes. Consequently, such outcome-based pricing will allow the prescription of the drug(s) most likely to provide a positive outcome for the patient. In addition, by going digital, the price a healthcare system pays can be linked to the performance of the drug in real life.
Nevertheless, the pace of the digital revolution in healthcare has been slow, owing largely to the current regulations, or lack thereof, surrounding digital health.
Potential Barriers
Other barriers preventing the widespread use of AI in medicine include today’s medical culture, which often values physician intuition over evidence-based solutions. Many physicians do not like being told what to do, especially by a computer. Hence, means of getting them comfortable with the idea of a machine observing their practice are needed. There are also financial barriers, especially in countries with a fee-for-service reimbursement model such as the U.S. In these cases, there is no financial incentive for practitioners to implement such a system.
Furthermore, despite the growing number of publications, high-quality large-scale clinical research studies on digital health are still lacking. Especially, there is a huge unmet need for real-world, patient-generated data on the efficacy of mHealth and AI. In addition, the technology must be easy to use for both the patients and providers, and the collected data must be easily interpreted.
There need to be extensive education and marketing efforts to make sure that the right patients or at-risk populations will use the relevant apps or devices. Even if the apps themselves work perfectly, if their target consumers do not use them, their effectiveness is limited. For example, getting overweight individuals, who may not be motivated to lose weight, to use fitness or diet apps represents an important challenge.
Finally, there are several ethical barriers to address. Digital health apps inevitably have to collect personal data. Ensuring the safety of those data is imperative. Especially, after the implementation of the GDPR earlier this year, this should be a focus for all stakeholders. Further, another concern is that AI algorithms may be prone to bias. For example, the algorithms may inadvertently contain racial or socioeconomic biases if the management decisions are designed to take into account the financial or insurance status of the patient.
How to Overcome These Barriers: The Importance of Leveraging Expert Insights
Despite these potential barriers, in the next decade, most healthcare organizations and companies will likely use digital health tools to some degree. To achieve this goal, pharmaceutical companies need to continuously engage with external stakeholders to incorporate their needs and wants into the offered technologies.
Advisory boards comprising the relevant stakeholders are essential for leveraging expert insights. In terms of developing digital health technologies and overcoming the current barriers, advisory boards serve multiple purposes. They can help determine the need for specific tools and provide feedback on new apps. Among others, the stakeholders may include payers, physicians, nurses, allied health professionals, or patient support groups. However, as advisors are often living in different regions or countries, getting them to meet in person can be both difficult and expensive. One way to circumvent this is to conduct online advisory boards using digital platforms such as the Impetus InSite Platform®. This allows the advisors to provide feedback when convenient, saving them the travel time.
Besides enabling online discussions among the advisors, the Impetus InSite Platform® allows collaboration in various forms. For example, the advisors can co-develop apps or guidelines using asynchronous annotation tools. Furthermore, you can conduct several digital advisory boards over a specified period, each customized to build on the insights obtained in the previous. If needed, Impetus can organize web-based or in-person meetings at critical points of the process. Using a digital system also helps minimize the administrative burden by automating project elements such as email reminders and collation of responses into transcript reports.
References
Armstrong, H., Padilla, N. (2017). Digital Health: A new path to success. Deep Dive. Retrieved from https://pharmaphorum.com/deep-dive-digital-II-december-2017/index.htm#!/digital-health-a-new-path-to-success
Author unknown. (2018). From A&E to AI – Artificial intelligence will improve medical treatments. The Economist. Retrieved from https://www.economist.com/science-and-technology/2018/06/07/artificial-intelligence-will-improve-medical-treatments
Desai, D. (2017). Healthcare’s hype cycle: which technologies will stay the course? Deep Dive. Retrieved from https://pharmaphorum.com/deep-dive-future-pharma-july-2017/index.htm#!/healthcares-hype-cycle-which-technologies-will-stay-the-course
IQVIA Institute. (2017). The Growing Value of Digital Health – Evidence and Impact on Human Health and the Healthcare System. Retrieved from https://www.iqvia.com/institute/reports/the-growing-value-of-digital-health
Pearl, R. (2018). Artificial Intelligence In Healthcare: Separating Reality From Hype. Forbes. https://www.forbes.com/sites/robertpearl/2018/03/13/artificial-intelligence-in-healthcare/#353a7e791d75
Staines, R. (2017). Can digital technology transform pharma R&D? Deep Dive. Retrieved from https://pharmaphorum.com/deep-dive-digital-II-december-2017/index.htm#!/can-digital-technology-transform-pharma-rd
Steinhubl, S.R., Muse, E.D., Topol, E.J. (2015). The emerging field of mobile health. Science Translational Medicine, 15, 283.
Weintraub, A. (2018). Artificial Intelligence Is Infiltrating Medicine — But Is It Ethical? Forbes. Retrieved from https://www.forbes.com/sites/arleneweintraub/2018/03/16/artificial-intelligence-is-infiltrating-medicine-but-is-it-ethical/#3310f0763a24