Hyper-personalization of Healthcare: Empowered by New Innovations

Big Data and AI-driven technology have made an impact on every kind of business, and healthcare is affected by its influence. The global COVID-19 pandemic, along with the inclusion of big data in healthcare, has created the need for a revolutionary data-driven personalized approach. As a result, a profound trend in the healthcare business has emerged; the hyper-personalization of healthcare. 

This technology, which is based on the medical patient data market, has the power to transform the way we experience health services and direct healthcare’s future trajectory. Our focus in this research surrounds hyper-personalization in medicine and the two main tools that will define its implementation: remote patient monitoring and digital twin technology.

Table of Contents

What is Hyper-Personalization?

Hyper-personalization is the focus on serving the customer’s individual needs. Creating a customer experience that is shaped to address the individual customer pain points at every touchpoint of the customer journey (Amar et al. 2020). Previously, this was largely done in the field of marketing, such as hyper-personalized advertisements or promotions to address the specific needs of a given persona.

Within the healthcare, industry hyper-personalization is the development of patient-specific and customized treatments based on more than just conventional medical diagnosis methods. These precision medicines are a result of the latest technological trends in the market, such as genomics, proteomics, metabolomics, and big-data-driven predictive analytics.

The main aim of this advancement is to drive meaningful data to accelerate healthcare outcomes in the long run, create personalized treatment journeys and leverage the power of next-gen technologies to treat patients based on the gained insights. 

As a result of its unlimited potential, the market for big data and big medicine in healthcare is already booming, and by 2025 the global personalized medicine market is expected to reach $3.18 trillion (Grandview, 2019).

What Drives This Trend?

Personalized healthcare is driven by a number of sources:

  • Healthcare analytics – When patients’ health histories are available at the inception of treatment, the healthcare providers make fewer guesses and provide more informed decisions.
  • Big Data – Big data provides access to more patient data points. Delivering an abundance of information to healthcare professionals as they address increasingly complex healthcare challenges.
  • AI and Machine learning – AI’s predictive models make a significant impact in healthcare by informing or even shaping how providers diagnose patients.
  • The Orphan Drug Act: After the act was passed in 1983, healthcare has witnessed an exponential growth in the number of therapies for rare diseases.

The Benefits of Hyper-Personalisation

  • Timely Identification and Accurate Treatment of Diseases – Big data in healthcare, digital twin technology, and healthcare analytics help physicians in early identification of diseases. Furthermore, these technologies give healthcare providers access to a reference point of similar patient-specific analytics and help construct customized patient treatment plans.
  • Providing one-on-one treatment: Big pharma – with the help of advancements in cell and gene therapy, 3D-printed surgical implants and bespoke drug manufacturing tailored for a single patient – are furthering modern healthcare. This will not just improve the provider’s and patient’s experience, but also help deliver more promising health outcomes.
  • Manage Genetic Mutations – Hyper-personalized medicine and healthcare analytics create opportunities to stabilize the health conditions of patients with certain genetic mutations. Gene editing and replacement will enable doctors to generate more effective drugs. These drugs may not cure genetic mutations but have the potential to lessen the negative impacts on afflicted patients. Hyper-personalized medicine and healthcare analytics can also accurately specify the drug quantity needed to control health situations in the long term.
  • Encourage a Healthier Lifestyle – Hyper-personalized medicine can empower more informed health decisions. For example, it can monitor blood pressure in at-risk patients so they can control their daily regimen and even inform their drug intake (Turner, 2007).

 What is Remote Patient Monitoring?

Remote Patient Monitoring Devices, like Fitbits, wearable heart monitors, Bluetooth-enabled scales, glucose monitors, skin patches, or maternity care trackers have made it possible for providers to observe, report, and analyze the patients’ acute or chronic conditions from any part of the world in real-time. As a result, these devices have become highly useful for patients, clinicians, and program directors.

Apart from monitoring elements as basic as calories, these devices help patients with multiple diseases such as diabetes, high blood pressure, atrial fibrillation, or even dementia. Remote patient monitoring enables patients to share live updates about their health, vitals, and environment more easily. Patients and doctors can also acquire, transmit, process, and store patient data. Patient monitoring devices and platforms help medical providers retrieve accurate data when they need it and make better treatment plans.

Remote Patient Monitoring Trend & Growth.

The remote patient monitoring market is a booming market and by 2026, is expected to reach $85 billion, an increase from $20.027 billion in 2019 (Wood, 2021). The main contributors to this growth are the growing aging population and the increasing demand for accessible healthcare to combat the occurrence of chronic diseases. Furthermore, the focus on better health, especially after the global pandemic, has made remote patient monitoring an impactful solution for improved healthcare.

How Does Remote Monitoring Help Healthcare Providers?

  • Big Data allows doctors and health administrators to understand more about their patients as a whole and on individual levels by collecting high-quality data to influence diagnosis and predictive health models. 
  • A.I & Data Analytics. AI assists medical service providers in predicting outcomes and making better data-based decisions for patients under their care.


Investment Trends in Continuous Remote Patient Monitoring Technology

The amount of capital invested and deal count for Remote Patient Monitoring solutions have been on an increasing trend in the previous decade. The amount of capital invested is growing at an exponential rate after the pandemic, reaching a peak of $2.14 billion. While the number of deals slightly decreased after the pandemic, this only indicates that the deal sizes for this technology have increased in value.

 For the period 2011-2021, The United States is the global leader in investments for Remote Patient Monitoring solutions, standing at $3 billion. Europe has a similar number of solution providers but only brings in $155.90 million in investments, suggesting investors’ perception be undervaluing these technological solutions. 

It has also been observed that earlier in the period, the majority of investments were coming in for earlier series (i.e seed or Series A & B). After the pandemic, later series (i.e C, D, E, & F) consists of the majority of investments for solutions in Remote Patient Monitoring.

The Emergence of Digital Twin Technology in Healthcare

Digital Twin Technology is an outcome of new technologies accelerating the creation of super-advanced “virtual twins”. These data-driven healthcare models can prevent numerous diseases and build more efficient healthcare systems. 

Digital twins, or the digital representation of human physiology, when combined with the power of big data of individuals and populations, provide a model for advanced tracking and modeling of the human body. This highly advanced technology is revolutionizing clinical processes and helping researchers to learn more about human diseases, new drugs, and medical devices. Digital twin technology will also enhance the performance of patient-specific treatment plans, saving countless human lives. 

Digital twin technology can also be utilized to represent the human genome and other psychological characteristics of a patient inducing the lifestyle of a human being. This way, it will allow doctors to discover the disease even before the patients start showing symptoms. Thus, it will help them provide earlier treatments, precautions, or an even better preparation for surgery.

As a result, the digital twin market was valued at USD 3.1 billion in 2020 and is expected to reach USD 48.2 billion by 2026, at a CAGR of 58.0% from 2020 to 2026 (MarketsandMarkets, 2020).

Digital Twin For Personalized Diagnosis

Digital twins allow collection and usage of vital data (e.g. blood pressure, oxygen levels, etc.) at the individual level, which helps individuals to track persistent conditions and, consequently, their priorities and interactions with doctors by providing basic information (Simsek, 2022). Thus, such personalized data serve as the basis of clinical trials and research data at labs.

In the healthcare systems, digital twins are the digital replica of the physical object or human body they represent. The main aim of these replicas is to provide monitoring and evaluation without being in close physical proximity. 

Implications of Digital Twin Technology

  • Understanding individualized risk factors. – A digital twin contains all the necessary details about an individual including their genetic profile, environmental information, interactions, etc. Therefore, it helps medical experts in making better predictions and preventing or preparing for future medical conditions.
  • More accurate and rapid diagnosis- With the help of a digital twin, doctors can synthesize data from already existing imaging records, lab results, and genetic information and diagnose previously known or unknown diseases.
  • Predicting responses to interventions. – Digital twins can also incorporate a patient’s pharmacogenomic data and help the doctors in suggesting an optical therapy. If there is a requirement for surgery, then doctors can use the twins to simulate procedures to devise the right devices and methodology for the procedure as well as predict a possible outcome.

Digital Twin technologies in Healthcare is still in the innovation trigger stage of the Gartner Hype Cycle. This emerging technology, only recently introduced, is a practical and impactful application in the healthcare space and is in the pursuit of some organizations. Gartner evaluates that it would take more than 10 years to reach the plateau of productivity. This is mainly due to societal barriers and ethical concerns with the widespread use of this technology (Panetta, 2021). 

Current Status of Digital Twin in Healthcare

Digital Twin technology in healthcare is still in the innovation trigger stage and even after the research, very few places have been successful in developing twins yet. For example, Linköping University in Sweden mapped mice RNA, for creating a digital twin and predicted the possible effects of treatment (Leifler, 2019). Essentially matching medicine with individual patient needs through quantitative analysis and computational algorithms. 

According to Gartner, it is estimated that it would take more than 10 years to reach the plateau of productivity. This is mainly due to societal barriers and ethical concerns with the widespread use of this technology. 

Another concern that restricts the market growth for the digital twin technology is the issue of hacking and viruses. Hackers can potentially gain access to private and valuable data and cause an irreversible amount of damage. That’s why the developers must take every possible step to ensure the technology stays in the right hands.

Conclusion and Final Thoughts

Hyper-personalization of healthcare services is crucial as health awareness increases in the general public due to widespread communicable and non-communicable diseases. These are the two emerging technologies that are key to enhancing the work of caregivers and physicians, leading to hyper-personalized health services: 

1) Remote Patient Monitoring devices – These devices provide an opportunity for healthcare professionals to take a Big Data approach when addressing patient needs, gaining insights on the change in patient vital health signs over time, and enabling inferences based on the change in treatment and environment, or behavior.

2) Digital Twin in Healthcare – It takes a further step in understanding how an individual’s health is impacted by its treatment, environment, or behavior. With simulation capabilities, the digital copies of patients could indicate the potential impact of these changes. Allowing for more efficient use of resources and time can prove significantly beneficial to a patient’s healthcare journey. 

Apart from enhancing the patient’s healthcare journey and ultimate outcomes, these technologies can alleviate the workload of healthcare professionals, providing them the bandwidth to focus on more meaningful work when the healthcare industry’s resources are scarce.

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Grandview Research (2019). Personalized Medicine Market Size, Share & Trends Analysis By Product, By Region And Segment Forecasts, 2019 – 2025. URL: https://www.reportlinker.com/p05807253/Personalized-Medicine-Market-Size-Share-Trends-Analysis-By-Product-By-Region-And-Segment-Forecasts.html?utm_source=PRN Accessed: July 14, 2022.

Leifler, K. S. (2021). Digital twins – an aid to tailor medication to individual patients. Linkoping University. URL: https://liu.se/en/news-item/digital-tvillingar-hjalpmedel-for-skraddarsydd-medicinering-.

Accessed: March 17, 2022

MarketsandMarkets. (2020).Digital Twin Market by Technology, Type, Application, Industry, and Geography – Global Forecast to 2026. MarketsandMarkets Research

Panetta, K. (2021). 3 Themes Surface in the 2021 Hype Cycle for Emerging Technologies. Gartner. URL: https://www.gartner.com/smarterwithgartner/3-themes-surface-in-the-2021-hype-cycle-for-emerging-technologies. Accessed: March 19, 2022

Simsek, H. (2022). Best Digital Twin Applications & Use Cases in Healthcare in 2022. AI Multiple. URL: https://research.aimultiple.com/digital-twin-healthcare/. Accessed: March 18, 2022

Turner, Stephen T. (2007). Personalized Medicine for High Blood Pressure. URL:https://www.ahajournals.org/doi/10.1161/hypertensionaha.107.087049 Accessed: July 14, 2022.

Wood, L. (2021). $85 Bn Remote Patient Monitoring Market – Global Forecasts from 2021 to 2026. ResearchAndMarkets.com. URL:https://www.businesswire.com/news/home/20210720005704/en/85-Bn-Remote-Patient-Monitoring-Market—Global-Forecasts-from-2021-to-2026—ResearchAndMarkets.com. Accessed: March 20, 2022


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