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Health

Hyper-Personalising The Digital Health Experience

Hyper-Personalising
THE DIGITAL
HEALTHEXPERIENCE

Overview

Customers today are more informed and technology-abled than they were a few years ago. Moreover, the COVID-19 pandemic has transformed how most businesses and industries function, including healthcare. Despite the global disruption the pandemic caused, it has demonstrated that adopting data-centric, digitally-driven business models can help organisations become agile and resilient to unforeseen crises. In particular, the pandemic has been a ripe opportunity for the healthcare industry to reset its operations.
On the one hand, the virus has exposed the pitfalls and limitations of the global healthcare system. On the other hand, it has accelerated advancement towards data-driven and future-proof healthcare experiences through hyper-personalisation. Let’s look at how the digital health experience is getting a makeover through hyper-personal care.

Hyper-Personalisation in Healthcare

Healthcare systems and providers that oer hyper-personalised experiences develop an N of 1 or single subject profile of each customer. They do so by collecting, collating, and analysing consumer data in a way that views each customer as a unique individual rather than a generic population segment. As a result, healthcare institutions can customise their marketing and communication strategies to cater to the individual needs of patients and customers while delivering proactive and personalised care plans.
In the healthcare context, hyper-personalisation entails the development of patient-specific treatments and medical amenities. It combines digital technologies, big data-driven predictive analytics, genomics, proteomics, and metabolomics to deliver targeted and tailored healthcare products and services to consumers.

Components of Hyper-Personalised Healthcare

The hyper-personalised care infrastructure has three fundamental constituents at its core that enable healthcare providers to create personalised digital experiences. These components are:

UnderstandingUnderstanding
the Consumer

Healthcare providers collect the target consumer’s data, including medical history, decision-making patterns, communication preferences, social and cultural determinants of health, etc. The aim is to build a data architecture that perceives the customer as an individual with unique needs.

RecognisingRecognising Individual Needs

This component aims to enhance the consumer’s engagement with the healthcare system by creating tailored experiences. For instance, identifying the best channels to connect with the consumer, recognising the requirements for the patient’s wellbeing, and so on.

PersonalisingPersonalising
Care

The final component involves setting up personalised care touchpoints by predicting and addressing the patient’s healthcare needs and offering proactive and timely measures to mitigate instances of acute care. Personalising care also calls for simple and seamless navigating through multiple care touchpoints and customising care pathways for individual health needs.

Drivers of the Digital Health Ecosystem

Although the concept of digital healthcare services has been around for a while, it is worthwhile to look at the key drivers of the digital health ecosystem.

  • Healthcare DataHealthcare Data

    The burgeoning volume of healthcare data presents an ideal opportunity to integrate an individual’s personal health information and develop a hyper-personalised approach to health and wellness.

  • Global mobileGlobal mobile
    Health Market

    The global mobile health market is estimated to reach a valuation of US$ 189 billion by 2025. With increased access to smartphones and the internet, mHealth apps have become people’s preferred choice for virtual consultations, health data monitoring, buying medicines, etc. The increase in usage of digital health tools on the go reflects people’s trust in various digital health channels.

  • McKinseyAnalysis by McKinsey

    A 2021 analysis by McKinsey revealed that virtual consultations have increased 38 times since 2019. The use of electronic health records (EHRs) also witnessed a rise, with 31% using EHRs in 2021. These figures suggest that more and more people are welcoming digital healthcare experiences.

  • EvolvingEvolving and emerging
    technologies

    such as the Internet of Things (IoT), artificial intelligence (AI), and 5G have the potential to transform the digital healthcare experience radically. From sensors monitoring social distancing to AI aiding drug discovery, these technologies served at the frontline during the peak pandemic phase. It is estimated that the global market size for AI in healthcare will surpass US$ 28 billion by 2025.

  • McKinsey ResearchMcKinsey Research

    As per a 2021 As per a 2021 McKinsey research, about 40% of survey individuals expressed interest in continuing telehealth in the future, up from 11% in the pre-pandemic era. The figure shows the increasing inclination towards contactless healthcare assistance. It should drive healthcare providers to deliver value-added services by collecting consumer data, diversifying digital health channels, and enhancing patient engagement..

The Reality of Hyper-Personalised Healthcare

A data-driven future for the healthcare industry is inevitable. Below are two notable instances of hyper-personalised healthcare that can potentially change the fate of the sector.
The use of predictive analytics in early diagnosis and disease detection plays a crucial role in biomedical research and the development of personalised medicine.
The advancement in drug manufacturing techniques, 3D-printed surgical implants, clinical science, and genomics has accelerated the development of personalised medicines, therapies, and treatments. CRISPR engineering and genome sequencing are currently two promising candidates with the potential to lead the hyper-personalised medicine revolution. The gene medicines could be in the form of gene editing, gene replacement, or antisense oligonucleotide therapy, to name a few. 3D-assisted surgeries are another example of patient-specific treatment.

Conclusion

The global personalised medicine market size is forecasted to reach a whopping US$ 5.7 trillion by 2030, a figure that’s enough to highlight the remarkable advancement of the sector. The availability of big data, the evolution of machine learning and AI, and the rapid adoption of electronic health records across healthcare systems have been the key drivers of this growth. Healthcare providers can make more-informed care decisions and customise patient treatment plans with round-the-clock and real-time access to patient data and state-of-the-art technologies.