Data-Driven Healthcare Innovations: Trends & Challenges

It’s no secret that the pandemic forced healthcare institutions across the globe to digitize – and fast. From telemedicine to remote monitoring, to AI-powered data processing and cutting-edge research, we are witnessing unprecedented development in the health technology field.

The rapid digitization has created even more data for healthcare providers and health tech companies to use to drive outcomes and innovations. And this isn’t slowing down any time soon – it’s estimated that the volume of health data created annually will grow by 48% year-over-year.

As such, the data-driven innovations spawning for the healthcare sector are many, including remote monitoring, nanotechnologies, and augmented reality. As further technologies emerge, however, the need for high-quality, clean data rises too. This presents complex challenges for an industry characterized by heavy data protection controls and cybersecurity attacks.

In this blog, we’ll explore the top trends in health tech innovations right now, the challenges being faced in the sector and a look ahead for the future of the health tech landscape.

Top Data-Driver Innovations in Healthcare

Healthcare is facing a new frontier of technology innovations that hold huge promise to deliver better patient outcomes and empower healthcare provider decision-making. Here are my top picks of the innovations out there right now.


Nanotechnology, which involves applications of nanoparticles to make repairs at the cellular level, is already leading to notable outcomes in healthcare. Scientists are using this technology to improve drug delivery systems and medical imaging, as well as to combat tumors. In fact, the nanotechnology market size is set to reach almost $291 billion USD by 2028.

One company leading the way in this field is Verily, which is developing nanoparticle libraries to support drug delivery. The company’s nanoparticle R&D program includes a scalable platform for “synthesis, characterization and high-throughput screening of particles with predictable physicochemical properties."

IoT-Powered Monitoring

IoT devices are on the up in the healthcare sector, and are currently being used for remote patient monitoring – an essential tool for a world still gripped by the COVID-19 pandemic. This technology is becoming so widespread that 53% of US hospitals have a remote patient monitoring system. What’s more, McKinsey predicts that human health will make up 10-14% of IoT’s estimated value by 2030.

Shanghai Public Health Clinical Center (SPHCC) reported that it is using IoT tech and wearable sensors to monitor the body temperature of COVID-19 patients, reducing the risk of exposing caregivers to the virus. As well as keeping tabs on patients with COVID without the risk of physical interaction, applications of remote monitoring using IoT include continuous blood glucose monitoring, treatment of sleep apnea, and tracking vital patient data from the ambulance to the hospital.

People are even taking IoT into their own homes to closely monitor their children’s health and habits. Lumi by Pampers is an all-in-one connected baby care system that gives parents and carers a real-time view of their baby’s sleep, feeding, and diapering patterns – all through an app.

Data Analytics

Data analytics and AI are helping to push forward multiple innovations in the healthcare industry, one such example being driving drug delivery. Lucas Pye Bio is reducing the time it takes for drugs to be released using AI and business intelligence.

The company does this by fast-tracking the clinical development of biologics for regulatory approval, manufacturing the biologics at lower costs than the market price, and accelerating drugs into the commercial global market.

AI and data analytics are also being used in precision medicine, as the increasing availability of clinical data and molecular profiling technologies are helping to speed up cancer research. A study published in the Journal of Clinical Oncology Clinical Cancer Informatics shows that researchers could use a big data analytics tool that is able to mine large datasets to identify patterns in treatment options and accelerate precision medicine.

Another example of a health tech company using AI to fight cancer is Vara, which is developing algorithms to screen for breast cancer, using a data set of 2.5 million breast cancer images for training, validation, and testing.

Augmented Reality & Virtual Reality

While they may sound like futuristic technologies, augmented reality (AR) and virtual reality (VR) are already making headway in the health tech sector and driving innovations. AR and VR are providing solutions in education, surgical visualization, physical therapy, and more.

One such example comes from surgeons using AR and VR to evolve their skillsets for advanced medical procedures. VR tools allow surgeons to train and create muscle memory without any risk to the patient – resulting in faster procedures and fewer mistakes.

The Biggest Challenges of Data-Driven Healthcare

Building and leveraging health tech solutions is no simple task, especially in an industry where data protection is a top priority and access can be restricted.

One of the biggest challenges while creating data-driven health tech innovations is data management and handling. Moving, manipulating, and managing health data is a complex task – and without properly managed, accurate data, technology solution providers risk producing unreliable results and creating biases.

Much of the health data that could be used to power technologies is not yet cleaned or correctly formatted. Capturing data that is clean, accurate, comprehensive, and formatted precisely has been a challenge for many organizations. In many cases, it’s also important for this data to be standardized and integrated from multiple sources. Inconsistent data entry into electronic health records (EHRs), however, produces inaccurate datasets.

Tony Scanio, a data management and business intelligence director at a leading multinational health system based in the US, highlights this challenge within his organization.

“One of the biggest challenges we have right now with our data is a standardized way to identify our products across borders. We know that the same multi-national companies are present in all of the countries where we operate, but matching those items across borders has proven to be a challenge,” says Scanio.

“We are very interested in utilizing a standardized device identifier, such as a GTIN (Global Trade Item Number), in our supply chain operations. This GTIN would help resolve various issues we face, as well as will allow us to start more in-depth analyses to track clinical outcomes with supply chain activities,” he explains. This would help his team operate in countries where there are no government-mandated data quality standards and no overall market adoption of those standards.

Healthcare datasets continue to be a top target for hackers, so it’s crucial that health tech companies and providers adopt advanced security practices to prevent costly data leaks. While 91% of respondents to a recent KPMG survey predicted that AI could increase patient access to care, 75% believe AI could threaten patient data privacy. So it’s no surprise that HIPAA indicates almost 18 components of personal health information (PHI) that must be ensured.

As such, a challenge for health tech providers is gaining access to the data they need to power their R&D and solutions, which is often inaccessible in order to protect personal patient information. Without any central sharing mechanism, however, a lot of data that could facilitate large-scale research or big data methodologies is unavailable for use. To combat this, players in the health tech sector must find a way to eliminate the core PHI components while still making data valuable for analysis.

Looking Ahead to a Data-Driven Healthcare Industry Innovations

In order to continue to drive advancements in big data and AI and help build the innovations of the future, healthcare institutions and technology partners must come together to ensure proper data quality and handling. This means leveraging data management solutions to drive data quality. They should also adopt security measures such as authentication protocols, transmission security, controls over access, and auditing to best ensure data security.

And when looking to AI to help drive decision-making, healthcare providers should remember that the technology is there to augment their own intelligence, not replace it entirely. With proper data management in place, who knows how long it’ll be before we see futuristic innovations such as VR telemedicine or widespread embedded devices!

Healthcare is providing a new frontier for data-driven innovations that have the power to drastically improve health outcomes for people across the globe. Faced with challenges around proper data management and standards, it’s essential that healthcare providers and technology partners come together to build a system that both protects and secures data while facilitating further innovations.

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