Published: Sep 08, 2022
how big data is shaping the future of healthcare?
A mere two years after the outbreak of the Covid-19 pandemic, the healthcare community developed effective vaccines, therapies, and diagnostic tools for tackling the SARS-CoV-2 virus, things that would have taken significantly longer, perhaps even decades, prior to the pandemic.
This was partly achieved by using artificial intelligence (AI) and machine learning (ML) to analyse large datasets. Pfizer said that “process and technology optimisations, including a new machine learning tool known as Smart Data Query (SDQ)” helped speed up data analysis in the company’s Covid-19 vaccine trial.
Meanwhile, Najat Khan, Chief Data Science Officer and Global Head of Strategy and Operations for Janssen Research & Development, the developers of the Johnson & Johnson vaccine, said that “Data science and machine learning can be used to augment scientific understanding of a disease. For Covid-19, these tools became even more important because our knowledge was rather limited. There was no hypothesis at the time. We were developing an unbiased understanding of the disease based on real-world data using sophisticated AI/ML algorithms.”
This is part of a wider trend towards digitalisation in the healthcare sector. By digitalising processes and harnessing the power of data, today’s healthcare institutions are building resilience and agility and driving innovation.
This data-driven approach is timely. With urban populations expanding fast and many healthcare institutions grappling with staff shortages, healthcare leaders need to fundamentally rethink how care is delivered. This includes taking into account the following questions:
- How can we optimise clinical operations with efficient allocation of resources and manpower?
- Are there other ways we can study and understand a patient’s condition besides live testing?
To address these questions, healthcare leaders need to understand the importance of big data and how it is enabling new health ecosystems that better meet the changing needs of clinicians, medical researchers, and patients. They need to be able to process large datasets and derive useful and timely insights from them through the use of AI-powered analytics. This will help them understand patients better, solve complex problems, and improve decision making.
An example of how this works in practice is the Appointment Scheduling Optimiser (ASO), a smart scheduling solution which NCS is developing in partnership with the Singapore National Eye Centre (SNEC). The first solution of its kind in Singapore, the ASO will transform clinic operations, reduce patient waiting times, and allocate manpower and resources more efficiently. It uses NCS NEXT’s capabilities in AI, advanced analytics, and ML technology as well as SNEC’s patient and operational data to perform optimal supply-demand matching, thus ensuring patient appointments are matched optimally with available clinical resources.
Healthcare and the Internet of Things
This begs an important question: where is all this valuable data coming from? There is a wide array of sources, including patient records, lab results, scientific literature, social media, and more.
However, it is the Internet of Things (IoT) that is arguably enabling the greatest possibilities in the area of data-driven healthcare services. Things like wearable devices and implantable transceivers deliver real-time or near-real-time health updates which healthcare institutions can use to provide “telemedicine” solutions. These solutions allow healthcare practitioners to monitor patients’ conditions, give consultations, and issue prescriptions remotely. They not only make it easier for people to seek treatment for illnesses, they also allow them to more easily maintain good health.
The global IoT medical devices market is growing fast. According to MarketsandMarkets, it was worth USD26.5 billion in 2021 and is projected to be worth USD94.2 billion by 2026. Consumer tech companies like Amazon, Apple, and Fitbit are increasingly getting in on the action. Deloitte Global says that 320 million consumer health and wellness wearable devices are expected to ship worldwide this year and that figure will likely hit 440 million units by 2024 as new offerings enter the market and healthcare providers become more comfortable with using them.
As the market expands, connected medical and wellness devices are growing more advanced. The Apple Watch, for example, can monitor the wearer’s blood oxygen levels and take electrocardiogram readings and, according to Bloomberg, future models will include features like body temperature and blood sugar sensors.
If healthcare providers are able to properly capture and process the wealth of data generated from IoT medical devices, they will be able to understand their patients better and thus offer more accurate diagnoses and improve treatment outcomes.
Taking healthcare to the next level with big data and AI
Harnessing AI is now top of the agenda for decision makers, investors, administrators, and innovators in the healthcare sector. The United States currently leads the way, with more completed AI-related healthcare research studies and trials than any other country as of 2020, according to a report jointly released by EIT Health and McKinsey. However, “the fastest growth is emerging in Asia, especially China, where leading domestic conglomerates and tech players have consumer-focused healthcare AI offerings and Ping An’s Good Doctor, the leading online health-management platform, already lists more than 300 million users,” the report notes.
This increasing emphasis on AI goes hand in hand with an explosion in the amount of health data that is available through IoT devices. Moreover, more regulators around the world are now requiring healthcare providers to maintain a longitudinal health record for each patient comprised of data generated from all the patient’s interactions with the healthcare system. Singapore, for example, has created a central repository for healthcare data sourced from various institutions and players in the healthcare ecosystem.
With this data at their fingertips, authorised providers are able to make faster, more accurate diagnoses and deliver personalised long-term care plans for patients. This is helpful in supporting initiatives such as the Healthier SG initiative in Singapore, which aims to shift the focus of Singapore’s healthcare system from treating illnesses to keeping people healthy and thus, as far as possible, preventing them from getting sick in the first place.
Big data and advanced analytics capabilities have proved to be crucial in efforts to curb the spread of Covid-19. As part of Singapore’s Covid-19 contact tracing efforts, NCS created a digital solution called NCS OneShield which collects health status and contact tracing data through crowdsourcing, and uses relevant data to help organisations easily stay informed about the latest health status and movement of unwell employees. With this solution, a business can perform organisation-wide risk monitoring, place staff on quarantine if need be, and tackle the spread of the coronavirus within its own workforce.
Powered by cloud technology and advanced analytics, NCS OneShield allows users to determine which teams have the highest number of staff on medical leave, and if containment of that business unit needs to take place. A real-time analytics dashboard also makes it easy to spot and predict trends in staff behaviour so that a predictive disease response plan can be quickly initiated to prevent infections across the workplace.
The need for data governance
As healthcare institutions leverage increasingly large and complex datasets, it is vital that they ensure that the data is up to date, accurate, complete, and free of bias. Failure to do so will have an adverse effect on decision making.
As Goh Han Leong, Principal Specialist, Data Analytics & AI, IHiS said in an interview with GovInsider, “Poor data quality or understanding of the data collected will result in a garbage-data-in and garbage-insights-out situation. To respond to the data opportunities, we should also invest in building a trusted shared platform that has good data provenance and lineage.”
The Artificial Intelligence in Healthcare Guidelines (AIHGle) published by Singapore’s Ministry of Health (MOH) last year note that AI “amplifies existing process and data risks, and creates new accountability and algorithmic risks which, if not managed systematically, may lead to poor patient outcomes and erode clinician and patients’ trust in the use of AI – limiting the potential benefits of the technology.”
The intent behind the AIHGIe is to “improve the understanding, codify good practice, and support the safe growth of AI in healthcare.” The guidelines are underpinned by the understanding that AI should be deployed with fairness, responsibility, transparency, explainability, and patient-centricity. In addition to ensuring that the quality of their data is good, healthcare institutions need to take steps to protect the privacy of patients. This means putting in place strong cyber-security and data protection measures. As the AIHGIe points out, data protection includes things like anonymising data and applying privacy-enhancing technologies such as homomorphic encryption during data analysis and modelling.
Adapting to the rapid rate of change
As cutting-edge technologies and advanced capabilities like AI-powered data analytics become more widespread in the healthcare sector, it is important to ensure that all staff are kept up to date with the latest developments. According to a report by Elsevier, “clinicians identify education and training on the latest technical developments as a key priority for the next 10 years.”
Healthcare organisations will need to foster a culture which supports the use of digital technologies, with leaders communicating the need for such technologies to all levels of their organisation. Moreover, they should ensure that digital solutions are implemented with flexibility and scalability in mind to ensure that they remain effective over the long term.
From aiding drug research and development to streamlining appointment scheduling, there are numerous ways data and AI can improve the healthcare sector. Advanced data analytics is making it possible for healthcare institutions to provide more personalised care, thereby allowing them to shift their focus from treating illnesses to helping individuals maintain good health.
While these developments are welcome, healthcare leaders must make sure they keep patients front and centre in their digital transformation strategies.
As Lim says, “It’s an exciting time for healthcare technology and the possibilities that lie ahead will have many leaders racing to make things happen. But it’s important to always keep care and the patients at the very heart of any innovation and development.”