The age of big data

Big data analysis helps to deduce evidence-based information to improve efficiency, reduce healthcare delivery costs, says Vikram Thaploo

Vikram Thaploo, Digital health trial, Big data analysis, Cutting-edge technology, Telehealth, Apollo Hospitals Enterprises Limited, Apollo Hospitals, Healthcare, Public health data, Reduce healthcare delivery costs

The advent of digital technology and digitisation of healthcare-related information has given us unprecedented access to a large reserve of data. We are sitting over a data field that when processed can provide valuable insights into disease incidence, progression and treatment outcomes and even help us predict disease epidemics.

Big data analysis helps us deduce evidence-based information to improve efficiency, reduce healthcare delivery costs and arrive at best practices to treat a disease. It can also give a huge boost to clinical research and precision drug development. Market research indicates that the global big data analytics in healthcare market size which was valued at $ 16.87 billion in 2017, is projected to reach $67.82 billion by 2025. This accounts for a growth of a CAGR 19.1% from 2018 to 2025.

The industry is already processing over 30 billion transactions a year by producing zettabytes of data taken from EMRs, medical imaging, medical devices, etc. Much like in many other industries, this tool today is being used to revolutionise healthcare, improve service delivery, structure the research, enhance diagnosis/imaging results, and generate patient data outside clinical context, behaviorual data, wellness information, environmental data and public health data. All of these constitute a patient digital health trial.

Here is how big data is revolutionising healthcare:
Cost reduction
At the industry front, big data enabled technology has made life easier for medical personnel by allowing cost-effective methods of testing and diagnosis through online and mobile applications. Its usage is proving to be highly useful in remote healthcare, which helps medical practitioners monitor their patients without necessarily seeing them every day. Remote healthcare cuts the costs needed for being physically available, and regular in-clinic visits save time and energy both on the part of the doctor and patient.
By cutting down on overhead costs, rentals, inventories, and etc., remote healthcare enables medical institutions to earn better profits and use the same for extensive medical research.

Disease prevention
With improved understanding of communicable diseases and rising incidence of non communicable diseases, there has been a paradigm shift in healthcare management towards prevention. Several vaccines have been developed to prevent deadly diseases. The health education system has taught preventive lifestyle measures as the line of defence against modern lifestyle-induced diseases.

The digital devices that enable you to keep a regular check on your vitals, use data to push people towards healthier lifestyles are widening possibilities for the prevention of diseases. The same data when processed and analysed can be utilised to identify risk factors for the disease at population, subpopulation, and individual levels.

Effectiveness and quality of treatments
Big data has proven effective in earlier disease intervention, reduced probability of adverse reaction to medicines, and fewer medical errors. It is also helping the healthcare professionals and researchers to derive trend analysis of a particular disease profile and enhance the treatment impact. In the current scenario, 50% of the treatment is determined before patient visits using the data available with the clinician leading to better quality and quicker treatment. The data also helps the caregiver to determine casualties and understand the co-morbidities.
The historical data of a patient plays a crucial role in big data. Digitisation of patient data makes the system reliable and accessible for immediate use. Critical factors like genetic disorder and other warning signs can be tested, and health check-up packages can be customised to a patient.

Easing health-related research
Such a wide variety of useful data helps researchers to analyse and hypothesise findings, customised to a community, area, or group of people. The same results can then be related to factors such as air pollution, water-borne diseases, increased use of pesticides, disease transmission pathways, infectious and chronic diseases, etc.  These researches have been conducted in the past but were restricted in numbers. Big data can bridge this gap and enable researchers to conduct mass surveys and analysis.

The convenience of service
Convenience experienced by the potential patients and healthcare institutions are the significant benefits of this cutting-edge technology. The access of analysers to pick from available data and provide to the patient-relevant to them in a matter of few minutes is remarkable.

Individuals now can avail consultations with the doctor through mobile applications specifically designed to address their queries as well as connect them to their respective caregiver for test and check-up reminders.

Challenges and the way forward
Health data has grown dramatically, thanks to increasing penetration of Internet, lowering storage costs and greater Government encouragement to creating digital health information systems. Widespread availability of handheld devices and self care health applications have enabled patients to proactively manage their own health and also paved way for a large amount of data. However, structural obstacles lie ahead for big data and healthcare.

Significant challenges include technical skills required, the ability to ensure compliance with all security measures, privacy, and patient confidentiality.

The future lies in the use of AI/ML backed by big data to provide a predictive and analytical approach. AI uses machine learning and can deliver capabilities to predict the future condition of a patient based on early warning signs. It can also determine the best operational management practices and recommend prescriptions based on the treatment of a similar patient. AI/ML requires human intelligence to steer as a partner in patient care.
It will need an efficient combination of people, tools, data, and resources to leverage advanced technologies and usher in exciting breakthroughs in inpatient care.

HRE3KGNd4P Vikram Thaploo is CEO of TeleHealth at Apollo Hospitals Enterprises Limited.