Nirmalya Gupta, MD and Dhrubabrata Ghosh, Director, Protiviti Member Firm for India highlight how adoption of these disruptive technologies in healthcare will help in critical decision making as well as improve patient management and treatment outcomes
The data management landscape in therapeutic research within the healthcare delivery in India is set to undergo radical changes in the near future. Whilst it is still at a nascent stage, some developments have already been initiated and the pace is set for acceleration very soon. Major hospitals, healthcare providers, pharma giants and R&D centres are utilising big data and predictive analytics in their critical decision making. Clinical developments, real-time alerting, telemedicine, 3D printing and use of real time data in clinical trials are some of the changes that are happening within the industry. Many healthcare providers are using electronic health records to develop databases for interoperability and future use. A premier healthcare provider in India has already embarked upon the journey of utilising artificial intelligence (AI) capabilities in patient – management, clinical prescriptions suggestions and patient health predictions. Another major provider is currently in partnership with Microsoft to create an AI-focussed network for cardio related diseases. With the development of these AI tools and real world data, the provider will be able to gauge risk of heart diseases in patients at an early stage in hope of preventing or reversing these life-threatening conditions. Some of the healthcare providers have started using IBM Watson Health for disease identification and drug prescription.
The use of data and other disruptive technologies are still at a relatively nascent stage in the Indian healthcare industry as mentioned above. However, active participation of the major players and cohesive partnerships with the global IT leaders definitely hold great prospects for the future of the healthcare industry. At the current pace of development, substantial increase in the investments and support from government,we are very hopeful that use of data and technology in therapeutic research within the industry will hugely evolve over the next three to five years.
Data analytics to show maximum growth in following key areas:
- Clinical development: R&D centres and pharma clients are analysing Big Data for new drug or investigational products testing to reduce the cost of trials and running simulations. Use of data driven predictive models and statistical tools is improving the clinical trial success.
- Prevention of drug abuse: Developed countries are using Big Data to tackle the problem of overdose or misuse of opioids. Data scientists are working with health insurance service providers to develop predictive models where individuals are analysed on the risks that they are carrying based on a universe of critical healthcare-related risk factors.
- Improved staffing: Hospitals are hiring data scientists to crunch admission and time data using ‘time series analysis’ techniques and building predictive models for charge ability and admission for nurses, doctors and paediatrics.
- Drug management: Healthcare providers, along with the government, are connecting their inventories with the prescribed drugs at a real time basis to monitor drug usage and shortfall. This helps them in effectively managing the stock across multiple locations.
- Real-time alerting: Healthcare providers are utilising the capabilities of clinical decision support software and AI focussed networks to analyse patient health records and real-time medical data to provide insights to the practitioners to take critical decisions.
- Prospective cure of cancer: Medical researchers are using the data on patient treatment plans, recovery rates and symptoms of cancer patients to predict treatments that have the highest rate of success in real life scenario. This is still in a developing stage. However, the Cancer Moonshot Programme in the US is a definite indicator of what the future that lies ahead of us.
- Telemedicine: This term has been present in the market for over 40 years. However, with the current technology and IoT, it has been able to come into full bloom. The primary consultations, initial diagnosis, remote patient monitoring and real-time consultations are the current benefits of Telemedicine technology.
- Lifestyle analytics: The proposed system will provide healthcare solutions, based on various models to analyse the lifestyle of individuals and provide useful insights to prevent medical accidents and emergencies and increase the accuracy towards patient treatment.
- Outbreak analytics: In case of outbreaks such as dengue, H1N1, Zika and other diseases, it becomes imperative to identify the origin of the disease for the effective management of the same. Analysing huge amount of client and demographic data and connecting multiple data points to perform link analysis holds the key.
In the past few years, life sciences companies have made massive investments in commercial analytics.
In 2020, brand leaders will continue to invest in infrastructure to achieve truly prescriptive analytics. For many teams, rapid experimentation is the critical capability needed to translate insights into action.
- Extensive use of AI in life sciences and healthcare industry
- Neuro-linguistic programming tools and capabilities for effective patient management and medical value creation
- Block chain capabilities with wearable technologies and telemedicine for secured data pooling and analytics
- Genomic analytics for more cost-effective and efficient gene sequencing
- 3D printing for prosthetics and tissue engineering
There are a number of challenges in AI or similar technologies across the industry. Companies are struggling with issues pertaining to data quality, availability, storage, access, integration, privacy, security, retention, and management, complexity of the AI and block chain tools and limited talents in these areas. Specific challenges could be further articulated as below:
- Electronic Health Records (EHR): High costs, functionality and security are the major concerns while implementing the EHR based system.
- Real-time alerting: Lack of infrastructure and regulatory compliances across the countries are the roadblocks faced for implementing Real-Time Alert System.
- Telemedicine: High-costs and acceptance from society are the major hurdles in implementation of telemedicine.
The global scenario
The healthcare sector is booming at a faster rate globally. According to an International Data Corporation (IDC) report sponsored by Seagate Technology, it is found that Big Data is projected to grow faster in healthcare over other sectors like manufacturing, financial services or media. It is estimated that the healthcare data will experience a compound annual growth rate (CAGR) of 36 per cent through to 2025. Effective use of Big Data could add $300 million per year to the healthcare industry.
Microsoft has also taken an initiative to accelerate healthcare innovation through artificial intelligence and cloud computing. Microsoft is working with the market pioneers to develop innovative tools for healthcare, biotech and life science. They have further announced a number of solutions, projects and AI accelerators that contributes towards intelligent healthcare such as Microsoft genomics, Microsoft azure security, and AI networks, Microsoft 365 huddle solution templates, Project Empower MD and Project Inner Eye. Many healthcare providers, medical research societies, Biotech companies and pharmaceutical organisations are working side by side with Microsoft to take the full advantage of Big Data and these emerging technologies.
Apple also sees healthcare and wellness as core part of its wearable ecosystem and is partnering up with many healthcare providers, pharma companies and insurance organisations to provide better health solutions to the general public.
IBM Watson Health is providing solutions in the areas of cardiology, oncology, medical research and pharmacy etc. With a base of over 13,000 partners and clients, IBM Watson is creating meaningful change in health. Healthcare is witnessing a new wave of transformation globally. Increasing competition, investment and disruptive technologies will further evolve the general public healthcare and medical research. Healthcare data analytics will help the market contributors and government to make better informed decisions ultimately benefiting the society.