Despite the pandemic, significant progress has been made in the last two years. Nonetheless, the Healthcare Industry currently faces significant obstacles in a number of areas, including digital health repository, capacity-building in health research, genome sequencing, and epidemic forecasting.
With data and technological skills and strategic alliances, the healthcare business can analyze large amounts of data to obtain the necessary insights for future-readiness. Healthcare organizations are currently redefining how they utilize data, make clinical and operational decisions based on data, enable precision medicine, and reduce the cost of healthcare.
Using Artificial Intelligence (AI) and Deep Learning approaches to develop innovative medical devices
Companies such as NeuraLink (a project to synchronize the human brain with artificial intelligence) can heal a variety of neurological illnesses, such as restoring sensory and motor function, and enable people with paralysis to control computers and mobile devices quickly and easily.
Deep Learning for diabetic retinopathy detection
Google AI is collaborating with physicians and academics to examine the complete eye screening procedure in order to integrate deep learning models into clinical workflow and aid in the treatment of diabetic retinopathy. If left untreated, this condition might cause severe eye damage.
Vaccination and supply chain administration
Supply Chain Analytics strives to improve vaccine programs, supply, and delivery, as well as guarantee universal access to all important vaccines for all people throughout their life course. WHO’s supply chain tools, such as the Cold Chain Equipment Inventory and Gap Analysis Tool, the Immunization Supply Chain Sizing Tool, and the Vaccine Volume Calculator, facilitate the storage, transport, and distribution of vaccines.
Developing pharmaceuticals using sophisticated analytics
The most important aspect of drug research is testing possible new medicines on humans. Effective vaccine research and clinical trials contribute to the development of safe and effective human medications and vaccines. Through sophisticated analytics, the medical field is able to integrate and evaluate large data sets from various aspects of clinical trials, including genetic indicators, clinical signs, symptoms, and treatment responses.
Creating the conditions for more effective and tailored medications
Historically, the majority of medical concepts are derived from observations of a few hundred to a thousand individuals. However, the advent of digitization, abundant computing capacity, and cutting-edge machine learning models will enable the formulation of principles based on the observations of a much wider population, resulting in the development of more effective and individualized medications.
Despite developments in the Healthcare Industry, significant obstacles must still be resolved.
Cybersecurity Implementation and Global Cybersecurity Laws
Patient health records typically contain a tremendous quantity of personal and sensitive information. Health care in the United States is governed by HIPAA (Health Insurance Portability and Accountability Act of 1996) The National Cyber Security Policy (2013) of India ensures the safety of the cyberspace ecosystem. The Worldwide Cybersecurity Index (GCI) 2020 released by the United Nations (UN) agency-International Telecommunication Union (ITU) puts India tenth in terms of its commitment to cybersecurity on a global scale. This index serves as a reliable benchmark for measuring countries’ cybersecurity efforts. The difficulty in the healthcare industry is that the technologies used to develop healthcare services must comply with worldwide cybersecurity rules to ensure data security and sovereignty by offering secure infrastructure, control over personal data, and encryption.
Data Localisation and Data Compliance
Countries are increasing their protection of their residents’ data and imposing limits on the transmission of data across borders. Globally, data localization rules are implemented, which refer to policies dictating how data on a country’s residents is gathered, processed, and stored within the country. Cloud Geo-partitioning and local data hosting will aid compliance with data residency rules. In addition, they will increase data security by ensuring compliance with applicable laws.
Understanding natural language and machine learning
According to the Central Intelligence Agency (CIA), just 45 percent of the world’s population speaks English as a first or second language; more than a million people are native speakers of more than 400 languages (2018). For a healthcare product to be easily accessible, it must be usable in the user’s preferred language. Companies must invest in machine learning and artificial intelligence to improve their language comprehension and create models utilizing Deep Learning Techniques to accommodate several languages, be accessible to all ecosystem participants, and promote health equity for various populations. Implementation of online translation tools such as Google Translate and MediBabble in hospitals increased the satisfaction of both medical providers and patients (to 92 percent) and improved communication, the quality of healthcare delivery, and patient safety, thereby overcoming language barriers that make the delivery of high-quality healthcare extremely difficult.
Employing Multiple Cloud Data Services
Utilizing a contemporary, multi-cloud data stack, the healthcare business must give meaningful insights. COVID-19 Insights are derived from the Aarogya Setu Application, which uses Amazon Web Services (AWS) and Google’s Firebase analytics. Moderna, a maker of vaccines, utilizes AWS and Looker for analytics.
The size of the global cloud database market is expected to reach $68720 million by 2026, up from $7054.4 million in 2019, at a CAGR of 38.2% between 2021 and 2026. (From: Evaluation of reports)
The healthcare business should enable a Digital Health Ecosystem, construct a Unique Health Cloud Lake to give an Integrated Health Information Portal, and develop a Health Account Key containing information on diseases, diagnostics, reports, and medications.
Dashboards for business intelligence should be utilized
Globally, about 90 percent of R&D departments believe Cloud BI is essential for current and future industry projects. Cloud BI usage is currently highest in Manufacturing (58%), followed by Financial Services (40%) and Business Services (6%). (40 percent ). (Source: Dresner Advisory Services’ 9th Annual Report on the 2020 Cloud Computing and Business Intelligence Market Study)
Business Intelligence enables healthcare practitioners to access patient data, give more accurate care, anticipate future health risks, execute preventive therapy, and improve future patient health outcomes in real-time. Managing a vast array of data, such as medical records and insurance delinquencies, is hampered, however, by complex rules. With on-premises and cloud solutions that can be evaluated in safe environments, Data Analytics makes it possible to uncover the potential connections between all of this data. In addition, using Cloud Intelligence facilitates the long-term storage of huge volumes of data that may be utilized for analytics.
Developing Healthcare Products and Services have to involve an integrated strategy. National Digital Health Blueprint can generate nearly $200 billion in added economic value for the health sector over the next decade.
Advanced Analytics and AI can compensate for a lack of human resources to diagnose and provide treatment protocol guidance. Machine Learning algorithms can be used to interpret CT images and X-rays, saving radiologists time. By analyzing vast amounts of data, it can also predict disease outbreaks and epidemics, improve universal health coverage, enhance healthcare delivery, and provide the healthcare industry with better insights and tools to address health emergencies and safeguard people worldwide.