Healthcare has emerged as the light towards the end of the tunnel in times of unprecedented uncertainty. Today, many pharmaceutical companies are in a race against time to develop better vaccines, drugs, and treatment protocols. The past 18 months have led to the use of technology to spearhead innovations that will lead to better healthcare outcomes. Data, artificial intelligence (AI), and machine learning (ML) have all had a role to play in the changing fabric of healthcare and its subsequent evolution. Decision-makers were required to deploy critical technologies like AI on the fly to deliver better healthcare responses.
According to an Intel poll, the percentage of health IT decision-makers who had adopted or planned to deploy AI increased from 45 percent in early 2020 to 84 percent after the pandemic struck. Based on insights from Forbes and Healthcare Innovation, let’s garner a keener understanding of how data and AI are impacting healthcare.
Impact of Data
Patients’ data is being collected in greater quantities, but this raises privacy concerns. As telehealth grows more prominent, this trend is expected to accelerate. Doctors are using two-way technologies more than ever to provide healthcare remotely. Because of the rise of telehealth, both providers and patients now have greater access to data. Analyzing this data is difficult and needs modern technology, but it also opens up new possibilities. After examining clinical data, doctors can build more tailored patient treatment. In 2021, healthcare technology businesses will be more visible than ever before, thanks to the pandemic’s focus on data-driven solutions. Tempus, for example, is promoting precision medicine through the use of artificial intelligence in healthcare.
With tailored treatments, healthcare outcomes can be improved and the risk for side effects is mitigated to a great degree. There are many companies today that focus on genetic testing and offer data analysis to the doorstep of the customer. With genetic testing, it would be possible to determine a patient’s risk propensity towards a specific disease and make health as well as lifestyle changes in advance to prevent the onset. The notion of leading healthier and better lives can then be unlocked to a greater degree en-masse.
The rising role of AI
According to a 2017 Accenture analysis, the market value of health AI was expected to reach $6.6 billion by 2021, even before the pandemic. AI and machine learning are being leveraged by hospitals to enhance diagnoses, improve patient outcomes, and generate income. They can better predict dangerous illnesses, such as cancer, by applying AI technology to improve disease forecasts. Hospitals can also use AI to predict the risk of osteoporosis and anticipate which patients will get a specific cardiovascular disease. To avoid unnecessary hospitalizations, AI has helped hospitals manage capacity, screen COVID-19 patients, and target outreach to susceptible patients and communities.
As Covid-19 wreaked havoc on the planet, artificial intelligence (AI) became more crucial as a tool for developing prediction models for instances that were spreading across the country. Predictive techniques began tracking the infection and predicting the occurrence of significant symptoms. Machine learning has helped immunologists make new discoveries and develop Covid-19 vaccines. AI and machine learning will undoubtedly become more important in treatment procedures and clinical studies. AI has also reduced the administrative burden on clinicians, which has exacerbated burnout among doctors and nurses already stressed by the pandemic and costs the US $4.6 billion annually.
Better patient outcomes and lower costs are the consequence, which is essential at a time when 40 percent of acute care organisations are on the verge of collapsing owing to the pandemic’s financial impact.
The road ahead
AI is paving the way for better healthcare interventions and is enabling the pharma and Lifesciences industry to build more patient-centric business models based on data. In time, AI is expected to assist healthcare organisations in reducing the socioeconomic obstacles to care that contribute to inequities in health outcomes, resulting in a more egalitarian healthcare system.
