The Future of Employee Experience for Tech Companies Following the Pandemic
nThrive Insights: What the Future Brings for the Healthcare Industry
Nowadays, all industries have to adapt to the disruptive force of artificial intelligence. Recently we spoke with Jill Sutton, VP of Talent Development at nThrive, about how AI-based innovations will affect healthcare. She believes that they will spread widely over the next 10 years in the industry. Predictive analytics software, helping to establish the culture of personalized medicine, and training simulations, allowing medical workers to practice new skills in real-time and gain immediate feedback, will change the way the industry functions. Let’s talk about predictive analytics first. What is it and how can it transform healthcare?
Predictive analytics will bring data-based insights about patients’ diagnosis and prescriptions
The core technology of artificial intelligence lays in machine learning algorithms. These algorithms process large data sets, then select and define different patterns through data analysis and make predictions about the possible outcomes of particular events. For healthcare, it means analyzing different patients’ data and interpreting them in order to gain valuable insights into treatment approaches and their possible outcomes. These predictions will be used as the source of personalized treatment or therapy decisions for patients, which will improve patient care and even allow medical specialists to prevent illnesses. For instance, the studies on predicting whether a patient is at high risk of having a heart attack exist already.
However, in order to apply predictive analytics to the workflow of healthcare institutions, they’ll have to overcome a few challenges. Hospitals have to use functional electronic health records (EHRs)—basically, a big library with information about patients—and integrate them into software that will perform real-time or offline data processing to monitor patients, for instance. Aside from the technical complexity of such software, a challenge arises when hospital employees are trying to get used to it. Jill says that “due to increased use of technology, there will be an increased need to improve communications, coaching, and building trust and relationship” between medical workers and patients. The success of adoption also strongly depends on work culture: if an institution has flexible, learning-oriented leadership, predictive analytics will bring great value to its medical workers and patients.
Comprehensive training is a must for adopting predictive analytics and other AI-based tools
Training is vital for the successful adoption of any new solutions, and in that case, healthcare will need to use it to help medical workers use new predictive tools for personalized medicine. Jill says that even in healthcare, formal education will be less important than self-training and corporate training soon. She believes that to unleash the utility of new technical tools, training managers and mentors will need to become facilitators, not teachers. Their goal will lie in helping workers use the collective knowledge of the organization and meeting these workers where they are, speaking a common language with them. She says that nThrive itself “is hoping to be a more customized, self-service model that promotes teamwork and the sharing of knowledge.” She hopes that training and new data-driven tools will help her company to get “better up-front decisions being made about cost prior to a procedure taking place, creating more customized and competitive care structures.”
The efficiency of training could be measured by attrition and engagement scores. Jill says that engagement in healthcare, driven by career benefits or salary in other industries, is fueled by the idea of using data as a tool to help others. As medical workers have both a psychologically rewarding and stressful job (since people’s lives depend on them), the brand new perspective on medicine makes hospital staff more engaged and purpose-filled. Gamification and training simulations will also contribute to healthcare employees’ engagement because they will allow medical workers to practice their skills in real-time. She hopes that AI will also help to unlock more about how the brain works which will help healthcare improve methodologies for developing skills and change individuals’ behaviors. This relates to neuroscience-based training programs tailored to the specifics of how the human brain learns.
Changes in industries, triggered by the omnipresence of AI, will not only transform their core working mechanism but will also have an impact on the workplace culture as is.
Workplace culture as a whole will be more fluent, and healthcare isn’t an exception
In the future, Jill says that companies will provide their employees with opportunities to work remotely, in more flexible ways. Those with a high level of expertise will be able to contribute to multiple businesses: work will no longer be based on a 40-hour work week; it will be more about completing a given project or task effectively and working at companies that support alternative work schedules. She also believes technology will start to replace workers, and those who want to stay will learn to be more comfortable with change, embracing agility, problem-solving, and communicating with different audiences.
Three predictions for the future of work from Jill Sutton
- The workplace will be less structured and more flexible. The workflow will consist of completing separate projects—such an approach will replace the 40-hour classical schedule.
- There will be a growth of small and medium enterprises with a decline of loyalty to big brands. People will choose what is suitable for them and will buy goods or services from small and medium companies. That’s why it’s crucial for companies to learn how to meet customers where they are.
- More technology will be used to replace workers, and those who are willing to stay must be flexible, open-minded, and willing to learn.
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