Health Care Organizations can use AI to Solve Practical Business Problems in Transformational Ways | Deloitte US has been saved
Limited functionality available
By Kumar Chebrolu, managing director, Deloitte Consulting, LLP
Artificial intelligence (AI) is already helping to make some aspects of health care more efficient. As data—including health care and social determinants of health (SDoH)—becomes more interoperable and secure, we expect AI will become a critical engine driving digital transformation and data analytics. For example, with many health systems reeling from the COVID-19 pandemic, AI-enabled solutions could help reduce costs by automating some types of manual work. AI could also be used by health plans to develop new products and improve consumer engagement.
The pandemic overwhelmed many hospitals and health systems and exposed limitations in their ability to deliver care and reduce costs. Since March, many health systems have experienced a significant shift to virtual health, fueled by necessity and regulatory flexibility, according to results of Deloitte's 2020 survey of physicians. The pandemic also opened the aperture for AI and digital technologies to solve problems.
Our latest report, Smart use of artificial intelligence in health care, offers a thorough look at how health care organizations are using AI. We determined that health care organizations can scale up their AI investment by pairing it with a robust security and a data-governance strategy.
AI is a key component in the future of health
AI is already being used to automate processes in health care. In our vision of the future of health, we view radically interoperable data as central to the promise of more consumer-focused, prevention-oriented care. Data analytics will be critical for generating actionable insight from the vast data that will be generated by ubiquitous sources. AI is already embedded into data analytics and is likely to become even more so in the future.
AI uses algorithms and machine learning (ML) to analyze and provide insights based on data. It also can be used to automate some types of repetitive work and has the potential to augment decision-making among operational and clinical staff. By reducing the time spent on administrative tasks, humans can focus on more challenging, interesting, and impactful management and clinical work.
Today, health care organizations often experience pervasive problems across their value chains, which can span every process along the continuum. In the future, health care organizations that apply AI across every process—from care to cure—will likely be able to improve the health and well-being of consumers.
Five areas AI could improve
Many day-to-day, non-clinical operations (e.g., submitting and paying claims) are ripe for AI. For example, natural language processing can understand unstructured data from electronic health records. AI can automate tedious administrative work and generate insights for monitoring fraud and abuse or physician practice patterns. Here are five areas where we see AI having the biggest impact in health care:
|Two key AI applications in health care
What are some of today’s major challenges?
Deloitte’s State of AI survey, which was released in late 2019, looked into how organizations are adopting, benefiting from, and managing AI technologies by industry. The survey found that about 75% of large organizations (e.g., annual revenue of over $10 billion) invested more than $50 million in AI projects/technologies, while approximately 95% of mid-sized organizations (e.g., annual revenue of $5 billion to $10 billion) invested less than $50 million. And 73% of all organizations said they expected to increase their funding in 2020.
The three most cited reasons for using AI were to make processes more efficient (34%), enhance existing products and services (27%), and lower costs (26%). Respondents from health care organizations reported that their main concerns about AI investments were the cost of the technologies (36%), integrating AI into the organization (30%), and implementation issues, including AI risks and data issues (28%).
Investing in AI while confronting risk
As investments in AI increase, and as AI-powered solutions become more widespread in health care settings, the industry should address a new set of challenges both from the data used (including cyber threats) and the potential for bias in the AI algorithms. The strategy should comply with regulations and patient-privacy rules.
AI algorithms can create risks such as variability in patient diagnoses and treatment, data bias, and traditional IT risks such as change management. Health care organizations should work to verify the integrity and accuracy of their AI algorithms by focusing on data strategy, testing, and monitoring. Best practices for health systems and health plans range from confirming stakeholder buy-in, creating a set of strong governance practices, safeguarding patient data privacy, and implementing protection from cyber threats. Providing transparency to consumers about how their data is used is a key component of AI governance.
Health care organizations should consider ramping up AI investments
Every health care stakeholder has opportunities to use AI effectively.
AI is already beginning to deliver significant business benefits throughout the health care sector, and it has the potential to shape it more dramatically in the future. Health care organizations that remain in the experimental pilot phase too long could be left behind by both traditional and unconventional competitors.
Kumar is a Managing Director in Deloitte Consulting LLP’s Life Sciences and Health Care practice. He leads Deloitte’s Applied AI and Digital Analytics practice for the health care sector, and his work ranges from identifying growth opportunities, to implementing transformational programs, building innovation capabilities, and creating disruptive products and services by leveraging artificial intelligence / machine learning, expert decision support systems, digital analytics, and cloud computing.