Readers Write: Improving the Healthcare System with Advancements in Data Science and AI

Improving the Healthcare System with Advancements in Data Science and AI
By Hugh Cassidy

Hugh Cassidy, PhD, MBA is head of artificial intelligence and chief data scientist at LeanTaaS.

Healthcare has historically been slow to adopt modern technologies, but recent advances in AI have propelled it into the mainstream, allowing AI to be confidently used in critical systems like healthcare. These advancements, in both computational power and sophisticated algorithms, have made AI not only more popular, but also more reliable for complex, high-stakes environments.

According to a recent survey from the Berkeley Research Group, 75% of healthcare professionals anticipate that AI technologies will be widespread throughout the industry within the next three years. This optimistic outlook highlights the potential of AI to transform healthcare operations and to keep pushing forward with advancements in data-informed technology and predictive healthcare solutions.

However, healthcare’s history of slow technology adoption emphasizes the need for a strategic approach. Without a clear implementation plan, organizations may fail to harness the full potential of AI to improve operational efficiency and outcomes and to meet broader organizational goals.

To fully appreciate AI’s transformative potential, it’s essential to delve into its specific applications across various healthcare challenges.

One of the most pressing issues in healthcare is excessive patient wait times. Many of us have experienced long hospital delays, and the ongoing staffing crisis coupled with rising patient volumes has only made the situation worse. AI can play a pivotal role in streamlining patient flow, helping ensure timely care while reducing operational inefficiencies.

Predictive analytics can sift through historical data to forecast patient inflow, going beyond current conditions to anticipate future trends. However, predictive insights alone aren’t enough. Prescriptive systems are essential to translate those forecasts into actionable schedules. By combining AI-driven predictions with prescriptive analytics, healthcare facilities can generate optimized schedules that not only forecast patient demand, but also suggest the best staffing and resource allocation to handle peak hours. These prescriptive systems are necessary to minimize bottlenecks, reduce wait times, and ultimately enhance the overall patient experience.

Another pain point that healthcare professionals face daily is an overwhelming number of administrative tasks, which inundates staff members and ultimately detracts from patient care. Staff members often work overtime to give patients the best care, yet still have mountains of paperwork to complete once their assigned shift is complete.

AI can make a major impact and alleviate this burden through automating routine tasks such as data entry and billing. Optical character recognition (OCR) and natural language processing (NLP) tools can read and organize clinical notes, reducing the time that doctors and nurses spend on paperwork. AI-powered conversational assistants can handle common patient inquiries and triage less-critical cases, freeing medical staff to focus on more complex and urgent patient needs. By using AI to their advantage, healthcare teams can streamline processes like appointment scheduling and build schedules that are tailored to each facility’s unique demand and capacity.

By streamlining administrative tasks and automating certain aspects of patient care, AI can contribute to increased efficiency in the healthcare system, leading to cost savings and better resource allocation. Tools such as automated billing systems reduce errors and streamline the billing process, reducing administrative overhead. Scheduling tools fill unused time and unlock the full potential of the OR and infusion centers. All of this helps create more revenue and lower costs for health systems and patients alike.

One of the best ways health systems can reduce costs is by accurately allocating their resources and serving their communities by providing consistent and timely access to care for every patient who is in need. This not only improves patient outcomes, but also drives higher revenue and keeps costs low.

The potential of AI and data science to revolutionize healthcare is immense, but it requires a thoughtful and strategic approach to implementation. Health systems should work towards overall workforce adaptation and train and prepare hospital staff to effectively work with AI tools. This will likely require changes to existing education and training programs, as well as require ongoing support to ensure the integration of AI-driven tools into everyday workflows, but it will also help shorten patient wait times, ensure that patients are getting better care, and guarantee that healthcare workers aren’t overworked.

Considering AI’s immense popularity these days, hospitals should capitalize on staff members’ excitement about new tools. The future of healthcare lies in the intelligent use of data and AI, and these technologies are already helping many healthcare systems overcome current limitations and deliver superior care. Along with better patient care, hospitals are also maximizing revenue and improving overall hospital operations, leading to happier staff and hospitals that are more capable at handling growing patient volumes.