By Zac Amos, Features Editor, ReHack
LinkedIn:Â Zachary Amos
LinkedIn:Â ReHack Magazine
Artificial intelligence (AI) has grown ubiquitous, infiltrating various industries. The healthcare sector is benefiting from this omnipresence. With rising prices and increasing demands for service, professionals are keenly interested in how AI can supercharge workflows and reduce expenses. Yes, AI can reduce the cost of care and improve health outcomes through these advancements.
AI’s Role in Reducing Healthcare Costs
The National Health Expenditure Accounts report that healthcare spending reached $4.9 trillion in 2023, allocating an average of $14,570 per patient. While AI can never replace critical human connection in the workplace, its automation tools promise a future in which healthcare expenses may be lower.
1. Streamlining Administrative Tasks
One primary way AI can lower healthcare expenditures is by automating administrative functions. For example, Mayo Clinic utilizes generative AI to automate routine tasks such as filling out forms, drafting clinical notes and scheduling patients. When organizations use automation, they see a 20% drop in costs while improving overall efficiency and productivity.
2. Improved Diagnostic Accuracy
AI’s ability to analyze large datasets and identify patterns that may elude human doctors has the potential to reduce diagnostic errors significantly. It can quickly interpret medical pictures — including mammograms — with 95% accuracy, freeing up radiologists’ time for other duties that call for their technical expertise.
Research funded by the National Cancer Institute has demonstrated that AI imaging algorithms can assist in forecasting the long-term risk of aggressive breast cancers and improve mammography detection of breast cancer. Methods leveraging AI also pave the way for diagnosing heart diseases early, enabling preventive care. This effectively reduces the need for expensive emergency interventions and initiatives for cost-effective treatments before conditions worsen.
AI-driven preventive care helps reduce long-term costs by minimizing emergency treatments and hospitalizations. Coupled with financial tools like Health Savings Accounts — which allow individuals to set aside tax-free money for medical expenses — patients can better manage their healthcare spending while benefiting from enhanced affordability.
3. Predictive Analytics for Resource Allocation
AI’s ability to predict patient outcomes and resource needs is another promising avenue for expense reduction. For example, these models can forecast which patients are at risk of readmission, enabling providers to allocate additional resources such as home care or follow-up services before they require emergency treatment. By optimizing staffing, inventory management and equipment use, AI can help hospitals and healthcare facilities avoid under- or over-utilization of resources, thus lowering operational costs.
Challenges to Cost Reduction
While AI offers substantial benefits, the transition to such systems is not without its challenges.
1. Upfront Costs
The upfront expenses of implementing AI technology — including purchasing software, training staff and upgrading infrastructure — can be significant. Since the medical field requires advanced systems, the initial investment could be around $100,000 to over $1 million.
2. Cost-Saving Potential
Moreover, AI’s cost-saving potential is heavily dependent on the scale of implementation and how well the technology integrates into existing systems. Without a seamless merging strategy, automated tools may not deliver the anticipated benefits and could result in additional expenses rather than savings.
3. Data Privacy and Security Concerns
Another factor that could prevent AI from driving down healthcare prices is the increasing complexity of data privacy and security regulations. Providers must ensure systems comply with the Health Insurance Portability and Accountability Act (HIPAA) and other data protection laws.
AI use in protected health information (PHI) faces limitations. Under the HIPAA Privacy Rule, there are clear guidelines for PHI access, collection, application and release. Additionally, hospitals are only allowed to use the minimum amount of PHI required for their intended uses. Maintaining compliance with these regulations is complex, and additional costs for security measures, auditing and legal consultations may result.
The Long-Term Outlook: Will AI Lower Healthcare Prices?
The short answer is yes — recent reports show AI could save at least $80 to $110 billion over the next five years. The longer answer is AI’s potential to reduce healthcare costs in the long term is undoubtedly promising. However, it is essential to understand that the transition will be gradual.
The leading difficulty to AI adoption is the lack of AI skills, knowledge and competence, with 34% of organizations citing this as their biggest obstacle. A third of firms encountered this problem, while the expensive cost was another hurdle to cross.
AI’s Cost-Saving Promise for the Healthcare Industry
AI can lower healthcare expenditures by automating tasks, improving diagnostics, optimizing resources and enhancing preventive care. While high initial spending poses challenges, long-term savings are promising. As AI matures and becomes more accessible, healthcare providers will see reduced inefficiencies, improved patient outcomes and, ultimately, lower overall costs.