How Does AI Reduce Costs in Healthcare

Healthcare costs are spiraling upwards for both patients and hospitals. In this tense scenario, AI came as a relief. This blog will explore how this technology saves the industry from the financial burden and makes healthcare services affordable and effective. 

The Challenges in Path of Healthcare Cost Reduction 

The United States spends more on healthcare than any other developed nation. These startling statistics from the Centers for Medicare and Medicaid Services and Medical Economics are the proof:

• In 2022, US healthcare spent 4.3 trillion.
• Healthcare costs will grow at an annual rate of 5.4% from 2022 to 2031.
• Administrative costs are about 25-30% of total spending, compared to 10-15% in any other country.
• Preventable medical errors cost $20 billion annually to the country’s economy and are also the third leading cause of death.
• Chronic diseases account for 90% of the nation's $3.8 trillion in annual healthcare expenditures.
• Physician burnout is also one of the reasons behind rising expenses. It costs the industry around $4.6 billion annually and impacts productivity and medical outcomes. 
• Overall expenses will reach $6 trillion by 2028.

Key Areas of Rising Healthcare Costs According to AMA 

The healthcare industry is under the weight of inefficiency, waste, and escalating costs. Several factors—labor costs, drug prices, medical supplies, and the rising complexity of care—are the reasons behind this growing weight. The American Hospital Association showed how these factors are affecting the budget.

• Labor Costs: Hospital labor costs have risen by 20.8% in recent years, with a 24.7% increase in labor expenses per patient since 2019​. 
• Drug Prices: Drug expenses are a major driver of healthcare cost inflation. The median price of new drugs has soared, with some medications launching at prices as high as $200,000​.
• Medical Supplies and Equipment: The rising cost of essential medical supplies has further strained healthcare providers, with supply chain disruptions exacerbating these challenges.​
• Hospital Services: Inpatient and outpatient care costs continue to rise, contributing to over 40% of total healthcare expenses​.

These figures show how desperately the industry needs innovative solutions to balance quality care with cost. By using AI for healthcare cost reduction, the industry can deal with these financial challenges. 

6 Ways of Reducing Healthcare Costs Through AI Technology 

AI is lowering healthcare costs in multiple areas, not only in one department but in multiple others. We have explained each one and its financial impact. 

1. By Preventing Misdiagnosis

Diagnosing patients incorrectly is dangerous for both patients and healthcare providers. The errors lead to wrong treatments, increased patient stays, additional tests, malpractice lawsuits, and, in the worst scenarios, deaths. 

AI-driven diagnostic tools reduce diagnosis errors and accurately identify abnormalities that are difficult for human specialists. They can scan medical images of poor quality, such as X-rays, MRIs, and CT scans, with a high level of precision.

2. By Lowering Patients' Readmission Rate

The increased number of patient readmissions due to ineffective treatments drives significant expenses for hospitals and patients. Those with a high readmission rate are also at risk of penalization by Medicare under its Hospital Readmissions Reduction Program (HRRP). Millions in penalties are levied against such hospitals annually.

AI-powered predictive analytics can reduce this rate and penalty. These tools analyze vast volumes of data, such as patients' medical histories, to identify possibilities of readmission. Through predictive analytics, clinicians can monitor high-risk patients and take proactive measures to prevent readmission, reduce emergency treatments, and reduce billings.

3. By Cutting R&D Costs in Drug Discovery 

Drug development costs billions of dollars and years for pharmaceutical companies to produce one effective drug. That's not the end of their expense; multiple clinical trials increase the cost without guaranteeing that the drug will be 100% effective. 

AI reduces the cost of research and development of new drugs while increasing the accuracy of their effectiveness. It also reduces the time to develop a drug from decades to a few years with automation. Many leading companies use AI for drug discovery to find the right target, design, and clinical trials. 

4. By Slashing Administrative Burden and Cost

A massive percentage of total healthcare expenses come from the administrative department. Many tasks are done manually, such as scheduling appointments, billing, and processing claims. Errors and delays cause unnecessary expense. 

AI can reduce administrative burden and cost by automating such tasks. It saves on salaries to hire large clerical staff, improves cash flow by minimizing errors in insurance claims, and also reduces paperwork for processing and verifying patient information. 

5. By Reducing Trial-and-Error in Patient Care

The one-size-fits-all approach no longer brings quality care to the patients. The trial-and-error practices result in revisits of patients, increasing the cost of treatment and readmission. 

The industry needs to think beyond standard ways of analyzing patients’ conditions and suggest 

treatments not only for in-house patients but also for virtual ones. 

AI is personalizing patient care by reading their genetic makeup, lifestyle factors, and medical records. These factors bring precision to treatment planning and therapy suggestions. 

Such targeted treatments reduce the need for multiple tests and rounds of treatment. When patients receive such personalized care, they recover faster and have lower daily expenses.

6. By Predicting Medical Supplies Early 

Achieving supply chain efficiency in healthcare is as important as in any other industry. Expired medications in inventory to stock up expensive medical equipment without real-time assessment contributes to high operational costs. 

AI can accurately estimate the medical supplies needed in different hospital departments. With its predictive capabilities, AI tools can tell which medical supplies are about to expire soon and what needs to be stockpiled in advance. It does this by predicting the future volume of patients and other requirements. Result?

• Low expense on emergency purchases 
• Reduced cost of storing medicines.
• Minimum medical waste. 

Conclusion

The healthcare expense stresses both payers and providers. From costly health insurance to rising labor costs in the industry, multiple factors are to be blamed. The intervention of new technologies can deal with factors that directly impact the costs. 

The above use cases show how payers and providers can reduce healthcare costs through technology. Payers can save up to 9%, whereas physicians can save between 3-8% of costs annually with AI. The estimate is higher for hospitals with the responsible use of AI solutions for healthcare.

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