The Potential Financial Benefits of AI in Healthcare Organizations

Assess the cost and benefit of AI use cases.

Analyst Perspective

As healthcare costs continue to rise, AI has the potential to help you save costs and enhance revenue in your organization.

Artificial intelligence (AI) in healthcare has the potential to provide various benefits through the automation of administrative processes, augmentation of physician decision making, advancement in preventative and precision medicine, efficient imaging and diagnostics, remote patient monitoring, virtual medical assistance, and drug development, among others. However, despite these benefits, many healthcare organizations currently face financial constraints and competing priorities that impact their decision to invest in and realize the financial benefits of AI.

The financial benefits of AI refer to the cost savings and revenue generation opportunities that AI can bring to your organization. AI has the potential to provide cost savings in call center operations, administrative processes, patient scheduling, supply chain and hospital decision support, as well as revenue cycle processes. Additionally, it presents new revenue generation opportunities, such as increased new patient capacity, additional operating room capacity, vendor partnerships, and the monetization of clinical data.

This research report provides an overview of the financial benefits of AI, complete with case study examples and a cost-benefit estimation tool. The tool will help you develop a comprehensive business case to present to your leadership team, demonstrating the tangible business value of adopting AI in your healthcare organization.

Sharon Auma-Ebanyat
Research Director, Healthcare
Industry Practice
Info-Tech Research Group

Executive Summary

Your Challenge

• The healthcare industry is undergoing rapid change, driven by staffing and financial pressures, with a strong emphasis on improving care outcomes, patient, and provider experiences, and streamlining operations for efficient care delivery.
• AI could offer significant financial benefits, including cost-savings and revenue generation, which have the potential to transform your organization's healthcare service delivery and address current challenges.
• Considering the current financial constraints, it is crucial for your organization to understand the financial benefits of AI to prioritize and develop a business case and budget for its implementation.

Common Obstacles

• AI investments can effectively optimize existing revenue streams and create new sources of revenue. However, many organizations are still unclear about the specific opportunities for revenue generation that AI can offer.
• The ongoing pressure to cut costs makes it challenging to justify investments in new technologies without a clear cost-benefit analysis and a solid justification of the business value.
• The process of prioritizing areas for improvement becomes challenging due to the presence of competing needs and limited resources.

Info-Tech's Approach

• Use the healthcare reference architecture to identify business capabilities in your organization that have potential for cost savings and revenue generation through the implementation of AI use cases, ultimately driving business value.
• Identify specific business goals and functional areas within your operations that require prioritization for improvement, aligning them with the AI use cases that can create cost advantages or enhance revenue.
• Conduct a high-level cost-benefit analysis of the selected use cases to develop a comprehensive business case that clearly demonstrates the value of AI in your organization.

Info-Tech Insight

When investing in AI, you should not only focus on the financial return on investment but also the overall business value to help you address operational, clinical challenges, and your organization's ability to use AI to proactively and effectively plan for future operations.

What is AI?

There is no universally accepted definition of AI; however, it generally refers to the development of computer systems capable of performing tasks that would typically require human intelligence, such as learning, reasoning, perception, and problem-solving. AI can be characterized as a set of technologies that enable machines to process and analyze vast amounts of data, identify patterns, and make predictions or decisions based on that data.

AI includes various subfields, such as machine learning, natural language processing, computer vision, and deep learning. Deep learning involves the use of neural networks to process and analyze large data sets. While these subfields focus on different aspects of AI, their common goal is to create intelligent machines capable of performing tasks without human intervention.

As a rapidly evolving field, the definition of AI continues to evolve as new technologies and applications emerge. Nonetheless, at its core, AI revolves around creating intelligent machines capable of performing tasks that typically necessitate human intelligence.

Source: Dataconomy, 2023; Procedia Computer Science, 2023.

AI adoption in healthcare is on the rise

COVID-19 was a catalyst for AI

The COVID-19 pandemic had a positive impact on AI, leading to an increased use of AI applications to keep people safely connected and informed. Examples of this include AI-generated status information on COVID-19 cases globally, chatbot communication in healthcare, and the automation of patient scheduling processes. These implementations demonstrated that incorporating AI tools in healthcare operations can help countries prepare for and mitigate the risks from future healthcare challenges.

A growing number of AI use cases

Despite the widespread inquiries about AI in healthcare, there are already 23+ AI healthcare applications in use (McKinsey, 2020). The rising demand for AI is driven by its capability for early and accurate disease detection and addressing provider shortages, which, in turn, has fueled innovation and product development in the healthcare sector.

AI is reducing healthcare costs

AI is demonstrating significant cost savings in hospitals, particularly in operations, quality, and safety. Examples include optimized operating rooms, detecting medical errors, referral management, and revenue cycle management with prior authorizations and claims processing. AI is estimated to save 5% to 10% in healthcare spending, which is equivalent to annual savings of US$200 billion to US$360 billion (Healthcare Dive, 2023).

AI shows revenue opportunities

According to a Data Bridge market research study, the global AI healthcare market is projected to reach US$272.91 billion by 2030, with a growth rate of 51.87% between 2023 and 2030. This significant growth is attributed to the increasing number of AI-based startups and the rise in private and venture capital investments in the healthcare industry (Data Bridge Market Research, 2023).

Trends: Healthcare cost drivers

The National Healthcare Expenditure projects that US healthcare costs are growing annually at a rate of 1.1%, outpacing its GDP, and are expected to reach US$6.2 trillion by 2028. If this trend continues, healthcare spending could reach US$12 trillion by 2040. The cost drivers described below are mostly applicable to the US healthcare market.

Cost drivers affecting margins of healthcare organizations:

1. Labor costs:
Labor expenses account for nearly half of hospital expenses. Staff and contract labor continue to put pressure on hospitals, with labor expenses in 2022 projected to exceed 2021 by US$57 million ("Hospital Finances," Kaufman Hall, 2022). Hospital labor costs rose 37% between 2019 and March 2022 ("Hospital Workforce Dislocation," Kaufman Hall, 2022).

2. Rising patient acuity:
The increasing number of people with chronic conditions (at least six in ten people) significantly increases the cost of care for healthcare organizations (Centers for Disease Control, 2022).

3. Supplies, purchased services, and pharmaceuticals:
Inflation has increased the prices of medical equipment and drug supplies at twice the retail rates. New drugs and products continue to drive healthcare costs and payer spending.

4. Administrative expenses:
The US healthcare system spends US$4.3 trillion annually, of which 25% goes toward administrative expenses (American Medical Association, 2023; McKinsey 2021). Almost 40% of these administrative costs are spent on back-office and non-clinical operations, which are a significant source of healthcare operational waste due to manual and inefficient processes (McKinsey, 2021).

5. Reimbursement gaps and inflation:
Healthcare organizations are faced with lower reimbursement rates due to surging inflation, increasing healthcare costs, and fluctuations in government and commercial rates.

Healthcare Cost Drivers According to US Patients

Source: Statista, 2019

A quarter to a third of these healthcare costs can be attributed to waste, which includes administrative challenges, duplicate services, unnecessary treatments, high drug prices, and readmission rates (Peter G Peterson Foundation, 2023).

Trends: Revenue enhancers in healthcare

The global hospital market is projected to reach US$4 trillion in 2023, driven by factors such as the aging population and an increased prevalence of chronic conditions, which has led to a rising demand for specialty care (Statista Market Insights, 2023). The forecast below indicates a steady hospital market growth with a CAGR of 4%, and the increasing demand for digital health, including electronic health records and emerging AI technology, will continue to influence this growth (Statista Market Insights, 2023). These revenue trends are mostly applicable to the US healthcare market.

Revenue enhancers for healthcare organizations:

1. Change in payer mix shifting toward government payers: The healthcare payer profit is set to increase, driven by the increasing aging population, with more Medicare Advantage users than Medicare fee-for-service users and a shift from these patients under Medicaid. The total enrollments could increase by 1.5% between 2021 and 2025 (McKinsey, 2022).

2. Healthcare services and technology: The global healthcare market, valued at US$11 trillion, is undergoing a digital revolution (Cision, 2021). This is due to rising consumer demand, patients becoming primary payers, administrative burden in operations, the aging population, and clinical labor shortages. In an effort to improve healthcare financial margins, several healthcare organizations are integrating workflow technology and intelligent automation to streamline their clinical operations and revenue cycle operations.

3. Pharmacy services: The continued evolution of the pharmacy industry with new models of patient care, specialty services, partnerships, and new digital pharmacy models and tools has created opportunities for pharmacies to expand their services and grow their revenue.

4. Mergers and acquisitions: To increase their economies of scale and revenue, healthcare organizations are increasingly engaging in mergers and acquisitions and forming healthcare provider networks. This provides investment opportunities in niche capabilities and enhances payer contract negotiations.

Global Hospital Revenue Trends

• Revenue in the hospitals market is projected to reach US$4.08 trillion in 2023.
• Compared to other countries, most revenue will be generated in the US (US$1,436.00 billion in 2023).
• Based on total population figures, hospitals will generate a per person revenue of US$530.90 in 2023.

Source: Statista Market Insights, 2023

AI applied: Healthcare capability reference architecture

Capability Reference Architecture Defined

In business architecture, the primary view of an organization is known as a capability reference architecture. A business capability defines what a business does to enable value creation, rather than how.

Business capabilities:

• represent stable business functions.
• are unique and independent of each other.
• typically will have a defined business outcome.

A business capability map provides details that help the business architecture practitioner direct attention to a specific area of the business for further assessment.

Legend

The cost-benefit implications AI in healthcare are significant

AI use cases can create value as cost value creators and revenue enhancers