How does AI reduce costs in healthcare organizations?
Workforce shortages, technology burden, connecting patients and medical staff, chronic disease management.
The U.S. healthcare system faces a cycle of interconnected problems:
- Staff shortages overwhelm workers, they are burned out and perform worse.
- Outdated technology adds inefficiency and strains them more.
- Limited care access and weak prevention drive chronic diseases. They raise costs and demand for specialists… who are scarce.
These problems create a vicious cycle. In this article, we’ll show you how these problems can be solved using technology, especially AI. If you’re a decision-maker in a healthcare delivery organization in the US, this is a must-read for you.
Custom solutions for healthcare
How AI can help with staff burnout & administrative burden
| PROBLEM | SOLUTION |
| Healthcare workers are overwhelmed by tasks and the aging workforce resists change. |
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Healthcare workers face unprecedented levels of burnout.
According to recent data, 49% of practicing physicians experience burnout weekly. Many doctors and nurses approach retirement, leaving a growing gap in skilled professionals. Couple this with an aging workforce resistant to new technologies, and you get a critical challenge for healthcare organizations.
The main culprit?
Repetitive manual tasks.
Much of this issue arises from systemic challenges. Healthcare professionals spend up to 35% of their time on administrative tasks. For a 15-minute patient visit, that means over 5 minutes are spent just on documentation. This administrative burden not only contributes to burnout but also reduces time for direct patient care.
AI Agents and Ambient Intelligence
How can healthcare organizations use technologies to reduce staff burden and burnout?
- AI agents are specialized software programs that can handle routine tasks automatically. Major tech companies like Microsoft, Oracle, and NVIDIA now offer AI agents specifically designed for healthcare back-office operations. These agents can manage documentation, schedule appointments, and handle routine administrative work.
- Learn more: AI agents for healthcare [2025 guide]
- Ambient intelligence creates an intelligent environment using sensors and AI to monitor and respond to what’s happening in healthcare settings. It can be used to monitor patients’ health, listen to doctor-patient conversations, and automatically document visits in EHRs. Ambient microphones present during patient visits could reduce documentation time from 2 hours to as little as 15 minutes in some cases.
- Well-being platforms – digital tools designed to promote and improve the mental health and overall well-being of employees.
Going back to the capabilities of AI agents, let’s discuss Oracle’s Clinical AI Agent. It can instantly access patient records, automate documentation, and suggest relevant treatment options. For example, a doctor can simply ask the agent “What are this patient’s allergies?” and receive the answer immediately, freeing up time for patient interaction.
According to Oracle’s press release, its AI agent implementation at AtlantiCare reduced documentation time by 41%, giving providers back 66 minutes each day. For a hospital with 100 providers, that’s over 40,000 hours annually redirected to patient care.
Case studies. How we do it
- In our own experience, when we implemented automation features in WithHealth’s patient portal, we saved enough work hours to equal one full-time employee’s workload (40 hours per week or about 2,080 hours per year). This allowed the healthcare staff to redirect their time to higher-value activities like supporting more patients.
- We built Health Folder – Teczka Pacjenta, a system that enables patients to scan, categorize, store, and analyze their medical records. The paper documents are scanned using precise OCR (Optical Character Management) technology. A similar solution, if integrated into a healthcare organization’s system, could drastically reduce the unnecessary paperwork.
We enabled patients to scan, categorize, store, and analyze their medical records
We drastically reduced unnecessary paperwork using AI.
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How AI helps manage patients with chronic diseases
| PROBLEM | SOLUTION |
| Rising need for care for patients with multiple chronic illnesses. Insufficient prevention programs. High treatment costs. |
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By 2060, the number of Americans aged 65 and older is expected to almost double to 95 million, from 52 million in 2018. (source)
What’s more, 90% of the nation’s $4.5 trillion in annual healthcare expenditures are for people with chronic and mental health conditions. (sic! – source)
With an aging population and insufficient preventive care programs, the cost of managing chronic diseases continues to spiral upward. How can technology & AI help reduce these costs?
Predictive Analytics
With the growing adoption of AI, there has been a shift in healthcare providers’ approach – a focus transition from treating conditions to predicting them through data-driven healthcare.
Advanced AI algorithms can now at-risk patients before their conditions worsen.
By analyzing patterns in vital signs, medication adherence, and lifestyle factors, these systems can predict potential health deterioration up to weeks in advance. For example, machine learning models can detect subtle changes in blood glucose patterns that might indicate an impending diabetic crisis.
Coordinated Care Platforms
Modern AI-powered care coordination platforms are breaking down traditional silos between specialists, primary care physicians, and other healthcare providers.
These systems automatically synthesize patient data from multiple sources and create comprehensive health profiles that all care team members can access and update in real time.
Here, the A identifies gaps in care, suggests interventions, and ensures that all providers are aligned in their treatment approaches.
Remote Monitoring
Internet of Things (IoT) devices’ role is to continuously collect vital health data and use AI to interpret it. They show a great impact on cutting organizational costs; active patient monitoring can help prevent health issues before they happen, or, if they do – allow for a timely intervention.
- Connected glucose monitors not only track blood sugar but predict potential complications based on pattern analysis
- AI-enabled blood pressure monitors adjust medication recommendations based on real-world patient response
- Smart home sensors detect changes in movement patterns that might indicate deteriorating health. Examples:
- Sensi.AI – the platform uses audio data from sensors in the house, such as smart speakers, smartphones, and security cameras, to detect seniors’ daily activities, including eating meals and taking showers.
- Nobi lamps use artificial intelligence (move detection) to detect falls, turn on lights, and alert care staff in case of a patient’s inactivity.
- Kintsugi Voice is an API-first platform that uses novel voice biomarkers in speech to identify, prioritize, and care for mental health in real-time.
A timely intervention is a massive cost-saver. For example, the Oklahoma Health Care Authority (OHCA) achieved remarkable outcomes, including a 24% reduction in emergency department visits per engaged member annually and a 40% decrease in hospital admissions per member annually. Notably, much of this improvement occurred within the first six months. Overall, medical costs dropped by over $1,500 per engaged member per year. (source)
Saving 40 hours weekly & 2000+ hours yearly
Automation features in WithHealth’s patient portal saved enough work hours to equal one full-time employee’s workload.
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How AI helps doctors and patients connect – and slash operational costs
| PROBLEM | SOLUTION |
| Financial and geographical barriers limit access to healthcare. Long waiting times for specialists. Health disparities in rural, low-income, and minority communities. |
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Financial and geographical barriers limit access to healthcare, resulting in:
- Missed appointments costing hospitals $150-$200 per no-show for primary care physicians (source)
- Emergency room overcrowding due to lack of primary care access ($2,000 average cost for preventable ER visits) (source)
- Inefficient resource allocation leading to revenue loss
Strategic implementation of AI-powered connectivity solutions that dramatically reduce operational costs:
AI-Enhanced Telehealth
Virtual care delivery isn’t just convenient – it’s a powerful cost-reduction tool. Healthcare organizations implementing AI-enhanced telehealth report:
- 50.7% reduction in no-show rates through AI-powered scheduling and reminder systems (source)
- Telehealth realizes $361 in savings per patient or $8566 total service cost savings compared with traditional in-home care programs over 6-months (~$13,713 per annum). (source)
Key cost-saving features:
- Automated pre-visit documentation
- Real-time language translation eliminates interpreter costs ($279 per person per year).
- Smart triage systems reduce unnecessary emergency department visits by 1.2–22.2% (source)
Remote Monitoring: Prevention Pays Off
Integration of AI-powered wearables and IoT devices creates a continuous patient-provider connection that significantly reduces costs:
Real-world implementation:
- Remote cardiac monitoring: Cost savings of €4,142 per patient over 5 years, equating to approximately €828 per patient annually. (source)
- COPD monitoring: 44.3% decrease in ED visits among COPD patients using remote patient monitoring for at least a year. (source)
Smart Patient Engagement Systems
AI-driven engagement platforms create cost efficiencies through:
- Automated appointment scheduling reducing administrative costs
- Smart reminders decreasing no-show rates, saving $150 per avoided no-show
- Chatbots handling routine patient inquiries at a fraction of the cost
- Personalized care instructions reducing unnecessary follow-up visits
How AI bridges the tech gap
| PROBLEM | SOLUTION |
| Lack of interoperability between EHR systems. Manual data entry and administrative tasks. Duplicate tests and procedures. IT staff time spent resolving interoperability issues |
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According to Gartner, by 2025, companies will spend 40% of their IT budgets on maintaining technical debt, which includes legacy systems. Additionally, application costs can make up to 80% of the entire IT budget.
What happens if you modernize your healthcare organization’s tech?
In 2021, Deloitte surveyed organizations that moved beyond piloting intelligent automation about their cost-saving. They told Deloitte they have achieved an average cost reduction of 32 percent. One financial services executive they spoke to reported that radically re-engineering processes and using multiple intelligent automation tools resulted in cost reduction of over 70 percent in a targeted area.
What areas should you transform to reduce costs?
Enabling Interoperability
The lack of communication between systems remains one of the biggest obstacles in healthcare.
- How we do it: That’s why the care delivery platform we developed integrates data from multiple sources and provides valuable insights into cultural attributes, psychographics, and other demographic information.
Simplifying System Interfaces
Complex EHR interfaces slow down workflows and frustrate medical staff. AI can simplify these systems by automating repetitive tasks like data entry and streamlining navigation.
- Natural language processing (NLP) allows healthcare workers to interact with EHRs through voice commands or simple queries, just like in the AtlantiCare examples mentioned above.
Switching to the Cloud
High costs often deter organizations from adopting advanced technologies. Luckily, cloud-based solutions and AI-driven optimization tools make implementation more affordable and scalable. These technologies require fewer upfront resources and adapt to the specific needs of healthcare organizations.
- How we do it: WithHealth’s patient portal, built in just six weeks during the pandemic, leveraged cloud infrastructure to keep implementation costs low while providing high-value services. This approach made advanced care accessible even for mid-sized organizations.
Enhancing Predictive and Analytical Capabilities
AI doesn’t just improve integration; it also adds value by analyzing the integrated data to generate insights. Predictive analytics tools can identify trends, flag potential issues, and optimize patient care pathways. These capabilities turn raw data into actionable intelligence.
- How we do it: Predictive analytics reduced no-shows by 30% in one of our projects by identifying patients likely to miss appointments.
We reduced no-shows by 30%
With predictive analytics and integrated multi-source data, we helped a healthcare organization easily predict no-shows.
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The AI promise vs. reality: Why expertise matters
AI offers remarkable potential for healthcare cost reduction, but successful implementation isn’t a simple plug-and-play process. It requires careful planning, deep healthcare expertise, and a thorough understanding of regulatory compliance.
That’s why partnering with an experienced technology team is crucial.
At Pragmatic Coders, we understand the US healthcare system’s complexities, have developed multiple HIPAA-compliant solutions, and can guide you through the entire implementation journey. Our track record shows consistent success in helping healthcare organizations achieve significant cost reductions through building custom medical software perfectly aligned with their specific goals.
Ready to reduce costs in your healthcare organization? Contact us to discuss how we can help you achieve your goals while improving patient care.
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