How AI is Helping Transform Healthcare Administration
AI improves more than clinical operations
When people think of healthcare AI, they often envision how it can help medical staff improve patient care. However, many functions take place behind the scenes, such as planning, quality improvement, operations, and more, that make these services possible.
Therefore, organizational leaders shouldn’t focus solely on how AI can enhance direct patient care. They should also assess how automation in hospitals and beyond can transform critical administrative and operational functions that keep healthcare systems running smoothly.
To give you some perspective on what this looks like, we’ll uncover how AI is transforming healthcare administration.
1. AI can streamline revenue cycle management
Over the years, managing clinical revenue has become more challenging as the U.S. healthcare industry has grown more complex. As one 2024 article pointed out, what’s supposed to be simple has become complicated due to:
Negotiated contracts
Coding requirements
Compliance regulators
The changing reimbursement environment
Difficult insurance payors with differing guidelines (e.g., service preauthorization, detailed document requirements)
AI’s role in RCM processes
An AI healthcare transformation that has been revolutionary in saving time and reducing costly errors is revenue cycle management (RCM). In fact, according to an AKASA/Healthcare Financial Management Association survey, about 46% of hospitals and health systems now use automation in their RCM operations.
Some key areas where AI has had the most impact include:
Automated coding and billing. AI-powered platforms can analyze clinical documentation and automatically suggest appropriate diagnosis and procedure codes. Auburn Community Hospital in New York experienced a 40% increase in coder productivity from using AI.
Claims scrubbing and denial prevention. Before submission, AI systems can scrub claims to identify potential issues, such as missing information or coding inconsistencies. A Fresno Hospital saw a 22% decrease in prior-authorization denials by commercial payers after implementing AI claim review tools.
Prior authorization automation. AI tools can compile medical records, complete authorization forms, and then submit requests to insurance companies with minimal human intervention.
Payment posting and reconciliation. Automated systems can match payments to claims, identify discrepancies, and flag issues for review.
2. AI can optimize hospital operations
The way we view automation in hospitals has changed dramatically over the last couple of years due to AI.
Consider how hospital operations involve countless moving parts, from scheduling and staffing to supply management and patient flow. Traditionally, these functions have relied heavily on manual coordination, which is ridden with inefficiencies, delays, and increased costs.
AI healthcare transformation is now turning these operational challenges into opportunities for improvement, so let’s look at a few examples.
Operating room scheduling and optimization
In 2024, Tampa General Hospital launched a new surgical operations system that leveraged cameras and AI. These tools enabled surgical teams to gain real-time insights to accurately predict case durations and turnover times. In turn, it eliminated reliance on manually entered timestamps.
AI’s role in supply chain management
Machine learning models are changing how hospitals manage their inventory and procurement processes by accurately forecasting demand and optimizing stock levels.
Some key advantages include:
Cost savings. AI approaches improve the flexibility and efficiency of inventory management processes, thereby lowering operating costs.
Predicts disruptions. AI can help predict supply chain disruptions and suggest alternative solutions, ensuring hospital operations continue smoothly.
Decreases medication waste. AI-powered analytics can forecast the number of medications and medical supplies needed for storage, minimizing surplus inventory.
3. AI streamlines administrative clinical workflows
AI streamlines time-consuming repetitive processes, transforming how administrative teams work and improving overall operational efficiency.
Some examples of how it helps with administrative duties include:
Efficiently managing patient data. AI systems can organize, categorize, and process patients' electronic health records (EHRs) and treatments with superior accuracy and efficiency.
Streamlining workflow processes. Through process automation, operational decision support, and intelligent appointment scheduling, AI enhances administrative workflows, minimizes inefficiencies, and optimizes overall operational performance.
Automating documentation. A 2021 study noted how natural language processing technology can automate the documentation of patient visits in EHRs.
Reducing manual workload. AI can improve hospital-wide workflow efficiency by automating tasks like discharge planning and bed assignment, allowing administrative staff to focus on more complex tasks that require human judgment.
4. AI enhances quality improvement initiatives and patient safety
Quality improvement is central to healthcare delivery, but conventional approaches often rely primarily on retrospective reviews and manual data collection. But let’s look at some examples of how AI is changing that.
Identifying adverse events and patterns
Failure Modes and Effects Analysis (FMEA) and root cause analysis (RCA) are considered the cornerstones of risk assessment in healthcare, with FMEA focusing on the present and RCA reflecting on past events. However, AI has now become a valuable asset to both.
GPTs can create RCA tools
For example, generative pre-trained transformers (GPT) can create RCA tools that identify root causes, prioritize causes based on their potential impact, and suggest steps to address them. Regarding FMEA, a case study on AI's applicability found that it can identify a large number of possible failure points more quickly, saving staff significant time.
Accelerating quality improvement processes
Beyond identifying risks, AI is transforming how healthcare companies monitor and report on quality metrics. Its implementation offers:
Real-time monitoring. AI-powered systems can continuously track quality indicators, recognizing trends and potential issues as they emerge.
Automated reporting. Organizations can use AI to streamline regulatory compliance and reporting tasks that previously required dedicated staff hours.
Faster response times. Standard quality initiatives often require extensive manual data collection. However, AI allows them to access real-time dashboards and respond to quality concerns more urgently.
Fuel AI healthcare transformation with the right infrastructure
AI is transforming healthcare in many ways, from revenue cycle management to hospital operations and quality improvement. However, successfully implementing AI also requires the proper infrastructure and support.
OpenLoop provides full-stack, white-label telehealth solutions with built-in AI that address many of the regulatory, operational, and clinical challenges organizations face when launching and scaling digital health services.
So, when you utilize OpenLoop’s infrastructure for your digital health business, you automatically gain access to efficient AI technology.
Want to learn more? Contact us!
*This content is intended for general informational purposes only and should not be construed as legal advice. For guidance on your specific situation, please consult a licensed attorney.