AI and Automation Solutions
Strategic advisory support to help you harness the power of artificial intelligence (AI) in revenue cycle safely, quickly, and effectively.
Activate AI in Your Mid-Revenue Cycle
The 2024 healthcare revenue cycle workforce needs to work smarter, not harder. AI, robotic process automation, and machine learning tools enable staff to be more productive in the healthcare revenue cycle. Organization CFOs and VPs of Revenue Cycle that invest in these technologies will experience net revenue growth, cash acceleration, and reductions in expenditures by focusing their respective work forces on value added tasks while allowing the technology to process repetitive, non-value tasks. But not all intelligent automation is equal, with few proven use cases implemented at scale.
e4health’s deep expertise and decades of innovative healthcare technology and revenue cycle experience, is a great match to support hospitals and health systems executives as they evaluate automated technology and AI solutions. Partnering with e4health, healthcare organizations can ensure they receive maximum value and achieve their desired outcomes from new (and in some cases still evolving) investments.
What is your 2024 AI and Automation Plan?
The decisions you make around AI today will directly impact your organization’s future success. e4health can help you with planning and assessment of AI solutions to optimize your revenue cycle.
Explore our AI and automation solutions
Machine learning, large language models (LLMs) and AI has emerged as powerful tools to resolve the persistent revenue cycle challenges faced by health system executives.
Patient Identity Management
Duplicate medical record remediation and clinical data abstraction require are already benefiting from advances in AI. By leveraging predictive algorithms and pattern recognition, machine learning can identify and rectify duplicate entries in a hospital’s Electronic Health Record (EHR) system and ensure the right data is assigned to the right patient. This not only enhances data accuracy but also improves patient safety and care quality. By eliminating redundancies, machine learning facilitates smoother operations and better resource utilization. However, for health systems to fully capitalize on this technology, a thorough understanding of its potential and limitations is essential. e4health employs a holistic people, process, and machine learning approach to accurately identify and resolve duplicate patient medical records and ensure the integrity of the data in your hospital systems.
Patient Access
Robotic Process Automation (RPA) has emerged as a game-changer in the segment of patient access within the revenue cycle. RPA plays a pivotal role in patient eligibility verification by automatically validating patient coverage by extracting relevant data from payer portals and the hospital’s Electronic Health Record. This not only minimizes denied claims due to eligibility issues but also mitigates the risk of delayed or missed revenues. e4health can help your organization define an RPA implementation plan for your revenue cycle to achieve streamlined operations, reduced labor costs, and improved staff productivity.
Clinical Documentation Integrity
Artificial Intelligence has emerged as a remarkable tool for capturing clinical documentation in patient records. AI systems, with their advanced Natural Language Processing capabilities, can interpret and transcribe physician’s notes, scan documents for specific information, and even code diagnoses and procedures for billing. This not only enhances the accuracy of clinical documentation but also significantly reduces the administrative burden on healthcare professionals. e4health can help your organization harness the power of ambient clinical documentation to achieve more efficient operations, improved patient care, and better financial outcomes.
Autonomous Coding
Autonomous coding, while early on, is being piloted and utilized by hospitals to streamline their operations. This technology leverages Artificial Intelligence to advance CAC to automatically interpret and code clinical documentation, such as diagnoses and procedures, which are then used for billing purposes. Outpatient procedures have made more progress, while Inpatient remains relatively elusive. The use of autonomous coding not only enhances the accuracy of medical billing but also significantly reduces the administrative workload on healthcare staff. e4health can help your organization build the model to navigate deployment of people, solutions, and technology in your coding operation to improve efficiency and profitability.
Enhanced Auditing
By using advanced algorithms, AI can meticulously analyze medical codes and documentation to identify discrepancies such as incorrect coding, unbundling of services, or upcoding. This precise detection of errors across a much bigger sample, if not all charts, ensures enhanced accuracy in the auditing process and prevents improper payments, thereby contributing to financial integrity in healthcare institutions. For healthcare executives, the adoption of AI-assisted claims auditing can be a gamechanger, driving operational efficiency and safeguarding against financial leakages. e4health can help your organization define an AI-driven auditing strategy that ensures what was coded and what is in the patient chart is accurately clinically validated to prevent denials and optimize reimbursement.
Denials Management
Automated and preventable denials management is a powerful tool for speeding up cash flow in the revenue cycle. Identifying those cases at high risk for denial, before a claim is submitted, will save time, ensure timely filing, avoid rework/resubmission and delayed cash for health systems. For denials that are known and involve repetitive steps, these can be efficiently handled by programmed bots allowing your team to focus on more value-added tasks. e4health is capable of conducting an assessment of these denials to pinpoint opportunities for workflow optimization.
HCC Risk Adjustment
Hospitals are increasingly leveraging the power of Artificial Intelligence in Hierarchical Condition Category (HCC) Risk Adjustment. AI, with its advanced algorithms and learning capabilities, can effectively analyze patient data and accurately predict HCC scores. This not only facilitates the identification of potentially overlooked conditions but also enables healthcare providers to deliver more personalized care plans, by more effectively planning in advance of the patient encounter. For healthcare executives, the integration of AI into HCC Risk Adjustment represents an innovative approach to improve patient outcomes and optimize reimbursement processes reliant on this data. e4health’s industry-leading experts will analyze your HCC Risk Adjustment to identify areas for effective integration of AI.
Forward-Thinking Thoughts on AI’s Role in Health IT and HIM
Matthew Zubiller, e4health CEO, shares insights on three pivotal ways AI is poised to revolutionize health IT and HIM.