Go beyond paper for Strategic Business Outcomes in Healthcare by using AI/ML-driven Intelligent Document Processing Automation

Key takeaways

• Intelligent Document Processing automates paper-intensive processes in Healthcare and eliminates process inefficiencies.
• It unlocks the true potential of paper-based data and expedites processes while ensuring compliance with the ever-changing regulatory landscape.
• It has a direct impact on Revenue Cycle Management by expediting workflows and reducing the cycle turnaround time.
  
  

The inefficiencies of paper processes in the Healthcare sector

• Process inefficiencies: Workflows are inherently slow. The processes are laborious and require many hands to perform repetitive tasks, such as transcribing information, validating it, and keying it into the central systems. It distracts human resources from their core activities of patient care.
• Error-prone transcription: Handwritten information from paper forms and documents is difficult to comprehend and transcribe. Manual document handling induces errors in the captured data. Errors such as a misspelled name or a misinterpreted note can compromise patient care, deny healthcare claims, and create never-ending disputes.
• Lack of data accessibility: Paper processes trap information in physical siloes. The information is difficult to search for and share when required. It hinders decision-making and the collaboration between different Healthcare departments, which further compromises patient care.
• Higher risks: Healthcare sector has stringent regulations, such as HIPAA and GDPR. As physical documents are difficult to search and retrieve as well as vulnerable to damage and theft, managing and maintaining physical records in repositories is difficult and expensive.
• Lack of scalability: As the operations grow, the scale and volume of the documents also grow. Paper storage and manual operations require a significant amount of investment in terms of storage, human resources for managing the records, making the maintenance and upkeep difficult and expensive.
• Poor stakeholder experience: Procedural delays and long wait times due to process bottlenecks, the requirement of the same information time and again, slow claim processing, etc., create a frustrating experience for the internal stakeholders and external patients. It further impacts satisfaction and loyalty.
• Deferred revenue generation: Manual processing is slow and error-prone. It requires rework and directly impacts the turnaround cycle time and, hence, the cash flow. It locks the finances leading to opportunity loss for investment.

The process efficiencies together pose a strategic impediment to business growth. They prevent Healthcare entities from growing in a dynamic and competitive business landscape.

Why do you require an AI/ML-powered Intelligent Document Processing solution in the Healthcare domain?

• Document ingestion: The solution ingests data from many document sources, including paper documents, PDFs, scanned images, emails, digital forms, hand-filled forms, etc. It is multi-faceted and easily adapts to different document types.
• Document classification: The underlying AI/ML algorithms quickly identify the type of document, such as blood report, ECG report, invoice, purchase order, etc., classify it, and route it to the appropriate workflow. They thus reduce waiting time, which is predominant in manual processing.
• Data extraction: The solution creates value by leveraging AI/ML-driven technologies, such as OCR, NLP, IDP, etc., from unstructured and free text documents like clinical narratives. It extracts complex medical terminologies, dates, names, etc., with high accuracy.
• Data verification and validation: The solution then verifies and validates the extracted data by using algorithms and internal and external databases. It significantly reduces error. The solution has human-in-the-loop functionality for a quick review, which also trains the model in parallel.
• Data integration: The validated data, which is now in a structured format, integrates seamlessly with the enterprise systems. These systems include Revenue Cycle Management (RCM) platforms, billing systems, and CRM solutions, ensuring seamless availability of data when required.

What are the strategic business outcomes of Intelligent Document Processing in Healthcare?

AI/ML-driven automation solutions, such as Intelligent Document Processing, have a direct impact on revenue generation and much beyond efficiency gains. Some of the strategic business outcomes of Intelligent Document Processing include –

• Speedier Revenue Cycle Management (RCM): It reduces the claims processing time from days to minutes. It eliminates the manual touch points and hence the data entry errors that are involved in data capture from claim forms, medical reports, explanation of benefits, etc. As a result, it has a strong impact on revenue. The faster and accurate data extraction also reduces the claim denial rates. It translates into uninhibited cash flow due to few resubmissions and less rework. The AI/ML-powered medical coding automatically assigns the appropriate codes from the clinical documentation. It significantly reduces errors due to manual data entry for complex billing and protects revenue integrity. The inherent nature of Intelligent Document Processing to digitize, classify, and store data streamlines the processes for audits, thus ensuring transparency and compliance. All such factors improve the RCM drastically. 
• Good patient experience and higher satisfaction: Faster patient onboarding by ingesting the data from various forms reduces waiting times, thus delivering a better patient experience. The solutions allow faster access to data that results in quick consultation and treatment, thus improving patient care. The automation solutions allow a holistic view of the patient data by unlocking it from paper and integrating it with the Electronic Medical Records (EMRs). With accurate and real-time patient information available in one place, the Healthcare fraternity are able to make better decisions and design personalized treatments. They can communicate more effectively with patients, address concerns, and reduce emotional turmoil.
• Higher operational efficiency: The automation of repetitive tasks and paper-based processes facilitates significant savings with RoI to the order of 200% in the first year of implementation. The improved data capture accuracy and data quality substantially reduce rework. The solutions are immensely scalable in terms of the processing output and the variety of the data handled by leveraging the existing headcounts, allowing the business to adapt to workload fluctuations. The Healthcare fraternity becomes free from administrative activities, allowing them to focus on patient care and intellectual initiatives. The end-to-end automation workflows eliminate procedural bottlenecks and accelerate the processes across the Healthcare value chain.
• Better compliance and risk management: The digitally extracted data is stored in a structured format in a secure and controlled environment. It automates the compliance check and maintains audit trails. The solution adapts quickly to changing regulatory requirements. The ready availability of data helps to detect patterns by using over-the-top analytics for taking corrective and preventive actions and tangibly eliminating risk. The resulting audit trails prove useful in compliance audits.
• Data-driven decision-making: The automation solution makes the extracted data accessible, machine-readable, and actionable. Healthcare companies can use business intelligence solutions to gain deeper insights from the data generated from different aspects of the Healthcare business, such as Operational Performance and Revenue Cycle Management. These companies can leverage this data to predict patient demand, resource allocation, and patient recovery graph. The Healthcare automation solutions, thus, prove to be an innovation and growth catalyst. 

What are the Intelligent Document Processing Use Cases for the Healthcare sector?

Intelligent Document Processing is essentially driven by AI/ML algorithms. It auto-learns with each exception handling in each installment of batch processing and processes documents. As a result, technology itself is adept at processing a document in any format. Further, automation solutions that have Intelligent Document Processing at the core automate a myriad of use cases in the Healthcare sector.

• Medical billing: The automation solution supports the collection and combination of data from different stakeholders into a centralized process that feeds into the billing mechanism. It generates significant amounts of cost savings.
• Provider application: The businesses collect different documents for the new provider onboarding in the Healthcare network. The documents are essential to gauge the provider’s credentials. The automation solution then verifies the extracted data with different internal and external sources.
• Claims management: The automation solution, powered by Intelligent Document Processing, is able to streamline the claims management process. It speeds up the data processing and eliminates data transcription and ingestion errors. It identifies exceptions and raises flags.
• Physician credentialing: The solution extracts the data and integrates with the core business system. It helps speed up the verification of the physician information with external public sources and different websites.

More Healthcare use cases >>

Future Roadmap of Intelligent Document Processing adoption for the Healthcare domain

• Identify the areas of automation: Select areas that are more paper-intensive. The low-hanging ones include Patient Onboarding, Claim Processing, Accounts Payable, Revenue Cycle Management, Human Resource Document Management, etc.
• Define goals and objectives: List down the measurable goals and objectives. Clear KPIs are essential for measuring the progress of the program. Some of the examples are – improve data accuracy to 99%, decrease operational costs by 30%, etc.
• Establish a data-first culture: Data is a strategic asset. Build an enterprise culture where data quality, accessibility, and analysis are primary. Create rules and regulations about how data is collected, managed, and reused.
• Select the right technology partner: Identify the technology provider who is well-versed with both the technology and the Healthcare domain. The partner should have proven capabilities with a commitment to data security and data compliance.
• Create a PoV: Create Proof-of-Value to demonstrate the technology capabilities. Implement it where returns are faster. Once successful, scale the PoV by using higher workloads across different processes and functions. 
• Set a change management process: Set up a program management team that is involved on the ground and get buy-ins from the enterprise leadership or their representatives. Create a program roll-out plan that conveys the expectations and benefits, trains the human resources across the hierarchy, and addresses concerns.
• Establish a culture of continuous improvement: Set up a mechanism for continuous monitoring of the KPIs, user feedback, and refinement of the solution and optimize the solution benefits across the enterprise.

Simply put

Intelligent Document Processing solution goes much further than data extraction from paper and integrates it with the downstream systems. It offers an intelligent solution on a proven road that parses, assimilates, and integrates unstructured data in any form, such that it can be used for further processing on an accelerated path and generating actionable insights. It builds the Healthcare enterprise to be future-ready, where process agility and superior patient experience define success, which automatically supports Revenue Cycle Management. Unlocking the true potential of data within the purview of the compliance regulations by using Intelligent Document Processing is the real strategic outcome in the Healthcare domain.

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