Digital transformation is not only all the rage in the industry, but is also an important part of the strategy of forward-thinking hospitals and healthcare systems today. It aligns healthcare organizations with their customers – highly digital patients.
This is one of the most important topics for healthcare CIOs and other healthcare C-suite and IT leaders to talk about today. That’s why we went to talk to Dr. Gauri Puri, Chief Business Officer, Healthcare and Life Sciences business unit, at WNS, a global business process management company that works with companies across industries including healthcare.
Here we discuss what successful digital transformation of processes such as administration, revenue cycle and clinical management looks like; a digital-first model for clinical and revenue cycle management, and how providers can approach adoption of this model; and how emerging technologies can help providers avoid problems such as revenue leakage and payment delays.
Q. What does a successful digital transformation of processes such as administration, revenue cycle and clinical management look like to you?
A. This includes a number of important elements. First, it’s about optimizing workflows to eliminate manual tasks and streamline operations.
In our experience, 60-70% of scheduling and appointments are done manually and patients do not have simplified and intuitive apps or portals to manage their own care. Likewise, seamless data exchange between hospitals, health insurers and regulatory systems is critical for efficient functioning. Automation, powered by artificial intelligence and analytics, improves productivity and accuracy across tasks.
For example, in RCM, manual processes from coding to claims submission are being replaced by technologies such as robotic process automation, optical character recognition and generative AI.
These technologies automate tasks such as patient eligibility verification, charge capture, and denial management, ensuring high data accuracy and faster turnaround times. AI-powered coding and predictive analytics further optimize monetization and cash flow.
Likewise, hyperautomation streamlines administrative processes such as appointment scheduling and patient registration, integrating them into a unified platform. GenAI-based chatbots enable patients to serve themselves, while automation bots perform time-consuming tasks such as data entry, freeing administrative staff to focus on value-added activities.
In clinical management, automation, AI, machine learning and genAI technologies are revolutionizing workflows, enabling real-time access to comprehensive patient data and clinical guidelines. Automated clinical workflows, transcription and clinical note generation improve efficiency and accuracy, while AI-based decision support systems optimize patient care and staff productivity.
This solves a critical problem for nurses and doctors, who currently spend most of their time collecting administrative and clinical information and still do not have access to the most appropriate clinical guidelines or an updated 360-degree view of patient information.
Data integration and interoperability are crucial components of a successful digital transformation in healthcare. Seamless connectivity between systems enables better decision-making and coordination, improving patient outcomes and operational efficiency.
However, holistic transformation goes beyond the implementation of technology. It includes developing a comprehensive strategy, establishing robust technology and data foundations, building scalable business models, and driving change management for digital adoption. By embracing these elements, healthcare organizations can tackle the complexities of digital transformation and deliver greater value to both patients and stakeholders.
Q. What is a digital-first model for clinical and revenue cycle management, and how can providers approach this model?
A. A digital-first clinical and RCM model prioritizes the use of digital technologies, data-driven approaches and a digital mindset to streamline operations, improve efficiency and improve patient care outcomes.
It aligns with the Quadruple Purpose of healthcare: improving the patient experience; improving public health; reducing costs; and increasing the working lives of healthcare providers.
From the patient’s perspective, a digital-first approach means enabling: teleconsultations or visits through their preferred channel; book personalized self-service appointments; and transparent access to their healthcare data.
This is made possible by intuitive portals, AI-driven insights and virtual care options.
For RCM teams, a digital-first model includes implementing touchless prior authorizations and claims, automating data collection and coding processes, and leveraging advanced analytics for data-driven decision making. This allows teams to prevent refusals, analyze payments and carry out efficient accounts receivable follow-ups.
In clinical management, a digital-first approach enables personalized care by using comprehensive patient data aligned with clinical guidelines. GenAI is used to automate the capture of relevant patient-provider interactions, improving clinical decision making and patient outcomes.
To adopt a digital-first model, healthcare organizations must prioritize patient needs and reimagine processes, systems and agreements accordingly. This includes implementing digital workflows, digitizing processes and improving customer-facing experiences.
Integrated digital platforms that include EHRs, practice management systems and RCM technologies are essential and facilitate seamless communication and data exchange between clinical and administrative departments.
Providers should opt for digital portals for patient onboarding, scheduling appointments, accessing medical records and handling patient queries, promoting better engagement and empowerment. For clinical processes, automated workflows and AI-based decision support systems improve turnaround times, improve clinical staff experience, and increase productivity.
Adopting the right digital-first model starts with defining a digital strategy and assessing current processes to identify transformational opportunities. Providers must clearly define goals, assess workflows and technology infrastructure, and address pain points in clinical and RCM operations.
Building the right talent pool, establishing cross-functional teams and fostering a culture of flexibility and innovation are crucial for success. Strong governance and change management practices ensure effective program management and implementation, while robust data foundations drive insights and end-to-end transformation.
Overall, a digital-first approach enables providers to deliver high-quality care, improve operational efficiency, and drive positive outcomes for patients and stakeholders.
Q. How can emerging technologies help providers avoid problems such as revenue leakage and payment delays, and what are these emerging technologies?
A. Emerging technologies play a crucial role in helping healthcare providers avoid issues such as revenue leakage and payment delays, ultimately ensuring healthy revenue and improved cash flows. Advanced analytics serves as the cornerstone for pinpointing the root causes of revenue leaks, AR aging, and denial reasons.
Providers can leverage a combination of technologies, including data analytics, AI and ML algorithms, business intelligence tools and predictive analytics, to optimize their RCM processes.
A key area where emerging technologies are having a significant impact is patient collections and AR management. By using data analytics and predictive modeling techniques, healthcare providers can assess patients’ willingness to pay and prioritize collection efforts accordingly.
Collections analytics can predict the likelihood of on-time payments based on historical data and demographics, allowing collection agencies to tailor their strategies and communication channels for maximum effectiveness. This targeted approach has led to remarkable improvements, with a 20-30% increase in collection rates for our customers.
Additionally, collections analytics helps providers devise effective debt collection strategies for patients who fail to pay. By identifying the most appropriate communication channels and offering personalized payment plans, providers can minimize bad debt rates, leading to more robust financial performance. We have witnessed this strategy result in a 10% reduction in bad debt for our clients.
On the payer side, AI and ML algorithms analyze vast amounts of claims data to identify patterns and predict high-risk claims that are likely to be denied. This proactive approach allows providers to take preventive action, address potential payment delays and reduce the overall denial rate. Additionally, using genAI-powered coding tools improves coding accuracy and minimizes coding-related rejects, further optimizing RCM processes.
Overall, collections analytics and shift-left analytics initiatives are aimed at improving financial performance, reducing bad debt, and improving the patient experience by streamlining the revenue cycle and payment collection processes . By leveraging data-driven insights and emerging technologies, healthcare providers can make their RCM processes more efficient and effective, benefiting both healthcare providers and patients.
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