In addition to prevailing industry trends, digital transformation is a key component of the strategies of today’s advanced hospitals and health systems. It engages healthcare organizations with their customers – the highly digital patients.
This is one of the most important topics healthcare CIOs and other health IT and C-Suite leaders can talk about today. That’s why we sat down to chat with Dr. Gauri Puri, chief business officer, life sciences and healthcare business unit, at WNS, a global business process management company works with businesses across many industries, including healthcare.
Here, we discuss what successful digital transformation of processes like administration, revenue cycle, and clinical management looks like; a digital-first model for clinical management and revenue cycle and how providers can approach its adoption; and how emerging technologies can help suppliers prevent problems such as revenue loss and payment delays.
Q. What does successful digital transformation of processes like administration, revenue cycle and clinical management look like for you?
ONE. This includes several key elements. First, it involves optimizing workflows to eliminate manual tasks and streamline operations.
In our experience, 60-70% of scheduling and appointments are manual and patients do not have a simple and intuitive app or portal to self-manage their care. Similarly, seamless data exchange between hospitals, health insurance systems, and regulations is critical for efficient operations. Automation driven by artificial intelligence and analytics helps improve productivity and accuracy across a variety of tasks.
For example, in RCM, manual processes from coding to claim submission are replaced by technologies such as robotic process automation, optical character recognition, and synthetic AI.
These technologies automate tasks such as verifying patient eligibility, collecting fees, and managing denials, ensuring high data accuracy and faster processing times. AI-powered predictive analytics and tokenization will further optimize revenue generation and cash flow.
Similarly, hyper-automation streamlines administrative processes such as appointment scheduling and patient registration, integrating them into a unified platform. GenAI-based chatbots empower patient self-service, while automation bots handle time-consuming tasks like data entry, allowing administrative staff to focus on value-added activities .
In clinical management, automation, AI, machine learning, and genAI technologies have revolutionized workflows, enabling real-time access to patient data and comprehensive clinical guidance. Automated clinical workflow, transcription, and clinical note creation improve efficiency and accuracy, while AI-powered decision support systems optimize patient care and staff productivity. pellets.
This solves an important problem for nurses and physicians, who currently spend the majority of their time gathering administrative and clinical information and still lack access to clinical guidelines most relevant or up-to-date 360-degree view of patient information.
Data integration and interoperability are key ingredients for successful digital transformation in healthcare. Seamless connectivity between systems enables better decision making and coordination, improving patient outcomes and operational efficiency.
However, comprehensive transformation goes beyond technology implementation. It involves developing a comprehensive strategy, establishing a strong data and technology foundation, building scalable operating models, and driving change management for digital adoption. By leveraging these elements, healthcare organizations can navigate the complexities of digital transformation and deliver enhanced value to patients and stakeholders.
Ask. What is the digital-first model for clinical and revenue cycle management, and how can providers approach adopting it?
ONE. The digital-first model for clinical and RCM prioritizes the use of digital technology, data-driven approaches and digital thinking to streamline operations, improve efficiency and enhance High patient care outcomes.
It aligns with the Quadruple Aim of healthcare: improve patient experience; improve people’s health; discount; and improving the work hours of health care providers.
From the patient’s perspective, a digital-first approach means allowing: remote consultations or visits via their preferred channel; personalized self-service appointment scheduling; and transparent access to their healthcare data.
This is powered by intuitive portals, AI-based insights, and virtual care options.
For RCM teams, a digital-first model includes implementing touchless requests and pre-authorizations, automating data collection and coding processes, and leveraging advanced analytics high for data-based decision making. This enables teams to prevent declines, analyze payments, and conduct effective follow-up on accounts receivable.
In clinical management, a digital-first approach enables personalized care by leveraging comprehensive patient data mapped to clinical guidelines. GenAI is used to automate the capture of relevant patient-provider interactions, enhancing clinical decision-making and patient outcomes.
To adopt a digital-first model, service delivery organizations should prioritize patient needs and reimagine processes, systems and interactions accordingly. This involves implementing digital workflows, digitizing processes and enhancing customer-centric experiences.
Integrated digital platforms including EHR, practice management systems and RCM technology are essential, facilitating seamless communication and data sharing between clinical and administrative departments.
Providers should opt for digital portals to onboard patients, schedule appointments, access medical records, and handle patient inquiries, promoting better engagement and empowerment. For clinical processes, automated workflows and AI-enabled decision support systems will improve turnaround times, enhance the clinical staff experience, and increase productivity.
Adopting the right digital-first model starts with defining a digital strategy and evaluating current processes to identify transformation opportunities. Providers should clearly define goals, evaluate workflows and technology infrastructure, and address weaknesses in clinical operations and RCM.
Building the right talent pool, establishing cross-functional teams, and cultivating a culture of agility and innovation are critical factors for success. Strong governance and change management practices ensure effective program management and adoption, while a powerful data platform drives insight and transformation from end to end.
Overall, a digital-first approach helps providers deliver high-quality care, improve operational efficiency, and deliver positive outcomes for patients and stakeholders.
Ask. How can emerging technologies help suppliers prevent problems such as revenue loss and payment delays, and what are these emerging technologies?
ONE. Emerging technologies play a key role in helping healthcare providers prevent problems such as revenue leakage and payment delays, ultimately ensuring good revenue and flow. Money is enhanced. Advanced analytics serves as the foundation to detect the root causes of revenue leakage, AR aging reasons, and declines.
Vendors can leverage a combination of technologies, including data analytics, AI and ML algorithms, business intelligence tools, and predictive analytics to optimize their RCM processes.
One key area where emerging technologies are making a significant impact is patient collections and AR management. By harnessing data analytics and predictive modeling techniques, providers can assess patient payment trends and prioritize collection efforts accordingly.
Collections analytics can predict timely payment based on historical and demographic data, allowing collection agencies to tailor their strategies and communication channels for maximum efficiency. This targeted approach has resulted in notable improvements, with collection rates increasing by 20-30% for our customers.
In addition, collection analytics also assists providers in providing effective collection strategies for patients who default. By identifying the most appropriate communication channels and offering personalized payment plans, suppliers can minimize bad debt ratios, leading to stronger financial performance. We have seen this strategy reduce bad debt ratios by 10% for our clients.
On the payer side, AI and ML algorithms analyze large amounts of claims data to identify patterns and predict high-risk claims that may be denied. This proactive approach allows providers to intervene in advance, address potential payment delays, and reduce overall decline rates. Furthermore, leveraging genAI-powered coding tools will enhance coding accuracy and minimize coding-related rejections, further optimizing RCM processes.
Overall, collections analytics and left-shift analytics initiatives aim to improve financial performance, reduce bad debt, and enhance patient experience by streamlining the revenue cycle and processes. payment collection process. By leveraging data-driven insights and emerging technologies, healthcare providers can make their RCM processes more efficient, benefiting the whole family. provider and patient.
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