Untitled

Hyperautomation refers to the use of next generation technologies such as RPA, Artificial Intelligence, Analytics, NLP, etc. to enable end-to-end automation of processes. There is a rapid growth in Healthcare companies using hyperautomation to ensure adherence to regulatory compliance, quality control, automation of manual tasks and improvement in clinician/patient experience.

The inefficiency in healthcare systems addressed by automation is far-reaching, impacting the entire arena of healthcare operations; from patient data management, claims operations, customer support to patient-HCP engagement. Gartner predicts that the hyperautomation market will reach $596 Billion by 2022. The 2020 healthcare landscape is rapidly changing with electronic health records, digital patient engagement, wearable sensors, etc. generating enormous amount of big data on a daily basis. Life Sciences & Healthcare companies use this data for research purposes to improve patient outcomes, develop personalized therapy for patients, and improve the quality of drugs/care; while adhering to regulatory compliance.

Below are a few challenges leading pharma and healthcare companies face while dealing with large sets of data:

Siloed legacy systems largely depending on manual processes and fragmented internal workflows

Zero process transparency for patients/HCPs and non-adherence to Audit Trail compliance

Backbreaking, repetitive tasks consuming several man-hours leading to high operating cost

Manual error-prone processes pose a persistent operational & regulatory challenge

Hyperautomation addresses these challenges from the beginning till the end without requiring any human intervention, and thereby seamlessly complying with quality & regulatory guidelines.

The Rise of Intelligent Automation in Healthcare: Key Drivers

The global COVID-19 pandemic came as a surprise wake-up call for many organizations that did not invest in digitization and automation prior to 2020, and instead relied on legacy systems & practices. Moreover, the number of people requiring healthcare assistance is consistently rising along with the associated healthcare expenses. To be able to meet this increase in demand and make compliant and quality healthcare available to patients, the healthcare and pharmaceutical industry needs to invest in automation technology.

Rise in operational problems and repetitive tasks pose a barrier to the accessibility of high-quality healthcare. Using technologies such as RPA could add value across the entire ecosystem. This way, healthcare/research professionals can focus on higher-value, human-led decision making, diagnosis, scientific research, and treatment. Intelligent Pharma companies are also in dire need to fast-track drug discovery, vaccine development, and clinical trials by automating processes related to documentation, regulatory monitoring & compliance management.

While the healthcare industry largely relies on the expertise, training, and experience of clinical specialists for decision-making that needs human capabilities, there are quite a few areas where digital intervention can improve the care circle.

Hyperautomation Use cases for Healthcare Quality & Compliance

Hyperautomation is scaling automation and redefining patient’s accessibility to care, thereby positively impacting health outcomes, adding capabilities to existing processes, enhancing the value of both data and human expertise. Few Intelligent automation use cases that are gaining traction in the healthcare regulatory & compliance space include:

Voice Biometrics technology can be used to identify patients. It analyzes patients’ voices using complex algorithms to authenticate their identity and match it with the data provided on his or her registration form. This gives an extra layer of security as well as ensures no one impersonates a patient during any sort of interaction.

Artificial Intelligence in the form of chatbots or virtual assistants such as Siri, Google assistant, etc. can be fed with select use cases based on user’s input/feedback to provide answers to questions posed by users through self-learning algorithms. Such tasks can include answering FAQs, patient queries, managing appointment schedules, etc. which are being deployed in companies like Philip’s health technology.

Introducing RPA will bolster the automation of repetitive tasks such as claims processing which can reduce manual processing operational costs by up to 80%

Investing in Big Data & Analytics in the pharma supply chain will enable data to be looped back into manufacturing, and other data storage systems, providing greater visibility for quality compliance, adherence to regulations, and scalable manufacturing with agile supply chains.

Tracking quality issues of pharmacovigilance and adverse event handling–predicting & preventing errors regarding regulatory submissions or complaints around shipments & samples, etc.

Automation of the backend revenue cycle management, creating AI-driven care management to improve patient health outcomes, enhanced payer-provider interaction, voice-enabled patient experience- all of it can be achieved by eliminating internal functional silos to create smoother operations. These next-gen technologies also aid in accelerating and streamlining business processes by auto-populating patient forms, transferring patient data between systems, collecting data from disparate sources, performing analytics and generating reports on the same. Controlled access to data and audit trail stamps largely contributes to reducing compliance risk for the healthcare industry.