How to safely implement RPA in Healthcare
Robotic Process Automation (RPA) is a technology that often goes unnoticed – do you know how to leverage its full potential?
Proservartner constantly explores the potential of cutting-edge technologies like artificial intelligence but we also enjoy delving deep into the potential of the technologies like RPA which have less hype surrounding them but are often easier and more affordable to implement with a quicker impact and ROI. Without further ado, let’s dive in!
RPA employs software to automate repetitive and rule-based tasks, particularly those involving data manipulation and integration across diverse systems. In healthcare, RPA has the potential to be a transformative force, offering the promise of improved efficiency, cost reduction, enhanced quality, compliance plus – most importantly – superior patient outcomes and satisfaction.
RPA can be seamlessly fused with artificial intelligence to forge intelligent automation solutions capable of handling intricate and unstructured data sets, including Natural Language Processing (NLP) and Optical Character Recognition (OCR). All of these tools working in harmony opens up a realm where healthcare organisations can harness cognitive capabilities such as machine learning, computer vision, and natural language generation to dramatically elevate their automation capabilities.
The potential benefits of RPA in Healthcare
RPA holds the potential to deliver an array of advantages to healthcare stakeholders, including providers, payers, and patients:
Streamlined Administrative Processes: RPA excels at automating tasks like patient scheduling, billing, claims processing, reporting, and data entry. This automation reduces errors, saves time, and liberates staff to focus on value-added activities. For instance, RPA can enable patients to autonomously schedule appointments online and dispatch automated reminders to minimise no-shows.
Improved Clinical Documentation: RPA aids clinicians in documenting patient encounters, diagnoses, treatments, and outcomes by capturing data from electronic health records, voice recognition systems, and other sources. It can also assist in coding and billing by applying appropriate codes and modifiers based on clinical documentation, thereby enhancing accuracy, compliance, and revenue cycle management.
Enhanced Patient Care: At the core of these benefits lies the value delivered to patients themselves. RPA supports patient care by facilitating treatment coordination, case management, and remote patient monitoring. It aids in tracking patient progress, issuing alerts and notifications, offering personalised recommendations, and fostering communication between patients and healthcare providers. Furthermore, it can analyse data from various sources to identify high-risk patients requiring proactive interventions.
Learning from the successes (and failures!) of others
As healthcare providers increasingly adopt RPA tools, we’ve observed positive outcomes and success stories shared by companies specialising in RPA for healthcare, including IBM, New Dawn Robotics, and Telus International.
Challenges of Implementing RPA in Healthcare: Despite the promise of RPA, certain challenges must be acknowledged and addressed before implementing this technology in healthcare settings. Some of these challenges are familiar, echoing issues previously encountered with emerging AI tools. It is crucial to be mindful of these considerations:
Data Security and Privacy: Healthcare data is quite rightly held to the highest standards of sensitivity and subject to a number of stringent regulations, not to mention GDPR and HIPAA. Any RPA solutions implemented must therefore prioritise data encryption, anonymity, secure storage and restrict access to a limited list of authorised personnel. Additionally, RPA solutions need to adhere to comprehensive audit trails and reporting requirements to demonstrate accountability and transparency.
Integration and Interoperability: Healthcare systems are frequently complex and fragmented, often involving multiple incompatible or non-standardised legacy applications and platforms. RPA solutions must seamlessly integrate with existing systems and processes without disrupting workflows or compromising data quality. They should also be versatile enough to handle various data formats and sources, encompassing both structured and unstructured data.
Digital Transformation and Governance: Implementing RPA in healthcare necessitates a cultural shift and there must be a crystal-clear vision of the desired outcomes. As a result, to secure buy-in and adoption, healthcare organisations must involve stakeholders from diverse levels and functions in the planning, design, testing, deployment and monitoring of RPA solutions. Moreover, establishing defined roles and responsibilities for managing RPA solutions, including ownership, maintenance, updates, performance evaluation, and risk mitigation, is imperative.
Valuable lessons can be gleaned from the implementations businesses have already gone through. Healthcare organisations (or indeed any company) contemplating RPA adoption should keep the following principles in mind:
- Utilising RPA entails more than just investing in technology; it’s a form of business transformation.
- Competencies in RPA should be developed incrementally, recognizing that this change, like any other, requires careful facilitation, management and governance.
- Start with small-scale pilot projects targeted at ‘low hanging fruit’ to gain insights into the scope of internal processes, identify areas of friction and assess the potential for more widescale RPA integration across a whole organisation.
- Engage and empower all key stakeholders affected by the transition at an early stage.
- Involve the legal team early in the process to understand and navigate potential regulatory hurdles.
RPA has the potential to revolutionise healthcare operations and outcomes by automating repetitive and error-prone tasks in the same way that many other industries have begun doing. However, it also presents challenges that demand careful consideration before adoption. Organisations must conduct thorough assessments of their existing processes and requirements, evaluate the feasibility and appropriateness of RPA solutions for their specific use cases, and implement best practices to ensure data security, seamless integration, effective change management, and robust governance.
"RPA has the potential to revolutionise healthcare operations and outcomes"