The healthcare industry is incredibly complex, where daily challenges test the limits of staff and patients alike. Fortunately, automation has emerged as a vital remedy to help cure the sector’s ailments.

    From delivering medication to diagnosing diseases, around 50% of the work in healthcare is automatable. Indeed, the impact automation has on the healthcare sector is decisive. It promises a future where efficiency, accessibility and patient-centric care converge in unprecedented ways.

    With the UiPath Platform enabling the sector to automate administrative operations, clinical workflows and other business functions, it’s crucial automation within healthcare is implemented correctly.

    To do so, healthcare providers must understand both the opportunities and challenges posed by automation to harness its full potential.

    First, the benefits.

    How can automation help healthcare?

    With the responsibility of lowering costs and enhancing care quality becoming a top priority, healthcare providers need to adapt to the modern landscape. Automation is simply the next step.

    Healthcare professionals can harness automation to revolutionize administrative processes, elevate patient care, optimize diagnoses and usher in a data-driven era of informed decision-making.

    1) Boosting administrative productivity and efficiency

    In the quest for optimized healthcare delivery, administrative tasks play a pivotal role. Automation offers a compelling solution to streamline operational costs and reshape administrative processes, such as improving employee onboarding and reducing errors.

    Through automated workflows of routine tasks, healthcare providers can allocate more resources strategically to patient care, leading to improved patient satisfaction as well as bolstering productivity and efficiency.

     2) Elevating patient care and engagement 

    But at the heart of healthcare lies patient care.

    With automation’s support, patient care is being radically elevated. Healthcare providers can enhance patient engagement through personalized communication, automated appointment reminders and secure access to medical records.

    Not only that but with other processes being automated, it frees up healthcare providers to focus more on patients. For example, InHealth saved nearly 21,000 hours of work through automation, allowing them to provide an enhanced patient experience and an improved healthcare service.

    3) Enhancing clinical decision-making with data insights

    By processing vast amounts of patient data, automation assists healthcare providers in identifying patterns, predicting outcomes and tailoring treatment plans.

    Employing AI in the right way can also lead to quicker detection of life-threatening diseases. Take the model developed to predict the presence of Acute Kidney Injury (AKI) in patients up to 48 hours in advance; it helped doctors determine treatment options to prevent further deterioration of the kidney(1).

    These data-driven insights not only improve the accuracy of diagnoses but also foster a more proactive and personalized approach to patient care that could save more lives.

    The challenges of automation in healthcare 

    While the promise of automation in healthcare is huge, it’s essential to acknowledge that there are often hurdles that come with any change. Much like other industries, the healthcare sector faces a number of barriers as it navigates the automation landscape.

    1) The cost to automate

    The adoption of automation often comes with an upfront investment as well as other costs that are needed in support of the technology change. It can all quickly stack up.

    Balancing these costs against the anticipated benefits can be a significant challenge for healthcare providers, especially those operating on tight budgets or tied to government funding. However, the cost of not embracing automation will, in most cases, be higher.

    2) Data security becomes a bigger concern

    With bots now automating and interacting with patient and organizational data, it often raises concerns about data breaches and unauthorized access. However, research has revealed that up to 85% of data breaches are caused by employee mistakes, not robots(2).

    Robust data security still remains a crucial task but when implemented correctly, automation can, in fact, improve data security.

    3) The fear of job losses

    The fear of machines replacing humans will most likely never go away. The anxiety that automation brings looms large in staff, raising questions about the workforce’s future and the impact on patient care.

    But automation replaces tasks, not jobs. Therefore, it’s important to address any concerns with staff early on in the automation journey, emphasizing how it’s there to enhance human capabilities rather than replace them.

    It’s also important to remember that there are huge skills and resource gaps in healthcare. Automation can fill them, making people’s work more manageable rather than replacing them.

    4) Ethical considerations of automation in healthcare

    The integration of automation brings ethical concerns that demand careful consideration too. The prospect of robots making decisions in patient care, without a human touch, can understandably spark concerns.

    The phenomenon of ‘automation bias’ – where people blindly trust machines – raises concerns about patient safety and accurate assessments. It can lead to medical misdiagnoses, as seen in a recent study with radiologists relying on an AI system for mammogram scoring, despite the AI deliberately giving wrong answers. When the AI provided truthful scores, human accuracy remained high and aligned with the AI. But when the scores were deliberately wrong, human accuracy plummeted, even among experienced radiologists(3).

    Knowing when and where to use automation within healthcare is, therefore, key.

    Implementing automation the right way

    To start implementing automation the right way, the first step is discovering opportunities for process and task improvements, as well as identifying the highest ROI areas for automation. To achieve this, it’s essential to gain complete transparency into every process, task and service, finding where you can transform these elements through automation.

    This process involves understanding all the intricacies of the healthcare journey, mapping out how clinicians, nurses and doctors work and prioritizing areas based on their impact and ROI.

    Next is implementation. With the UiPath platform, automation can be applied to any system. Whether it’s an existing legacy system or something new, robots can be added to work alongside people on everyday mundane tasks, freeing staff to focus on providing better patient care.

    Finally, make sure that your automation operates on a foundation that meets enterprise-level standards to further mitigate any risks and ensure efficiency. Working with a trusted UiPath partner can guarantee this is done correctly.

    Ultimately, the smallest decisions can have the biggest impact in healthcare. So, it’s important to support your automation program effectively with ongoing testing and monitoring to ensure its reliability, accuracy and continued efficiency in delivering results and minimizing errors.

    Time to automate?

    Automation continues to revolutionize the industry by enhancing administrative processes, improving operational efficiency and enabling healthcare professionals to focus on what truly matters – providing the best possible care. And Tquila Automation is here to help your organization find the path to your automation needs, providing a comprehensive range of tailored solutions.

    Upholding the UiPath standards, Tquila has the tools to help streamline your operations from beginning to end, helping both patients and healthcare professionals.

    Schedule a free consultation with our experts today.

    (1) VA News, DeepMind develop machine learning system to predict life-threatening disease before it appears
    (2) Tessian, Psychology of Human Error
    (3) Forbes, How ‘Automation Bias’ Plus Artificial Intelligence Can Lead To Medical Misdiagnoses