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In the era of value-based healthcare, organizations are looking for innovation in healthcare with RPA, AI and automation technologies. We all have seen how functions ranging from diagnostics and pharmaceuticals to appointment scheduling and doctor-patient communication are all being enhanced by using automation algorithms all the way across the sector.

But is automation enough? However, embracing automation is the first step to being future-ready in the digital era, but to be clear about what artificial intelligence has to offer to healthcare and how it will evolve automation from here is the key to ensuring healthcare enterprises can gain the most out of it.

How does AI add value to decision intelligence in healthcare?

The answer is that it solves the problem that has been already faced by healthcare professionals like-

  • Data entry
  • Managing healthcare apps
  • Scheduling high-volume appointments
  • Optimizing healthcare operations

And one thing that is common in embracing automation and its impact on healthcare organizations is that we are more digitally connected and drowning in data. Hence, to manage our daily relationship with data that is changing every second, AI and MAchine learning algorithms will be necessary to find important signals in the sea of noises that stream in from digital devices. And if we want to add decision intelligence to healthcare operations or processes, we need to master all the data. That’s where the true value of AI lies.

At both individual and organizational levels, decisions are influenced by a multitude of experiences and biases, but all these decisions come from vetting information or data. However, humans are constantly weighing up probabilities based on the data provided for better healthcare decision making but the ability to make logical decisions get mucked up when there are too many compelling probabilities. For example, consider a problem that has 5000 probable solutions along with 5000 streams of information, and healthcare professionals have to make the best possible decision for the problem.

This voluminous data and its complexity are way beyond human capability. That’s what healthcare professionals often struggle to cope with. Consuming massive amounts of information flowing from multiple sources and determining patterns to rank relevance and sort variables and determinants for all those options is what our AI models excel at. Artificial intelligence can surface what is pertinent to support wise human decision-making. Applying AI and RPA in healthcare decision intelligence leads to a plethora of benefits like:

  1. Better data processing for building quality electronic health record management
    Most healthcare organizations don’t store their medical information in a standardized way. Hence, the chances of inaccuracy and error are very common, and healthcare organizations have a lot of work to do before they can even start building EHR management. Hence building quality electronic healthcare management requires a smooth transition of raw data into a structured one. And to make this happen, AI is the best probable solution. Utilizing AI technologies like Machine Learning, OCR, and NLP helps transform raw data into a structured format per healthcare requirements. Moreover, leveraging this process leads to low time spent on collecting data for maintaining patient records. In short, healthcare professionals get complete health records of patient medical history in one glance. That’s how electronic health record management helps enterprises take corrective action to provide better healthcare options and quality care to patients.
  2. Developing a work-friendly workflow for robust patient care
    We all have seen how patient scheduling an appointment has impacted the way healthcare organizations offer patient care. But to make it more effective, AI is the solution to discover patterns in patient health. For example, research has stated that AI can easily scan kidney disease and accurately forecast cancer remission rates. Including the AI capabilities helps healthcare professionals take proactive action before further development in any disease. In addition, AI also keeps track of how information moves through the system and is routed to the right person, as it directly impacts the critical decision-making process.
  3. Enhancing healthcare professionals’ skill sets for better decisions
    Enabling AI in a healthcare organization is easy, but making it adaptable for healthcare professionals is a must to create a scalable decision-making process. Any AI tool directly impacts everyone, including in the healthcare process ranging from staff to doctors. Hence, educating healthcare professionals is the first step to ensuring that clinical professionals can do their job successfully. In addition, enhancing healthcare professional skills helps professionals understand how a particular process often works when a model fails. This not only helps in developing an agile and flexible model but also helps retain new talent that can better understand how data and AI tools work for better decision-making.

In a world of rapid change and rapidly changing relationships with information, healthcare organizations must improve their decision intelligence by utilizing AI technologies because AI is the key to unlocking opportunities to add decision intelligence into healthcare organizations that functionalize over growing streams of data and constant learning to make information easily accessible for better decision making. Want to make your clinical decision more robust with AI? Give them a boost with the AutomationEdge RPA solution. Catch this webinar to learn more about how AutomationEdge Conversational AI and Automation help healthcare organisations with higher process efficiency.