How to Avoid Spending Hours Abstracting Data from Patient Records
Data management in the healthcare industry is about improving patient lives. When managed correctly, reliable, relevant data is available for quick access and review, allowing care providers and/or payors the opportunity to make the best decisions and provide the best possible care in the shortest amount of time. An added bonus is often improved operations, as well. Time is money, after all. But how can the healthcare industry manage the big data sets that now come with the array of modern technologies; the volume, velocity and variety of information is often massive, inundating data stores so that it can be difficult to find, much less make meaning from, any one specific data point? The key is automation, which replaces repetitive, manual tasks with robotic labor, laying the groundwork for compounding digital cognition that further improves outcomes within the healthcare sector.
Using Automation for Selecting and Abstracting Data
Automation is the process by which a machine and/or technology replaces human input during certain applications. The term was first coined in the 1940s to describe the increasing use of machines on automotive production lines that was beginning to replace some of the need for human factory workers. Today, automation is more sophisticated and a lot more prevalent, often involving computers that not only can execute specific rule-based processes, but can even “learn” and implement new processing strategies using ongoing, machine-directed analysis (i.e., artificial intelligence or “AI”). In the healthcare industry, an industry that depends on timely, accurate information, automation frequently means faster, cheaper, more effective care because it removes the need for hours and hours of manual work, freeing up medical staff and other healthcare providers so they can perform more complex (often life-changing!) tasks.
The Benefits of Robotic Process Automation
Many manual data management tasks can be relegated to a Robotic Process Automation (RPA) system. For example, instead of spending hours selecting and abstracting data from patient records one at a time, an organization can use a program which enables a computer to autonomously identify, validate, record, organize and retrieve specific data points from a data set based on its own diagnostic needs and/or business objectives. And while RPA doesn’t completely negate the need for human-led reasoning and judgement, it can and does make data selection and data abstraction much more efficient processes since it:
- Helps Eliminate Duplicate Data
- Allows More Time for Patient Care
- Lowers the Cost of Patient Care
- Improves Patient Care
The Amitech Advantage
To learn more about using Robotic Process Automation, AI and machine learning processes to improve your organization’s information management so that you can avoid spending hours selecting and abstracting data, please contact us. Our experience ensures that our clients develop applications for automation that capture the data they need to deliver the most valuable and meaningful insights, with the objective always being the highest quality of care.