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Expenses Rising? How Automation in Healthcare and Data Capture Can Help Lower Costs 

Authored by: Dan Smith

The past few years have been rocky for many industries, including healthcare. High labor costs, talent shortages, and inflation are driving up the cost of practically everything – and putting increased pressure on the medical industry.  

An MGMA Stat survey found that 90% of medical practices reported costs rose faster than revenues in 2022, while only 10% reported revenues keeping pace with or ahead of rising costs. As a result, many seek new strategies to optimize workflows.  

One strategy is leveraging data capture technologies, such as optical character recognition (OCR) to help turn documents into data and streamline manual tasks that interfere with optimized workflows. But how does it work?  

Automation in Healthcare and The Benefits of Data Capture  

As you work to optimize processes and workflows, using a healthcare automation technology such as data capture has many benefits. 

Removes expensive bottlenecks. Automated document processing reduces hidden labor costs associated with manual tasks, such as data entry. You can also quickly get rid of backlogs that might otherwise result in expensive overtime or short-term labor expenses.  

Improves data accuracy. Automating processes helps reduce human error. Data capture, for example, enables the creation of business rules to improve accuracy quickly.  

Supports improved compliance. With an automated solution, data fields can be selected automatically, eliminating the need to enter data manually. Also, these metafields can trigger records management and retention rules, helping improve compliance and data search and discovery.  

Allows faster response to customers. When data appears in systems faster, your team can give customers answers more quickly. For example, imagine reducing customer response times from four days to one because you have the correct data to provide the appropriate response.  

Automation in healthcare: How does it work?  

At a high level, you might know that data capture helps remove manual tasks associated with getting data into your systems. But at a granular level, you might wonder, OK, but how exactly does that work? 

Here’s a quick rundown:  

  1. Image capture. The process starts with a scanned, imported, or emailed image or other relevant documents. For example, your software may monitor incoming mail, automatically identify each document type, and capture key data.   
  2. Classification and data capture. By applying classification, documents are automatically identified, sorted, and routed to the right person or department. It can utilize the physical attributes of a document image, match it to a library of images, or even “read” the document to determine content. The ability to classify incoming documents reduces the need for staff to sort documents before processing them manually.  
  3. Validation and processing. Traditionally, templates were necessary for automating the extraction of data from document images; however, modern technology no longer relies on them. Intelligent data capture can process a variety of document layouts without fixed templates using methods such as data label searching. This allows automation location and extraction of various data, such as invoice details, regardless of vendor-specific layouts. The system also remembers data locations for future instances. The captured data is then validated by use-defined tools, integrated with existing databases, and transferred to back-end systems to streamline processes.  

Automation in healthcare: What to do next 

Perhaps you’re interested in optimizing workflow through data capture but unsure of the next best steps. We’d recommend the following:  

  1. Review your current situation with paper, scanning, and data capture. Determine which processes are good candidates for removing paper and manual efforts. 
  2. Identify the specific steps that could be removed if the information is electronically captured from the document, whether paper, PDF, email, or some other format. For example, maybe you eliminate the need to read a document by using a technology with OCR healthcare capabilities.  
  3. Find a partner experienced in your industry. Ask how a prospective partner has helped other clients in your industry, review case studies, and speak with their prior clients.  
  4. Identify a pilot program that involves integrating scanning and capture in one of your processes.  

And remember that you can start slowly. You don’t need to tackle several processes immediately. Implement, measure results, and then move on to other processes. And if you need assistance optimizing your workflows, we can help.

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