Ask the Expert: What is Auto-Indexing and How Does It Work?

Blogs, Auto-indexing

Author: Ruchi Medhekar, SVP, Strategy & Platform


Vyne Medical is dedicated to helping hospitals and health systems capture and share information to create a more complete patient record, expedite workflow and recover lost revenue. Auto-indexing accomplishes these key objectives by quickly and accurately transforming documents into structured, reliable data.

What is Auto-indexing within Trace?

The Trace® platform captures and integrates voice, fax and image data into a searchable, centralized database for easy access across the enterprise. Our Auto-indexing functionality leverages advanced machine learning and form recognition technology to read incoming text data, map it to targeted fields and incorporate it into the patient record within Trace.

How does Auto-indexing work?

To accomplish Auto-indexing, we train our software to recognize certain types of patient demographic information contained in client-provided forms. The software learns to recognize patterns in unstructured form data and converts it to structured data. Data is automatically retrieved, classified and populated into the appropriate fields in Trace.

What types of documents are the ideal fit for Auto-indexing?

The best documents for Auto-indexing are high-volume forms that account for a significant portion of a hospital’s weekly fax volume. This allows us to extract data in a consistent, repeatable manner. The forms should be text-based, not hand-written, and contain compatible data fields such as blocks for name and address rather than checkboxes or bubbles.

How does Auto-indexing save time for hospital staff?

Without Auto-indexing, employees are required to manually open each inbound document, search for required fields, interpret information, and hand-key patient data. With Auto-indexing, inbound documents arrive with common data already classified and pre-populated into the appropriate fields in Trace. The work happens quickly and seamlessly behind the scenes, giving staff time to work ahead and accomplish more.

What are the benefits of Auto-indexing?

Leveraging automated data capture and indexing helps improve data integrity, enhance productivity and reduce cost. Automatically indexing data to the patient record reduces the burden of manual data entry and creates a significant opportunity to gain workflow efficiency while reducing the incidence of human error. These benefits can help elevate service levels, reduce overtime expenses, improve patient throughput, and enhance financial outcomes.

What are some of the findings from Auto-indexing clients?

Hospital clients using Auto-indexing functionality have experienced time savings, productivity increases and cost reductions. One client reported a 50-percent time savings in order reconciliation and a 3-week reduction in the hospital’s order backlog. Overall, the result has enabled customers to anticipate workload more accurately, reduce the need for paid overtime and increase patient outreach for procedure scheduling. Another client experienced record lows in abandoned call percentage and hold times as a result of Auto-indexing. Schedulers are able to work orders immediately, improving processing time by 40 percent and eliminating the order backlog. Perhaps most striking was the finding that Auto-indexing improved job satisfaction among staff by allowing them to reduce manual tasks and redirect efforts to other activities.

How do I get started with Auto-Indexing?

We are confident that we can help you reduce costs, drive workflow efficiency and maximize profitability with the Auto-Indexing functionality in Trace targeted at high-volume, text-based forms. To get started, reach out to a sales or support representative and schedule a demonstration. To ensure that we align to your goals and processes, we will conduct a brief workflow assessment and technical review and then you’ll be on your way with Auto-indexing. Contact us to learn more.



Any case studies, testimonials, examples, and illustrations included originate from customer statements as general experiences, which are intended for informational purposes with no guarantee of users achieving similar results.