Let us know if any of this sounds familiar…
- Your paper medical record volume has decreased
- You contract with a courier to pick up medical records at remote locations and physician offices
- You still have multiple FTE’s dedicated to documenting imaging and processing
- Your hospital is looking for ways to cut costs
If you ticked off any of these boxes you’re probably asking yourself, “is there a more efficient, secure and reliable way to handle paper medical records and reduce cost at the same time?”.
Might we suggest a distributed capture (A.K.A. remote) scanning model? By outsourcing the scanning and data capture, you can easily handle fluctuating volumes, reduce FTE, eliminate courier
costs and improve access to paper medical records.
Sounds great, right?
To help get you started, we thought we’d compile the most asked questions we get about our distributed capture model and answer them for you.
1. What is Distributed Capture?
Utilizing small desktop scanners or MFD (multi-function devices), documents are scanned at the remote locations by the hospital or the physician office staff and then securely uploaded for automated indexing and quality review.
2. How can Distributed Capture improve turnaround times?
An agreed-upon turnaround time should be negotiated with the vendor. This is probably one of the driving forces in your move to distributed capture so being reasonable but also holding your ground on the turnaround time you need is essential.
To give you a starting point, here’s how we break it down. On average, the time it takes from the moment it’s scanned to when it’s viewable in the EMR is 10-12 hours. Reaching this turnaround time is possible with a combination of industry experts and proprietary technologies to ensure that sensitive information is efficiently captured, accurately classified and loaded back into the EMR/EHR accessible system within a guaranteed SLA.
3. How will Distributed Capture improve index classification?
Once the documents are scanned, they go through secure automated indexing technology that assigns specific indexes, such as encounter number and document type to the image. For images that can’t be recognized by technology, make sure to ask about any manual review options they have available.
You should also ask about the vendors quality control process. For example, after the image is indexed, they pass through our quality control process to ensure the image was classified accurately and we adhered to the specified assembly rules from the hospital.
4. What is the process for handling errors in a Distributed Capture model?
The process of managing images with identified error issues/exceptions are built in tandem with the customer. The goal of an error handling process is to ensure visibility into any images with the identified issue and guarantee that a customer can rectify it as quickly as possible.
5. With the process of electronically transporting images, how will images be secured?
This is potentially one of the most important questions to ask any vendor. For us, we employ state of the art technology to efficiently and securely capture, transfer and process healthcare information. It’s important to us that we build out a proprietary internal workflow system, with forms recognition and OCR capabilities, streamlined data entry systems, and the ability to securely extend our internal technology through the use of secure thin client technology.
Other things to look for when asking about the security of your images in a capture process are certifications such as ISO 27001, Soc II Type 2, and while it may seem obvious, HIPPA and HITECH compliance capabilities.
6. How will Distributed Capture help with the fluctuation in paper document volumes?
As the volume of paper documents increases or decreases, a distributed capture model lends itself to be very beneficial. You can utilize your staff for scanning while leaving the burden of indexing and quality review to DataBank. That way, with the bulk of the process in someone else’s hands, you can easily move through the ebbs and flows of document volume.
