Case finding is a never-ending cycle of review and follow up. It’s an enormous manual effort to abstract data from patient files to populate hospital, central, state or the National cancer database to complete the case entry; as well as checking on the status of cases in suspense and quality control that binds it all together. Though I’m not a certified registrar myself, I definitely get the impression from those that I have spoken with that they continue to be fiercely devoted to the important work they do; and are steadfast in getting it right.
As I’ve discussed in the past, tools are available to improve efficiencies whether the records are held 
electronically in an EHR, or printed to paper from performing labs, Pathology or HIM. I’m not talking about taking the place of CTR’s here – I’m only making a point there are tools to help CTR’s make discrete data available for abstraction in reportable cases.
After a well-attended webinar Extract Systems held recently, there were a number of comments about the case finding aspects of a CTR’s job that we hadn’t specifically addressed, but perhaps should have. There are some great tools on the market which perform this function. We recognize that it’s not a great idea to reinvent the wheel but in general, most of these applications are limited to evaluating electronic documents. For a hospital that’s already achieved HIMSS Stage 7, where little to no paper is left in the day to day workflow for medical records, this is a happy place. Unfortunately, that status has only been bestowed upon 202 out of 6,356 hospitals in the U.S. (AHA’s March, 2015 Hospital Update). And no doubt that even they have to be able to perform more efficient abstraction with the resources available.
So, there’s still a lot of manual reading going on out there to find what CTR’s need.
Wouldn’t it be helpful if reportable diagnostic terms like “linitis plastica” could be searched for automatically from scanned pathology and cytology reports or medical oncology logs? Better still, what if those terms were highlighted in yellow for quick and easy identification? Wouldn’t it be fantastic if principal and secondary diagnosis codes from last month’s disease index were automatically identified clearly on the PDF file you were reviewing on your computer? Even better, what if terms like these could read from either paper or electronic? Think about the possibilities!
