How Smart Chart Abstraction Can Speed EHR Deployment

Posted on January 26, 2011 I Written By

Anne Zieger is veteran healthcare consultant and analyst with 20 years of industry experience. Zieger formerly served as editor-in-chief of and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also contributed content to hundreds of healthcare and health IT organizations, including several Fortune 500 companies. Contact her at @ziegerhealth on Twitter or visit her site at Zieger Healthcare.

Caught an interesting analysis this week from the California HealthCare Foundation, which has been studying EHR deployment within community clinics and health centers since 2006.

In most cases, chart abstraction creates a major bottleneck which can slow the transition to EHR use to a crawl, while cratering caregiver productivity in the process.  But if it’s done thoughtfully, you can avoid some of the chaos, the study suggests.

In its new paper, the foundation shares chart abstraction techiques that used by members of its California Networks for EHR Adoption initiative.

Here’s some strategies CHCF has identified which seem to speed  up the process — and in turn, streamline EHR deployment. (This is just a small sample; I highly recommend you check out the paper itself for detailed case studies and advice.)

Some of the research group’s suggestions:

* Start with a strategy: Decide in advance what information will be entered, when, and by whom — and decide how closely the EHR data should resemble the paper version.  Just as importantly, decide whether any given piece of data is really worth entering at all.

Don’t abandon paper too quickly: How do you abstract paper chart data?  Usually, you consider scanning charts, migrating data from legacy systems, entering data manually or going for a mix of all of the above.  While each can work, the key is not to drop paper charts too quickly.  To reassure staff, the clinics in CHCF’s initiative typically kept paper on hand all the way through the EHR go-live period — and sometimes for a while afterwards.

Fine-tune your abstraction approach: Clinics that did well with the abstraction process had make near-constant adjustments to their process.  For example, one clinic had to move quickly from traditional scanning to a software solution which gave the docs smart headers, after staff wasted countless hours poring over cryptically-named scans. Then, when that wasn’t enough, it had to develop a hierarchical naming system for scans not long after.

Readers, are you struggling with chart abstraction process as you prepare for EHR deployment?  Has staff productivity taken a big  hit?  Perhaps most importantly, how long do you think it will be before the paper-to-electronic- data process stops being an issue?