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All-You-Can-Eat Health Data

Posted on December 20, 2011 I Written By

Priya Ramachandran is a Maryland based freelance writer. In a former life, she wrote software code and managed Sarbanes Oxley related audits for IT departments. She now enjoys writing about healthcare, science and technology.

Casinos can teach the healthcare industry a thing or two about influencing customer behavior. So says this interesting feature in California Healthline this week.

Think about it – if it’s your first time, and you lose 500$ straight off the bat, you’re not likely to head to the nearest ATM to withdraw more cash. The people who run casinos understand this, the article quote California Healthcare Foundation CEO Mark Smith as saying. That’s why casinos have loyalty card systems in place – so they can not only know what you’re doing, and to influence your behavior in a way that benefits the casino.

A casino doesn’t necessarily want a first-time customer to lose money right away, he said, because that customer becomes unhappy and won’t come back. “So if you’re a first-time customer and you’re down 150 bucks, someone in the casino will slide up to you and ask you how you’re doing,” Smith said. “And maybe get you a comp meal or a drink.” The casino intervenes before customers reach the decision point to leave.

For the healthcare industry, the holy grail is patient data. If there is enough patient data, the innovators can come along, interpret it, and hopefully healthcare providers can nudge patient behavior enough to make a change in overall health.

The most interesting thing about the article, to me personally, was reading about how data that has been made publicly available can be used for interesting uses. The article talks how data made public by the National Oceanic and Atmospheric Administration fuels such varied things as the Weather Channel, mobile weather apps and so on.

And guess what? All that can happen to healthcare as well. Much public health information is available for access by the general public, and part of the job of HHS has been to make innovators aware that public health data is now available. The article talked about Bing using Hospital Compare data to provide users with hospital comarison statistics.

I followed some of the links on the article and finally ended up at the site, where as promised, a treasure trove of data is publicly available – just waiting for the right technogeek to come along and do something cool with it. Could that innovator be you? Go check it out!

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?