Free EMR Newsletter Want to receive the latest news on EMR, Meaningful Use, ARRA and Healthcare IT sent straight to your email? Join thousands of healthcare pros who subscribe to EMR and EHR for FREE!

A Model For Fostering Health Data Sharing

Posted on August 8, 2017 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.

Sometimes, I’m amazed by what Facebook’s advertising algorithm can do. While most folks get pitches for hot consumer devices, shoes or casual wear, I get pitched on some cool geek stuff.

Most recently, I got an interesting pitch from, a social networking site that helps members share and discover open datasets. The site is free to join, and if there’s a paid “premium” setting I haven’t found it. From what I’ve seen, this is a pretty nifty model which could easily be adapted for use by health IT organizations.

The site, which looks and feels something like Facebook, features data from a wide range of industries, tilted heavily toward government databases. For example, when I checked in, a front-page column listing the most commonly used tags includes “GIS,” “Homeland Security,” “police,” “SBA” and “DC” (which lead the pack with 688 mentions).

And there’s plenty of healthcare industry data to grab if you’d like. If you search for the term “healthcare” some useful datasets pop up, including a list of last year’s hospital HCAHPS ratings, California-specific data from 2005 to 2014 on the number and rates of preventable hospitalizations for selected medical conditions and New York state data on payments it made under its Medicaid Electronic Health Record Incentive Program. (You’ll have to become a site member to access these records.)

What makes the site truly interesting is the data sharing mechanism it offers. As a member, you have a chance to both upload open datasets, download datasets, post a project or join someone else’s project already in progress. Want help crunching the data on preventable hospitalizations in California? Let other site members know. There’s at least a chance you’ll find great project partners.

Of course, I’m not here to shill for this particular venture. My point in writing about its features is to draw your attention to what it does.

I think it’s more than time for healthcare organizations to collaborate on shared data projects together, and this is perhaps one mechanism for doing so. True, most of the data health systems work with is proprietary, but perhaps it’s possible to work past this issue.

Some healthcare organizations have already decided that sharing otherwise proprietary data is worth the risk. For example, late last year I wrote about a project undertaken by Sioux Falls, SD-based Sanford Health, in which the health system shared clinical data with a handful of academic researchers.  Benson Hsu, MD, vice president of enterprise data and analytics for the system, told Healthcare IT News this “crowdsourced” approached helped Sanford predict risk more effectively and improved its chronic disease management efforts.

Admittedly, Sanford’s approach won’t work for everyone. Today, healthcare organizations aren’t in the habit of cooperating on clinical data analytics projects, and anyone who suggests the idea is likely to get some serious pushback. Yes, in theory we all want interoperability, but this is different. Sharing entire clinical data repositories is a big deal. Still, how are we going to tackle big problems like population health management if we aren’t open to data analytics collaboration?

Sometimes new initiatives happen because people learn to understand each other’s needs, and decide that the prospect of mutual gain is worth the risk. I think a community devoted to data analytics could do much to foster such relationships.

Patient Wait Time Tracking – Can We Learn Something from Fast Food?

Posted on February 19, 2015 I Written By

John Lynn is the Founder of the blog network which currently consists of 10 blogs containing over 8000 articles with John having written over 4000 of the articles himself. These EMR and Healthcare IT related articles have been viewed over 16 million times. John also manages Healthcare IT Central and Healthcare IT Today, the leading career Health IT job board and blog. John is co-founder of and John is highly involved in social media, and in addition to his blogs can also be found on Twitter: @techguy and @ehrandhit and LinkedIn.

I was recently asked by @HIMTrainer (Jennifer Della’Zanna if you prefer) if I knew where my article was that I wrote about having a “patient wait” timer in an office. I vaguely remember talking about the idea, but couldn’t find and don’t remember specifically posting about the topic. However, the idea of a timer that tracks a patient’s wait time was interesting.

I’m sure that most of you are familiar with these timers at fast food restaurants. They track how long you’re waiting for your food and they often have some promise of free food if it takes over a certain amount of time. I’ve always found these timers interesting. In fact, I can’t remember a time when I’ve been to a restaurant with one of these timers that I ever had to wait very long for my food. Is that because of the timer or is that the nature of the restaurant and this was just a marketing mechanism? The answer is that it’s likely both.

The timer is a visual display of how long you’re really waiting. Time is a funny thing. A wait time that is relatively short can feel really long. We often lie to ourselves about how long something is, but that’s our perception. A timer helps to readjust that perception to the proper perspective. Of course, on a bad day it can also illustrate how much the restaurant needs to improve.

The other value of the timer is that it encourages the staff to work faster. At first this probably means the staff will feel some anxiety over the timer. However, over time it will just be a visual indication of how quickly or slowly their working and will help to ensure a consistent speed of service from most employees.

Now I’m sure that many of you are thinking that Fast Food is an awful comparison to healthcare. Fast Food is a pretty consistent product with a consistent request. Healthcare is a pretty inconsistent product with a wild variety of requests (almost limitless). Plus, I’m sure that many people’s gut reaction will be that this is an awful idea and corrupts the practice of medicine. I can already hear the cries for “Where’s the humanity in medicine?”

Certainly an organization could take this too far. However, maybe there’s something we can learn from the wait time clock that could help healthcare improve. Plus, when people cry fowl over something, that really makes me want to dig into that idea and see how it can help.

What’s Realistic in Healthcare?
There’s no way you’re going to see an actual clock at the check in or check out window in healthcare. I can’t even imagine how that workflow and tracking would work. So, it won’t be the same as fast food, but there are certainly a number of options available to track how long a patient is waiting. In fact, in many cases you can get quite granular.

Built in EHR Status Tracking
10 years ago when I first implemented an EMR system (yes, it was EMR, not EHR at the time), we could track the patient wait times in our EMR system. It wasn’t a perfect process, but you could get a good idea of how long a patient was in the office, how long they waited to be put in a room, how long they waited from the nurse to the doctor, and then when they checked out. Of course, you can add it all together and get an idea of how long the patient was in the office.

We simply used the statuses in the EHR to track this time data. It worked out pretty well with a few exceptions. If we didn’t have something that was specifically queued off of that status, then the data would be incorrect. For example, the nurses knew to bring a patient into an exam room based on the front desk changing them to a checked in status. So, the front desk always did this. The doctor would know to go into the room based on the nurse changing the status of the patient, so the nursing staff always did this. The patient was marked as discharged when the patient was making their payment (or checking to see if they had payments) and so this final status change was always done. Nothing was queued off of the doctor changing the status, so this often failed and so that data wasn’t very accurate.

Running these reports was fascinating and we could slice and dice the data in a variety of different ways. We could see it by provider, by appointment type, etc. Seeing the data helped us analyze what was taking the most time and improve it. We were also able to exclude any outliers that would skew the data unfairly to a provider who had a crazy complex case or in case a status change was missed.

Proximity Tracking
While EHR status tracking is good, there’s an even more powerful and effective way to track patient wait times in an office. I saw this first hand at the Sanford Health clinic in Fargo, ND at the Intelligent Insite conference. The entire clinic was wired with proximity tracking and other wireless monitoring technology that could track everyone in the clinic. Every nurse, doctor, MA, etc all had this technology embedded in their badge. Patients were issued a tracking device when they checked in for their appointment.

With this technology in place, you can imagine how the workflow for my above tracking is totally automated. They would actually immediately room the patient upon the patient’s arrival. In this case, the room would automatically know that the patient was in the room and provide an indication to the nursing staff that the patient was ready and waiting. I can’t remember the exact times, but they worked to have a nurse go into the room with the patient almost immediately after the patient got in the room. No doubt that’s a unique setup, but with these tracking devices they could know how well they were doing with the goal.

I won’t dive into all the other details of this workflow, but you can imagine how all of these tracking devices can inform the flow of patients, nurses and doctors through your office. Plus, all of this data is now trackable and reportable. The nurse, doctor, or patient don’t have to remember to do anything. The proximity devices do all the tracking, status change, etc for you.

I asked them if many patients walk out of the office with their tracking device. They told me that they’ve never had that happen, but they have returning the device as part of their checkout procedures so that could be why.

Informing the Patient
I think we’re just getting started on all of this. The price of this technology will continue to come down and we’ll do a much better job of tracking what happens in a practice. Plus, it offers so many interesting workflow benefits. I wonder if one of the next steps is to inform the patient of their wait time.

If we’re tracking the wait time, it’s not that far of a stretch to share that wait time with the patient. Kick off a clock that starts counting once they check in for their appointment. Maybe that wait time is displayed in an app on the patient’s smartphone. Maybe the wait time could be integrated into the Epion Health tablets a practice gives the patient during their office visit. If it’s a fast visit, do you prompt them to do a review of the doctor on a social site like Yelp or HealthGrades? Would doctors be ready for a patient to see front and center how long they’ve been waiting?

Final Thoughts
I’m sure that many doctors and practices will be afraid of this type of transparency. Plus, I’ve seen some general medicine doctors in particular make some serious arguments for why they run behind. Maybe the app could take this into consideration and inform the patient accordingly. While there are many unreasonable patients that are going to be unreasonable regardless of the situation, many other patients will have a much better experience if they just know more details on what’s going on.

While the comparison to a fast food timer clock is a stretch, the concept of tracking a patient’s time in an office is a discussion that is just starting. As providers work to differentiate themselves from their competitors, I’ll be interested to see how all these new technologies combine to make the patient experience better.