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Creating a Clearer Picture of Patient Flow

April 5, 2013
by Rajiv Leventhal
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In just a short amount of time, a web-based system with real-time data already has heads turning at Hugh Chatham Memorial
MEDHOST's PatientFlow HD

Figuring out how to prevent issues from becoming problems can be challenging, especially in a complex industry such as healthcare. But if done properly, invaluable time and money can be saved.

When it comes to finding a solution to help generate meaningful business, financial, patient care and workflow improvements, many hospital organizations are in the same uncertain position as the 81-bed Elkin, N.C.-based Hugh Chatham Memorial  Hospital was in.

But a little less than a year ago, Hugh Chatham turned to MEDHOST, a Plano, Tx.-based healthcare IT vendor, which has recently announced general availability of PatientFlow HD, a web-based system which provides hospital executives with real-time, mission-critical facility, clinical and patient-centric data so they can proactively identify and manage process management and patient-flow issues before they become problems and erode hospitals’ bottom lines. 

PatientFlow HD’s graphically-driven and highly intuitive user interface makes current information, such as 30-day readmissions, patients exceeding their reimbursed length of stay, observation status patients, and patients occupying higher acuity beds than necessary, available to hospital leaders at all times, so they aren’t making decisions with old data.  The system also offers visibility at the unit and bedside levels, and with onscreen and push notifications, everyone involved in patient care stays informed, which creates a culture of accountability and helps improve patient care and safety.

HCI Assistant Editor Rajiv Leventhal recently got a chance to speak with two of Hugh Chatham’s senior level executives, CFO Don Trippel and CIO Lee Powe. Below are excerpts from that interview.

Can you talk about how your hospital has used Patient Flow HD and how it is more effective than your previous system?

Lee Powe: When we first started off with it, we found out that after the second day of implementation, we were able to improve the time of getting the patient into the bed by 25 minutes. That was a shock right off the bat. It was one simple step of being able to make everything transparent within the system. With our previous method, the nurse manager who manages the beds would be running around with papers and phones and it would be completely hectic. Before HD, I would get a report once a month, and now I can see everything that is happening in real time. The difference is amazing.  After that, it took some time to populate the data into the system, but the benefits of HD became evident very quickly.  It created transparency at our hospital never before thought possible, and we’re now able to easily manage day-to-day operations and the wide assortment of factors and influences that affect patient flow and the hospital’s bottom line.

Lee Powe

We also have been able to set milestones and goals we want to achieve from the time a person gets inside to the time the doctor sees them, as well as from the time they get to the bed to the time they are discharged. These goals are in our face so we know how we are doing in real time. It helps because you know where you are and how you measure up. Now, 40 percent of our patients are being seen by doctors within 30 minutes of when they get in the door.

In what other areas have the system’s real-time notifications benefitted the hospital?

Don Trippel: A big part of this process is the case managers, and the information that they have access to now compared with what they used to have. A key area we’re concerned with is how long observation status patients stay at the hospital. We want to obviously try to get them out in 24 hours, but sometimes that is easier said than done because case managers might change on a weekend, and the new one might not be aware of how long that patient had been there.

Don Trippel

But HD has reduced their lengths of stay. We were at [an average of] 1.75 days before HD, and now it’s down to 1.5 days. We’re still looking to reduce that number even more. The other measure out there is the geometric mean length of stay. How long has the patient been there and how long are they expected to be there? Our length of stay was always fairly short—it was at 3.2 days, but since implementing HD, it’s dropped to 3.0. When we start getting to that point, we start thinking about discharging the patient. Now I’m not saying this is all because of HD, but it is definitely part of it. Having that information available to us is crucial.

Our environmental services department took on HD as a challenge to get better as well, since there are timers placed on just about everything in the system. There used to be confusion about when beds would get cleaned and if they were spending time doubling up each other’s work. But now that all of the information is right in front of us, so that has been cleaned up and there is better turnaround time.

What were some challenges you faced when first implementing the patient flow solution?