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Yale New Haven Hospital Partners With Epic On Centralized Operations Center

Posted on February 5, 2018 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

Info, info, all around, and not a place to manage it all. That’s the dilemma faced by most hospitals as they work to leverage the massive data stores they’re accumulating in their health IT systems.

Yale New Haven Hospital’s solution to the problem is to create a centralized operations center which connects the right people to real-time data analytics. Its Capacity Command Center (nifty alliteration, folks!) was created by YNHH, Epic and the YNHH Clinical Redesign Initiative.

The Command Center project comes five years into YNHH’s long-term High Reliability project, which is designed to prepare the institution for future challenges. These efforts are focused not only on care quality and patient safety but also managing what YNHH says are the highest patient volumes in Connecticut. Its statement also notes that with transfers from other hospitals increasing, the hospital is seeing a growth in patient acuity, which is obviously another challenge it must address.

The Capacity Command Center’s functions are fairly straightforward, though they have to have been a beast to develop.

On the one hand, the Center offers technology which sorts through the flood of operational data generated by and stored in its Epic system, generating dashboards which change in real time and drive process changes. These dashboards present real-time metrics such as bed capacity, delays for procedures and tests and ambulatory utilization, which are made available on Center screens as well as within Epic.

In addition, YNHH has brought representatives from all of the relevant operational areas into a single physical location, including bed management, the Emergency Department, nursing staffing, environmental services and patient transport. Not only is this a good approach overall, it’s particularly helpful when patient admissions levels climb precipitously, the hospital notes.

This model is already having a positive impact on the care process, according to YNHH’s statement. For example, it notes, infection prevention staffers can now identify all patients with Foley catheters and review their charts. With this knowledge in hand, these staffers can discuss whether the patient is ready to have the catheter removed and avoid related urinary tract infections associated with prolonged use.

I don’t know about you, but I was excited to read about this initiative. It sounds like YNHH is doing exactly what it should do to get more out of patient data. For example, I was glad to read that the dashboard offered real-time analytics options rather than one-off projections from old data. Bringing key operational players together in one place makes great sense as well.

Of course, not all hospitals will have the resources to pull something off something like this. YNHH is a 1,541-bed giant which had the cash to take on a command center project. Few community hospitals would have the staff or money to make such a thing happen. Still, it’s good to see somebody at the cutting edge.

A Look At Geisinger’s Big Data Efforts

Posted on December 28, 2016 I Written By

Anne Zieger is veteran healthcare branding and communications expert with more than 25 years of industry experience. and her commentaries have appeared in dozens of international business publications, including Forbes, Business Week and Information Week. She has also worked extensively healthcare and health IT organizations, including several Fortune 500 companies. She can be reached at @ziegerhealth or www.ziegerhealthcare.com.

This week I got a look at a story appearing in a recent issue of Harvard Business Review which offers a description of Geisinger Health System’s recent big data initiatives. The ambitious project is designed not only to track and analyze patient outcomes, but also to visualize healthcare data across cohorts of patients and networks of providers and even correlate genomic sequences with clinical care. Particularly given that Geisinger has stayed on the cutting edge of HIT for many years, I think it’s worth a look.

As the article’s authors note, Geisinger rolled out a full-featured EMR in 1996, well ahead of most of its peers. Like many other health systems, Geisinger has struggled to aggregate and make use of data. That’s particularly the case because as with other systems, Geisinger’s legacy analytics systems still in place can’t accommodate the growing flood of new data types emerging today.

Last year, Geisinger decided to create a new infrastructure which could bring this data together. It implemented Unified Data Architecture allowing it to integrate big data into its existing data analytics and management.  According to the article, Geisinger’s UDA rollout is the largest practical application of point-of-care big data in the industry. Of particular note, Geisinger is crunching not only enterprise healthcare data (including HIE inputs, clinical departmental systems and patient satisfaction surveys) and consumer health tools (like smartphone apps) but even grocery store and loyalty program info.

Though all of its data hasn’t yet been moved to the UDA, Geisinger has already seen some big data successes, including:

* “Close the Loop” program:  Using natural language processing, the UDA analyzes clinical and diagnostic imaging reports, including free text. Sometimes it detects problems that may not be relevant to the initial issue (such as injuries from a car crash) which can themselves cause serious harm. The program has already saved patient lives.

* Early sepsis detection/treatment: Geisinger uses the UDA to bring all sepsis-patient information in one place as they travel through the hospital. The system alerts providers to real-time physiologic data in patients with life-threatening septic shock, as well as tracking when antibiotics are prescribed and administered. Ninety percent of providers who use this tool consistently adhere to sepsis treatment protocols, as opposed to 40% of those who don’t.

* Surgery costs/outcomes: The Geisinger UDA tracks and integrates surgical supply-chain data, plus clinical data by surgery type and provider, which offers a comprehensive view of performance by provider and surgery type.  In addition to offering performance insight, this approach has also helped generate insights about supply use patterns which allow the health system to negotiate better vendor deals.

To me, one of the most interesting things about this story is that while Geisinger is at a relatively early stage of its big data efforts, it has already managed to generate meaningful benefits from its efforts. My guess is that its early successes are more due to smart planning – which includes worthwhile goals from day one of the rollout — than the technology per se. Regardless, let’s hope other hospital big data projects fare so well. (Meanwhile, for a look at another interesting hospital big data project, check out this story.)