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Yale-New Haven Health System’s Bold Plunge Into Analytics-Driven Performance Improvement

January 7, 2015
by Mark Hagland
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Thomas Balcezak, M.D. and Stephen Allegretto are leading a pioneering performance improvement initiative

At a time when virtually all patient care organizations in the United States are under pressure to simultaneously improve clinical outcomes and reduce patient care costs, figuring out successful strategies and pursuing practical tactics remain major challenges for most. At the Yale-New Haven Health System in Connecticut, finance and medical leaders are pursuing a promising strategy that is profoundly data-driven.

There, Thomas Balcezak, M.D., senior vice president and chief medical officer, and Stephen Allegretto, vice president of strategic analytics and financial planning, are helping to lead an exciting initiative that is beginning to bear fruit, at the health system, which encompasses three hospitals (the 1,500-bed Yale-New Haven Hospital in New Haven; the 350-bed Bridgeport Hospital in Bridgeport; and the 100-bed Greenwich Hospital, in Greenwich). Yale-New Haven Health System is a $3.3 billion health system in annual revenues ($2.4 billion of which are derived from flagship Yale-New Haven Hospital), with a medical staff of 4,000 physicians and 12,000 employees.

Dr. Balcezak and Allegretto are spearheading an initiative in which they’ve created an ongoing analytics process focused on what they’re calling quality variation indicators (QVIs), measures that are helping YNHHS leaders link clinical, financial, and operational factors together to determine where process improvements can be made. On Oct. 21, 2014, the two executives presented on the topic “Engaging Physicians to Drive Financial Performance,” at the Strata Decision Executive Leadership Symposium, held at the Swissotel in downtown Chicago and sponsored by the Chicago-based Strata Decision Technology, which is a vendor partner in the ongoing Yale-New Haven Health Care initiative. Dr. Balcezak and Allegretto spoke recently with HCI Editor-in-Chief Mark Hagland regarding their ongoing work in this important area. Below are excerpts from that interview.

You and your colleagues are using the phrase “cost of quality” to describe some of what you’ve been working to analyze.

Stephen Allegretto: Yes, one of the tenets we’ve been working with is identifying quality variation in a manner that both physicians and nurses could identify with. So we came up with the concept of “quality variation indicators,” or QVIs, phenomena we’ve identified that happen to patients in the hospital that we don’t want to have happen to patients in the hospital. About seven percent of our patients, out of 80,000 discharges, experience these QVIs. A QVI s a comprehensive definition of quality and safety; these patients stay on average about three times longer and cost about four times as much. So by looking at our patients through that lens, our clinical folks have identified that yes, these are the patients we care for, as they’re the same patients they’re evaluating for morbidity and mortality, or as we evaluate our healthcare-acquired conditions data…

What are some of the key indicators you’re looking at?

Thomas Balcezak, M.D.: Our QVI work really is a summarization of a lot of the stuff that’s been in the medical literature for years. There are estimates about what a hospital-acquired bloodstream infection costs, for example, anywhere between $20,000 and $60,000. So there are a number of different characterizations of these types of events. Patient safety indicators, PSIs [patient safety indicators], HAIs [hospital-acquired infections], and others, these types of measures are all on DRG- and ICD-9-driven lists. And Steve and I and our colleagues looked at a relevant list of PSIs and other commonly coded conditions and worked through what was thought to be possibly preventable and what was thought to e clinically relevant, and created the QVI list. It’s an amalgamation, with some clinical expertise overlay.

And it’s resonated with us because it’s been driven by clinical expertise on what’s possibly preventable and clinically relevant; and second, when we did tests about whether these QVIs made sense, we looked at two sets of data. One was financial data. One factor was that only 7 percent of our discharges accounted for 28 percent of our costs, where month over month and year over year, the amount and proportion of those patients really held steady over time. And that became even more interesting when we looked at some of our clinical data bases and registries. The clinicians really resonate with the registries, because they come out of specialty and subspecialty societies. And when Steve’s team lined up the registry work with the coded medical work and QVI work, we were able to obtain the Rosetta Stone of medical language, because it brought together the financial and clinical data.

What are a few examples of the most typical QVIs?

Three of the key ones we’ve run data on and analyzed so far have been accidental puncture or laceration during a procedure; postoperative deep venous thrombus and pulmonary embolism, or blood clot; and post-procedural pneumothorax, or punctured lung. They’re not talked about as much as catheter-associated bloodstream infection, which is on the list, too. Interestingly, in every instance with those three QVIs, we found that our medical record coded data and registry data were concordant; what’s more, in two of the three, there was a clinical practice issue that we needed to address, and in one of the three, a coding issue. Example, let’s talk about DVT [deep venous thrombosis] prophylaxis. There’s a wide disagreement in the literature about what is needed after a hip or knee replacement to prevent DVT. But here’s the issue from my perspective as a clinician: standardization in and of itself, is still worthwhile.

Why is it worthwhile with regard to the treatment of DVT prophylaxis, for example?


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