Critical Care Plus: New Methodology Promises to Help ICUs
June 1, 2001 6 minutes read
Critical Care Plus
New Methodology Promises to Help ICUs
Smoothing’ Elective Admissions Seen as Key
By Julie Crawshaw
Hospitals can provide a major boost to their intensive care units by applying variability methodology to elective admissions, says Eugene Litvak, PhD.1
Litvak, a professor of health care and operations management at Boston University School of Management, says there are four types of variabilities in health care delivery today. The first three—clinical, flow, and professional—are intrinsic. Patients have different diseases, thus creating clinical variability. Some hospital patients are scheduled while others arrive unpredictably through the emergency room, causing flow variability. And since all providers cannot provide the same quality of care, there is professional variability.
There’s a fourth type of variability that Litvak says hospitals can control. He describes this type of variability as artificial. To illustrate, he points out that though 50% of surgical patients at most hospitals arrive through the emergency room, research data show that the 30-35% of patients who come for elective surgery exert greater influence on patient census variability and thus influence the number of beds available for ICU patients.
"This is a perfect example of artificial variability," Litvak says. "ICU diversion has not received as much media coverage as emergency room diversion but is just as much a problem."
Variability affects staffing as well as diversions. Last year, the Institute of Medicine in Washington, DC, released a report showing that up to 98,000 patients die in hospitals every year due to medical errors. The Massachusetts Nurses Association says that medical/surgical nurses at the state’s hospitals are often responsible for from nine to12 patients on a shift. Nurses working in long-term care often have 30-40 patients.
Partners, the largest single health care delivery network in Boston, had been researching a network-wide operations cost-reduction effort for about a year when Michael E. Long, MD, met Litvak in 1995. Long is an adjunct associate professor of health care and operations management, assistant professor of anesthesia at Harvard Medical School, and deputy director of operating services at Massachusetts General Hospital. He then was also co-chairing a group seeking ways to increase operating room efficiency. He and Litvak developed their variability methodology in the process of collaborating on operating room design.
"Our research showed that variability of demand greatly impacts ICUs," Long says. "ICU beds are so scarce in Boston now that we’re having to transfer patients from one hospital to another. In rare instances, patients have even been sent out of state. Controlling variability in elective surgery schedules can have a great positive effect."
The level of elective patient census appears at first to be a factor over which hospitals have no control, but Litvak and Long say a closer look reveals otherwise. They observe that surgeons are usually given block time access to operating facilities. If they don’t use the time, the assigned rooms remain empty and the facility absorbs the cost of staffing for the unoccupied beds. Many surgeons decide to operate on Friday or Monday to free up other days, thus creating a peak in the hospital census.
When simultaneous peaks occur in the emergency room and the elective rooms, the outgoing flow from the emergency room is obstructed. "If you ask any emergency room director to name a single reason why the ICU and emergency room patients are being diverted, you’ll hear the reason is a lack of beds," Litvak says. "We have to smooth all elective admissions and discharges, which means the primary criterion is the hospital’s effectiveness, not the interest of the individual physician." Long and Litvak found a tremendous effect on hospital census from elective medical admissions as well.
Staffing Below the Peak is Asking for Trouble
In a typical hospital, the number of occupied beds varies dramatically from day to day, at an average of about 15%. "This means that the difference in the number of occupied beds could be as high as 30%, creating a major staffing problem," Litvak says. "Hospitals today cannot afford to staff to the peak demand."
A recent federal Department of Health and Human Services study pointed out that staffing below the level needed for peak usage causes a huge rise in medical errors. "When there’s a valley in the census, we waste our resources. When we have peaks, our resources are inadequate to meet the need," Litvak says. "Then quality of care declines and medical errors go up."
Litvak is quick to point out that scheduled medical admissions are variable as well. But he says that solving the variability problem—and thus reducing costs and medical errors—means surgeons must reconcile their schedules with their block time. "The problems of ICU and emergency room diversions, medical errors, and staffing issues cannot be resolved until we have smoothed elective admissions," he says. "When those are smoothed, half of the peak census, in terms of frequency and magnitude, will disappear."
Staffing to Valid Peaks May Fit the Current Budget
Once the artificial peaks are eliminated, the remaining peaks and variability are clinically driven. "We cannot do anything about that except incorporate this variability into our funding," Litvak says. "The only alternative is to staff to all the peaks, and no one can afford to do that today. If we could staff to all the peaks, we wouldn’t need managed care."
Litvak says that attempting to control hospital costs overall diminishes quality of care. "Let’s say you are running a pizza shop," he says. "It costs you $3 to produce the pizza and $7 to deliver it. You know the delivery cost is inflated because your drivers don’t know the proper routes and neither do you. Then your competitors lower the cost of their pizzas, creating financial pressure for you. So you respond by making cheaper pizzas with fewer toppings, thus offering diminished quality. This is exactly what we are doing in health care. We still have waste at the same time our quality is diminishing because we cannot separate artificial variabilities from clinically driven ones."
Litvak freely acknowledges that eliminating artificial variability will not solve all the problems hospitals face today. "What it will do is let us know exactly how many beds we need," he says. He points out that though many hospital administrators think they have already eliminated all the fat, they lack the quantitative proof that would provide a perfect shield for negotiations with HMOs.
"As it is now, neither side has any idea how much running a hospital really costs," Litvak says. "Can you imagine the owner of a pizzeria not knowing what the pizza production cost is? Until you can ascertain what you really need, you’ll be constantly engaged in funding battles."
Variability methodology already has some impressive accomplishments to its credit, including an algorithm for controlling overbooking in high-cost testing labs, methodology-supporting software, identifying a threshold for cost-reduction, and developing a reservation system for an acute hospital/rehabilitation that requires hospitals to pay for their performance failures.
BU to Offer Variability Methodology Training
To help physicians and administrators learn and apply the Litvak/Long methodology, Boston University will offer a Program for the Management of Variability in Health Care Delivery beginning in September. University officials say the program will develop, test, and evaluate methods for reducing variability in health care delivery processes. It also will disseminate findings regarding best practices for reducing costs and improving quality of care using written case studies, publications in peer-reviewed journals, workshops and seminars, and continuing education programs. Computer software has been developed to support the Litvak/Long variability methodology.
The program aims to:
• Determine the effect artificial variability has on medical errors and quality of care, and develop feasible strategies for eliminating artificial variability;
• Develop strategies to optimally manage "natural" variability" in order to reduce its negative effect on quality of care;
• Undertake systems analyses of patient flow and matching of resources, demand, and delivery of health care across office, institutional, and network environments;
• Develop simulation models that allow exploration of the effect of alternative designs for improving operations;
• Develop education programs to teach the principles of variability reduction and operations research/operations management to health care administrators and providers.
Reference
1. Litvak E, Long MC. Am J Manag Care. 2000;6:305-312.
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