The 100k Lives Campaign
150-200 words, intext citation and references
In the course text, read case 11-1, pages 338 (bottom) through 348. I have to respond to Discussion question #3
THE 100K LIVES CAMPAIGN: A VOLUNTARY CODE IN ACTION
In 2004, the Institute for Healthcare Improvement (IHI) put out a call for hospitals willing to participate in its 100,000 Lives Campaign. Its goal was to prevent 100,000 deaths in U.S. hospitals during an 18-month period (January 2005 through June 2006) by having hospitals implement some or all of six quality-improvement changes that the IHI and its campaign partners identified as evidence-based and potentially lifesaving.
The IHI developed the campaign in response to a 2001 Institute of Medicine report, Crossing the Quality Chasm: A New Health System for the 21st Century, that concluded that 44,000 to 98,000 Americans die each year because of medical errors and adverse events (injuries caused by medical management). This campaign provides an example of non-coercive alternatives to command-and-control regulation—referred to by some as “voluntary codes.” To illustrate how the campaign worked, this case discusses one of the six changes that the IHI put forward—establishing a Medical Emergency Team (MET), also referred to a Rapid Response Team—and describes one participating hospital’s efforts to implement that change.
THE 100K LIVES CAMPAIGN
The original campaign goal was to recruit 2,000 hospitals to implement at least one of the six quality-improvement changes (see Table 11-4). The final number recruited exceeded 3,000, representing about 75% of the nation’s hospital beds and 30 million discharges annually. Because most hospitals chose to implement multiple changes—many implemented all six—the campaign inspired 12,294 new quality-improvement efforts.
Each hospital had to set a target for the number of lives it would save. It had two options for how to do this. The simplest way was to set a goal based on the campaign’s target of saving 100,000 lives. To do that, participating hospitals and hospital systems would have to avoid slightly less than two deaths per thousand discharges per year. Thus, the calculation for arriving at a hospital’s target for lives that would need to be saved would be as follows (IHI, n.d.):
(Number of discharges per year) × (18 months ÷ 12 months) × (2 lives saved ÷ 1,000 discharges)
The alternative was to look at what the literature suggested was the lifesaving potential of each change and identify the population of patients whose care would be improved. From 339340that, a hospital could estimate the number of lives that would be saved if the program was fully implemented for 18 months and then adjust that downward to account for months when the program was not operational or in a “ramp up” phase.
The Institute for Healthcare Improvement and its partners identified six quality-improvement changes to promote through the 100K Lives Campaign. They were as follows:
• Prevent patients on ventilators from developing pneumonia by following four steps, including raising the head of the patient’s bed between 30 and 45 degrees (1,982 hospitals participating).
Participating hospitals had to agree to submit monthly raw mortality data for January 2005 through June 2006 and baseline data for the 18 months preceding the campaign (July 2003 through December 2004). To account for variations in 340341the acuity of the patient load, the IHI calculated the “case mix ratio” (CMR) using national acuity data. The ratio compared expected deaths per discharge for each month during the campaign period with expected deaths per discharge for the comparable month in 2004. Thus, for February 2006, the formula for calculating the case mix would be as follows:
(February 2006 CMR) = (February 2006 expected deaths per discharge) ÷ (February 2004 expected deaths per month)
The IHI then calculated the expected deaths per month if there had not been any quality improvements by multiplying the number of discharges each month by the mortality rate for the same month during 2004 and then adjusting for acuity by multiplying the anticipated number of mortalities by the CMR. It then arrived at the number of lives saved by subtracting the actual number of deaths from the expected number of deaths. The formula for calculating lives saved in February 2006, therefore, would look like this:
(February 2006 lives saved) = ([February 2006 CMR] × [February 2004 mortality rate] × [February 2006 number of discharges]) − (February 2006 number of deaths)
These calculations were made using national numbers and aggregated data from all of the reporting hospitals. Confounding factors would make it difficult for most hospitals to calculate their individual lives saved with much accuracy.
There was no immediate financial return or other significant direct benefit to participating hospitals and no monetary reward for reaching their goals, although some participants issued press releases touting their involvement and put information about the campaign on their Web sites. No law—either administrative rule or statute—was forcing them to 341342participate. Indeed, the campaign fits the model referred to as a “voluntary code.” Webb (2004, p.11) defined voluntary codes as follows:
• Commitments not required by legislation or regulations
• Agreed to by one or more individuals or organizations
• Intended to influence or control behavior
• To be applied in a consistent manner or to reach in a consistent outcome
“Unlike conventional command and control regulatory approaches,” wrote Webb, “voluntary codes harness market, peer and community energies to influence behaviour, and draw on the infrastructure of intermediaries such as industry associations, standards organizations and non-governmental organizations for rule development and implementation” (p. 11). Webb considered voluntary codes to be part of a concept called private governance, a term “intended to encompass the full range of ways that organizations not directly affiliated with the State attempt to organize their affairs” (p. 12). Other terms used to describe private governance include informal regulation, private regulation, voluntary regulation, self-regulation, co-regulation, and communitarian regulation, as well as soft law, self-management, and corporate social responsibility.
The 100,000 Lives Campaign seems to fit Webb’s definition of a voluntary code. The intermediaries in this case are the IHI and its partners, including the Joint Commission on Accreditation of Health Care Organizations (JCAHO), the American Medical Association, the American Nurses Association, the National Patient Safety Foundation, the Leapfrog Group, the U.S. Center for Disease Control and Prevention, and the U.S. Centers for Medicare & Medicaid Services.
Perhaps the best known types of voluntary codes are principles for responsible corporate behavior promoted by nongovernmental, environmental, health and welfare, and social justice organizations and adopted by corporations. There are many examples of such campaigns, one of which is the 342343“No Dirty Gold” campaign started by Earthworks, with industry leadership from Mike Kowalski, Chairman and CEO of Tiffany & Company, which encourages the gold mining industry to adopt sustainable practices and the jewelry industry to use “clean” gold.
Voluntary codes are not new, and they may or may not be in the public interest. In the Middle Ages, guilds controlled almost every aspect of commercial activities. The Better Business Bureau grew out of “vigilance committees” formed in the late 1800s, and the National Consumer’s League inspected working conditions at apparel factories as early as 1899, authorizing those that met its standard to use its white label.
Webb (2004) suggested that the current interest in voluntary codes may be due in part to the limitations of traditional government regulations:
Regulatory regimes pertaining to consumer, environmental, worker, and health and safety protection, and many other areas, have made considerable progress in improving the lives of millions. But for all their strengths, the command-and-control regulatory approach is not without its limitations, including expensive and protracted development and enforcement processes; jurisdictional constraints on subject matter, approach and scope; vulnerability to inconsistent and inadequate enforcement, due to staff resources and cutbacks, and associated downturns in government and public attention; and a tendency toward inflexibility and overformality (p. 4).
Webb and other authors, however, are quick to acknowledge the limitations of voluntary codes—for example, a “free rider” who chooses not to participate may gain a cost advantage over competitors who are “doing the right thing.” Voluntary codes and conventional government regulations are not mutually exclusive. In Canada, the use of bicycle helmets is required by law, but safety standards for their manufacture are voluntary; meanwhile, hockey helmets manufacturing standards 343344are federally mandated, but the use of helmets during hockey games is discretionary in most of the country (Morrison & Webb, 2004).
When JCAHO, an independent, nonprofit organization, sets a standard for health care organizations and then evaluates and accredits them, it is engaging in a form of private governance. State agencies that regulate hospitals may grant “deemed status” to hospitals that meet JCAHO’s standards, accepting accreditation in lieu of a visit by state inspectors or requiring less frequent state inspections.
State regulations and voluntary efforts to reduce medical errors may co-exist. As of September 2005, 23 states had passed legislation or regulations requiring adverse event reporting for hospitals (Rosenthal & Booth, 2005).
THE CASE FOR METS
Cardiac arrest teams that respond to the bedside of a patient who suddenly has no palpable pulse or detectible blood pressure, is unresponsive, or requires the initiation of life support are common features in hospitals. These teams, despite access to increasingly sophisticated technology and increasingly refined protocols, have had limited impact on survival. In the United States, the percentage of patients who suffer in-hospital cardiac arrest and survive long enough to be discharged has remained at around 15% for almost 3 decades.
The IHI has noted that there is wide variability in hospital survival rates. The IHI attribute this variability to three factors: (1) failures in planning, (2) failures in communication, and (3) failure to recognize deteriorating conditions. Cardiac arrest teams appear to illustrate the third factor. In the hours preceding arrest, patients typically show signs of distress. If those signs are recognized and appropriate steps taken, the arrest can often be prevented. One study found that 76% of patients who unexpectedly coded or had to be admitted to intensive care showed symptoms of respiratory, 344345airway, or circulatory deterioration an hour or more beforehand (Buist et al., 2002). Patients may be dying from respiratory or cardiac failure and related complications, but hospitals’ “failure to rescue” may be a contributing factor.
In February 1990, Liverpool Hospital in Sydney, Australia introduced a variation on the cardiac arrest team, something it called the MET. The difference between the cardiac arrest team and a MET was that hospital staff could summon the MET to treat anyone who was noticeably deteriorating or acutely unwell. Initial results, published in the mid 1990s, were highly favorable. In 2002, a team of Australian researchers published a study that found that establishing a MET in their hospital resulted in a 50% decrease in the incidence of unanticipated cardiac arrests, even after making adjustments for variations in case mix (the acuity of its patient population). Mortality declined from 76% to 55% (Buist et al., 2002).
Although there was broad agreement that METs made intuitive clinical sense, appeared to work, were relatively simple and inexpensive to implement, and did not seem to produce any clinical adverse outcomes, hospitals were slow to deploy them. Kerridge and Saul (2003) suggested that this “institutional inertia” might be traced to a continuing quest for data that would meet the “gold standard” of evidence-based medicine, and Buist et al., many argued, had not met that standard.
Then Bellomo et al. (2003) published more robust results. They studied a MET team established at a major Melbourne, Australia teaching hospital. The relative risk of experiencing a cardiac arrest, while a patient, declined 65% during the 4-month study period when compared with a 4-month period before the MET began operating. The relative risk of dying from an in-hospital cardiac arrest declined 56%. The number of days survivors spent in the intensive care unit declined 80%, and the total days they spent in the hospital declined 88%. Strikingly, the hospital’s overall mortality rate dropped 25%. The IHI cited this experience as evidence 345346when it put Rapid Response Teams on its menu of qualityimprovement changes. To meet its goal of 100,000 lives saved, the campaign estimated that it would need to prevent about two deaths per 1,000 discharges. The data out of Australia suggested that METs alone could prevent three deaths per 1,000 discharges.
VIRGINIA MASON’S EXPERIENCE
Virginia Mason Medical Center, a 100,000 Lives Campaign participant situated in Seattle, launched its MET in July 2005 (Virginia Mason Medical Center, 2006). The goal was to prevent avoidable codes by intervening before patients developed cardiopulmonary arrest or other adverse events. Each specially trained team included a critical care charge registered nurse, a respiratory therapist, and a hospitalist. To manage the program, Virginia Mason established a team made up of a project manager, the medical director for the critical care unit and respiratory therapy, the hospitalist service director, a respiratory therapy manager, a preceptor coordinator, the chief of nursing services for the intensive care unit, an administrative director, and a communications consultant.
The hospital nursing staff was instructed to call immediately both the MET (by dialing a special phone number) and the managing physician whenever any of the following occurred:
For outcome measurement, the team chose to monitor the number of MET calls per week, the number of cardiopulmonary resuscitation or intubation events inside and outside the intensive care unit each month, and the rate of potentially preventable codes. Initially, calls for the MET were fewer than hoped for. The project team then undertook a series of steps to increase utilization:
Over time, the number of MET calls increased, averaging 70 per month (55/1,000 discharges). The hospital observed a decline in the number of cardiopulmonary and respiratory arrests occurring outside of the critical care unit, although given the hospital’s low mortality rate, the numbers are too small to determine whether the intervention had a significant impact on mortality (Westley, 2007).
OVERALL 100K LIVES CAMPAIGN RESULTS
On June 14, 2006, the IHI released the results of the 100,000 Lives Campaign at its 2nd Annual International Summit on Redesigning Hospital Care. Across 18 months, the participating hospitals combined prevented an estimated 122,300 avoidable deaths. Perhaps more important, said IHI President and CEO Donald Berwick, is the fact that so many hospitals had institutionalized new standards of care as a result of the campaign. He noted that more than 20 hospitals have reported no deaths from ventilator-assisted pneumonia over an entire year. This form of pneumonia is the leading cause of deaths from hospital-acquired infections.
“When we decided to launch the campaign we didn’t know if hospitals could take on another challenge,” Dr. Berwick said. “But the campaign has exceeded our highest expectations. The participating hospitals have not only prevented an estimated 122,300 unnecessary deaths, but they’ve also proven that it’s possible for the health care community to come together voluntarily to make significant changes in patient care. I have never before witnessed such widespread collaboration and commitment on the part of health care leaders and front-line staff to move the system giant steps forward” (Berwick et al., 2006).
Purchase (2004) argued that industry groups develop voluntary codes to enhance their commercial interests, typically:
To gain consumer confidence and trust
To forestall collective actions by consumers
To forestall adverse political interventions
To promote desire of political interventions
To restrain trade.
1 How does well does the 100,000 Lives Campaign fit with those constructs?
2. What does the experience of Virginia Mason Medical Center say about the implementation of voluntary codes in health care?
3 If you wanted to conduct future policy research based on the experiences of the 100,000 Lives Campaign hospitals, what would you measure and why?
4. What are other examples of voluntary codes used in the health care environment? Why are they so prevalent in this industry? What seems to determine the mix of voluntary and government regulations in health care settings?
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