The SSC performance improvement initiative was launched in multiple sites internationally to measure changes in the rates at which the sites achieved the targets of the guideline bundles and to assess the impact of compliance with the program on hospital mortality. The Campaign activities included: the development of sepsis bundles; creation of educational materials; recruitment of sites and local physician and nurse champions through national and international meetings; organization of regional launch meetings where the initiative was introduced and educational materials presented; and the distribution of a secure database application that allowed for data collection and transfer, and offered a simple means for providing practice audit and feedback to local clinicians.
Guideline and bundle development
After the development of the evidence-based guidelines, the SSC steering committee partnered with the Institute for Healthcare Improvement (IHI) to develop a quality improvement program to extend the Campaign guidelines to the bedside management of severely septic and septic shock patients [23, 24]. In partnership with IHI, key elements of the guidelines were identified and organized into “bundles” of care [25, 26]. A two-phase approach was established, which included the generation of two sets of performance measures: the first to be accomplished within 6 h of presentation with severe sepsis (the “resuscitation bundle”) and a second set to be accomplished within 24 h (the “management bundle”) (Fig. 1) [27, 28].
Sites and patient selection
Any hospital wishing to join the Campaign was eligible. Participation was voluntary. Participant sites were recruited at professional critical care congresses and meetings, through the SSC and IHI Web sites, and by interest generated from publication of the SSC guidelines. Campaign symposia were regularly held at international congresses and other venues between 2004 and 2008 to increase awareness and participation. Local champions and Campaign faculty were identified and trained to develop regional and national networks.
Sites were encouraged to set up screening procedures to identify patients with severe sepsis based on previously established criteria . Sites were provided a sample screening tool in the Campaign manual and on the Web site . Participating sites were asked to screen for patients in the emergency department (ED), the clinical wards, and the ICU. Methods of screening were ultimately established locally, and no effort to supervise the quality or completeness of screening was attempted.
To be enrolled, a subject had to have a suspected site of infection, two or more systemic inflammatory response syndrome (SIRS) criteria , and one or more organ dysfunction criteria. (See Supplemental Fig. 1 online.) Clinical and demographic characteristics and time of presentation with severe sepsis criteria were collected for analysis of time-based measures. Time of presentation was determined through chart review and defined in instructions to site data collectors on the Campaign Web site and educational materials. For patients enrolled from the ED, the time of presentation was defined as the time of triage. For patients admitted to the ICU from the medical and surgical wards and for patients in the ICU at the time of diagnosis, the time of presentation was determined by chart review for the diagnosis of severe sepsis.
Educational materials and resources
Educational materials available on the SSC Web site included directions for implementing the bundles and supporting data for each bundle element. A comprehensive manual, Implementing the Surviving Sepsis Campaign, was published in 2005 and included the data collection tool in CD format . The manual was also distributed at meetings. It included protocols for participation and links to download the database. It also reviewed issues related to ensuring consistency and quality in data collection. The manual contents were placed on the IHI and SSC Web sites. Cards and posters of the two sepsis bundles (Fig. 1) were printed and widely distributed.
During the course of the study period, initiation meetings were held for participating hospital groups and regional SSC launches, at which educational materials were distributed, methods for data collection described, institutional change concepts introduced, and examples of implementation discussed. Ultimately, hospital-level efforts and local protocol development were the purview of individual improvement teams at each institution or network. An e-mail list server with voluntary membership was established to allow teams to collaborate across sites by asking questions of their colleagues and to direct communication from the SSC to sites. List members were encouraged to share tools, protocols, and experiences. Although no formal evaluation was in place to assess the quality of data entered, concern regarding this topic was the second most frequently discussed area among participants (following concern regarding roadblocks to achieving physician engagement). Two of the authors (CS and SRT) served as primary references for all questions regarding data collection and entry throughout the Campaign, and provided training for each site when requested. A bi-monthly electronic newsletter was published to share successes, strategies, and events.
Bundle targets and clinical outcomes
The primary outcome measure was change in compliance with bundle targets over time. We defined compliance as evidence that all bundle elements were achieved within the indicated time frame (i.e, 6 h for the resuscitation bundle; 24 h for the management bundle). As such, failure to comply might occur either because of the failure of the physician to attempt to meet the target or the failure to reach the target despite the clinician’s attempt. Secondary outcome measures included hospital mortality, hospital length of stay, and ICU length of stay. Ten performance measures were established, based on the individual elements of the resuscitation bundle and the management bundle.
Data were entered into the SSC database locally at individual hospitals into pre-established, unmodifiable fields documenting performance data and the time of specific actions and findings. Data on the local database contained private health information (PHI) that enabled individual sites to audit and review local practice and compliance as well as provide feedback to clinicians involved in the initiative. Data stripped of PHI were submitted every 30 days to the secure master SSC server at the Society of Critical Care Medicine (Mount Prospect, Ill.) via file transfer protocol (FTP) or as comma-delimited text files attached to e-mail submitted to the Campaign’s server.
The global SSC improvement initiative was reviewed and approved by the Cooper University Hospital Institutional Review Board (Camden, NJ) as meeting criteria for exempt status. Individual hospitals were encouraged to refer to these documents and submit to their local IRBs per local policy for documentation of exempt status or waiver of consent. The US Department of Health and Human Services’ Office for Human Research Protections clarified that quality improvement activities such as SSC often qualify for IRB exemption and do not require individual informed consent .
Analysis set construction
The analysis set was constructed from the subjects entered into the SSC database from its launch in January 2005 through March 2008. The a priori data analysis plan limited inclusion to sites with at least 20 subjects and at least 3 months of subject enrollment. Analysis presented here was limited to the first 2 years of subjects at each site (Table 1).
Sites were characterized by: hospital size (<250, 250–500, >500 beds); teaching status; ICU type (medical, medical/surgical, other); and geographic region (Europe, North America, South America). Subjects were characterized by baseline severe sepsis information: location of enrollment (ED, ICU, ward); site of infection (pulmonary, urinary tract, abdominal, CNS, skin, bone, wound, catheter, cardiac, device, other); acute organ dysfunction (cardiovascular, pulmonary, renal, hepatic, hematologic). Subject age and gender were not collected in deference to country-specific privacy laws.
Data were organized by quarter through 2 years, with the first 3 months that a site entered subjects into the database defined as the first quarter regardless of when those months occurred from January 2005 through March 2008. Results are presented by site quarter, comparing the initial quarter to the final quarter for all sites and by comparing the initial quarter to all subsequent quarters.
Because differences in bundle achievement and outcomes could be confounded by changes in the characteristics of subjects entered into the database, risk-adjustment logistic regression models were constructed to control for baseline subject characteristics. All baseline characteristics present in the database were included in the risk-adjustment models including location of enrollment, acute organ dysfunctions, and site of infection. Site of infection was reduced to pulmonary or non-pulmonary to decrease the number of covariate patterns in the data and increase the utility of the model residuals to assess model fit. Because the collection of some bundle elements was conditioned on subject characteristics, different models were constructed for each subpopulation. The model assessing the base set of elements applicable to all subjects (lactate measurement, blood culture before antibiotic administration, broad spectrum antibiotic administration, and glucose control) included the baseline subject characteristics as well as these elements. The model assessing the administration of drotrecogin alfa in subjects with multiple organ failures also included the baseline subject characteristics and the base set of bundle elements. The model assessing plateau pressure control in mechanically ventilated subjects also included the baseline subject characteristics and the base set of bundle elements. The model assessing the administration of drotrecogin alfa, low-dose steroids, CVP >8, and ScvO2 >70 in subjects in shock despite fluids also included the baseline subject characteristics and the base set of bundle elements.
To demonstrate that a decrease in hospital mortality over time was not associated with entering less severely ill patients in the database at individual sites, a logistic regression model was constructed. It contained all subjects entered over the maximum of 2 years of data collection and the baseline subject characteristics for the quarter of participation for up to eight quarters. Because sites could enter the Campaign at any time, the possibility that decreased hospital mortality over time was associated with a global decrease in mortality for the same severity of illness was investigated by constructing a logistic regression model for hospital mortality using the first quarter of data collection from each site, including the baseline subject characteristics and the calendar quarter (1 for the first quarter of 2005 through 13 for the first quarter of 2008).
We compared raw rates including hospital mortality and bundle compliance using Fisher’s exact test. We expressed the effects of predictor variables on hospital mortality using odds ratios, including 95% confidence intervals for risk-adjusted results. We assessed logistic regression model fit using the Hosmer–Lemeshow C statistic, the χ2 dispersion, the proportion of log-likelihood accounted for by the model, and an examination of model residuals. We constructed the databases in Access and FoxPro (Microsoft Corp., Redmond, WA) and conducted analyses in DataDesk (Data Description, Ithaca, NY) and SAS (SAS Institute, Cary, NC).