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Pediatrics. Mar 2011; 127(3): 419–426.
PMCID: PMC3387911
Nosocomial Infection Reduction in VLBW Infants With a Statewide Quality-Improvement Model
David D. Wirtschafter, MD,corresponding authora Richard J. Powers, MD,b Janet S. Pettit, MSN, NNP-BC, CNS,c Henry C. Lee, MD, MS,d W. John Boscardin, PhD,e Mohammad Ahmad Subeh, MA,f and Jeffrey B. Gould, MD, MPHg
aDavid D. Wirtschafter, MD, Inc;
bPediatrix Neonatology Medical Group, Good Samaritan Hospital, San Jose, California;
cDoctors Medical Center, Kaiser Permenente Medical Center, Modesto, California;
dDepartment of Pediatrics, Division of Neonatology, University of California, San Francisco, California;
eDepartments of Medicine and Epidemiology and Biostatistics, University of California, San Francisco, California;
fSchool of Medicine, Oregon Health Sciences University, Portland, Oregon; and
gDepartment of Pediatrics, Division of Neonatal and Developmental Medicine, Perinatal Epidemiology and Health Outcomes Research Unit, Stanford University, Stanford, California
corresponding authorCorresponding author.
Address correspondence to David D Wirtschafter, MD, 5523 Voletta Place, Valley Village, CA 91607. E-mail: david.wirtschafter/at/juno.com
Accepted December 10, 2010.
OBJECTIVE:
To evaluate the effectiveness of the California Perinatal Quality Care Collaborative quality-improvement model using a toolkit supplemented by workshops and Web casts in decreasing nosocomial infections in very low birth weight infants.
DESIGN:
This was a retrospective cohort study of continuous California Perinatal Quality Care Collaborative members' data during the years 2002–2006. The primary dependent variable was nosocomial infection, defined as a late bacterial or coagulase-negative staphylococcal infection diagnosed after the age of 3 days by positive blood/cerebro-spinal fluid culture(s) and clinical criteria. The primary independent variable of interest was voluntary attendance at the toolkit's introductory event, a direct indicator that at least 1 member of an NICU team had been personally exposed to the toolkit's features rather than being only notified of its availability. The intervention's effects were assessed using a multivariable logistic regression model that risk adjusted for selected demographic and clinical factors.
RESULTS:
During the study period, 7733 eligible very low birth weight infants were born in 27 quality-improvement participant hospitals and 4512 very low birth weight infants were born in 27 non–quality-improvement participant hospitals. For the entire cohort, the rate of nosocomial infection decreased from 16.9% in 2002 to 14.5% in 2006. For infants admitted to NICUs participating in at least 1 quality-improvement event, there was an associated decreased risk of nosocomial infection (odds ratio: 0.81 [95% confidence interval: 0.68–0.96]) compared with those admitted to nonparticipating hospitals.
CONCLUSIONS:
The structured intervention approach to quality improvement in the NICU setting, using a toolkit along with attendance at a workshop and/or Web cast, is an effective means by which to improve care outcomes.
Keywords: central-line–associated bloodstream infection, nosocomial infection, quality improvement, quality-improvement toolkits, quality-improvement evaluation
WHAT'S KNOWN ON THIS SUBJECT:
Quality-improvement techniques are increasingly effective as they move from passive dissemination to interactive techniques between those authoring practice change packages and their audiences. However, resource constraints and the many potential topics mitigate against prescribing intense collaboratives for every topic.
WHAT THIS STUDY ADDS:
Efficient progress in decreasing neonatal nosocomial infection rates can be achieved when statewide quality-improvement collaboratives using structured interventions (“toolkits”) are augmented with brief interactions that introduce, orient, and motivate potential users.
Reducing health care–associated or nosocomial infection in preterm infants has been a major challenge in the NICU. These critically ill infants are at risk because of biological factors, such as immature immune system,1 poor skin integrity,2 and prolonged need for parenteral support using invasive vascular access devices.3 In this setting, nosocomial infections result in increased morbidity, mortality, length of stay, and hospital costs.47 Overall, infection rates range from 21% to 30% of very low birth weight admissions to the NICU.5,8,9
The continuing efforts to identify and remediate neonatal nosocomial infection risk factors have been frequently described in this decade.1014 Implementing individual evidence-based interventions simultaneously as “care bundles” has become a standard stratagem.15,16 However, there still remain questions as to how best to efficiently foster adoption of these recommendations into routine clinical practice.
The primary focus of the California Perinatal Quality Care Collaborative (CPQCC) is to improve perinatal and neonatal outcomes in California by fostering evidence-based, data-driven performance-improvement projects. Since its inception, CPQCC has used a model in which toolkits with evidence-based practices and implementation aids are provided to member hospitals, with members invited to attend workshops and/or Web casts to further their knowledge as to how to implement their content.17 In this report, we evaluated the effectiveness of the CPQCC quality-improvement model in decreasing neonatal nosocomial infection rates. We examined the effects of quality-improvement participation as a predictor of nosocomial infection in very low birth weight infants born in CPQCC member hospitals by examining nosocomial infection rates during a baseline period (2002), implementation period (2003–2004), and evaluation period (2005–2006).
Study Design
This is a retrospective cohort study of NICUs continuously belonging to the CPQCC from 2002 through 2006.
Data Source
CPQCC membership is offered to any NICU in California. Members submit clinical data in a prospective fashion for very low birth weight infants at member hospitals using an expanded version of the Vermont-Oxford Network (VON) data set.18,19 To ensure data accuracy, the CPQCC conducts data abstractor trainings yearly, and each submitted record is subjected to a variety of range and logic checks both at the time of data entry and before data closeout. Records with excessive missing data are audited.
Intervention
The intervention consisted of promoting “provisional best practices” initially described as a bundle during the Neonatal Intensive Care Quality Improvement Collaborative Year 200012 and later incorporated, with modifications, into the CPQCC Nosocomial Infection Prevention Toolkit.20 These practices primarily addressed interventions relating to the evaluation and prevention of central line–associated bloodstream infections. These included (1) complying with diagnostic criteria and measurement standards for nosocomial infections; (2) improving hand-hygiene compliance; (3) preventing intravascular catheter–related infections by adopting stringent insertion practices and catheter maintenance routines, including maintaining closed vascular systems and reliable, antiseptic methods for line entry; and (4) promoting enteral feedings to lessen line days. The promotion of these methods followed a process that has been previously discussed,17 which consisted of (1) description of and endorsement by CPQCC, of provisional best practices; (2) production of a toolkit encompassing the evidence basis of these recommendations, along with exemplar policies, procedures, teaching aides, and quality audits for implementation; and (3) a 1-hour presentation to introduce the materials. These presentations were made either at workshops (February 28, 2003, and October 31, 2003) or as a Web cast (June 3, 2004). Every CPQCC NICU was invited to participate, preferably bringing a quality-improvement team consisting of physicians and nurses (nursing leadership, clinical specialist, and staff nurses and infection-control practitioners); attendance was voluntary and entirely at the discretion of each NICU. No provision was budgeted or made for follow-up collaboration to help participants with additional problem solving, experience sharing, or mentoring. Because of the time required to implement and assimilate these complex processes, we designated the entire 2-year period surrounding the roll-out events as the implementation phase (2003–2004).
Participation in the workshops and Web cast was variable, with 3 NICUs attending all 3 events, 9 attending 2 events, and 15 attending 1 event. However, toolkit usage within California also was freely available to nonparticipants and was, indeed, promoted by speakers at other meetings throughout the state and also likely by word of mouth as staff migrated between NICUs.
Definition of Nosocomial Infection
The primary outcome was nosocomial infection (ie, late sepsis or meningitis), as defined identically by the CPQCC and VON.18,19 The definition was sepsis or meningitis occurring after the age of 3 days (the day of birth is defined as day 1, regardless of time of birth). Sepsis or meningitis was diagnosed by positive blood or cerebrospinal fluid cultures of coagulase negative Staphylococcus (CoNS) or bacterial pathogens other than CoNS. If CoNS was recovered from a culture, several other criteria were applied to define the event as a nosocomial infection: (1) signs of generalized infection (such as apnea, temperature instability, feeding intolerance, worsening respiratory distress, or hemodynamic instability) and (2) treatment with 5 or more days of intravenous antibiotics after the culture was obtained. If both CoNS and another bacterial pathogen were recovered simultaneously from a culture, the patient was coded to have only a late bacterial pathogen and not CoNS.
Study Population
Fifty-four hospitals were CPQCC members continuously during the study period (2002–2006). During this interval, these hospitals cared for 20 934 very low birth weight infants. We limited our analysis to inborn patients who were never transferred to ensure that any nosocomial infection occurrence was accurately associated with just the 1 hospital in which it occurred, thus decreasing the sample size to 15 388 infants. This caused the loss of considerable sample size from the nondelivering Childrens' Hospitals in the state. Of those inborn, 960 died in the delivery room and were excluded, as were 1195 infants whose length of stay was less than 4 days or unknown; all of whom could not be coded as having nosocomial infections because the definition applies to only those 4 days of age or more. Another 12 infants were excluded because nosocomial infection status observations were not submitted. An additional 167 infants missing data for potential covariates (listed below) also were excluded.
We also excluded patients who had diagnoses of medical or surgical necrotizing enterocolitis noted or other abdominal surgery recorded (n = 809), reasoning that these diagnoses are associated with high bacteremia rates, whose presence reflects the primary disease processes rather than line-care processes, which is the focus of this intervention.8,14,21
The final analytic cohort consisted of 12 245 infants born at 54 hospitals. Of these, 7733 infants, referred to as participants, were born in the 27 hospitals whose staff member(s) participated in at least 1 workshop or Web cast, and 4512 patients, referred to as nonparticipants, who were born in 27 hospitals where no staff member participated. The nonparticipants were not strictly an unexposed control group because all toolkit materials were freely available via the Web site to all CPQCC members for use in locally initiated quality-improvement activities.
Analysis
We calculated crude NICU nosocomial infection rates for the years 2002 and 2006 and tested the participant and nonparticipant rates for differences using the Student's t test. A multivariable logistic regression model for nosocomial infection was developed with risk adjustment for the following variables: maternal race or ethnicity, prenatal care, gestational age in completed weeks, multiple birth, being small for gestational age, gender, congenital anomaly, 5-minute Apgar score, any surgery other than abdominal surgery, and the NICU's California Children's Services (CCS) level of care. Clustering within the hospital was accounted for by modeling the hospital as a random effect.
The CCS classification of NICUs are defined by regulation and include 3 levels: Regional NICUs provide mechanical ventilation and major surgery without restriction but only variably provide onsite extracorporeal membrane oxygenation and cardiac surgery for all serious malformations (equivalent to the American Academy of Pediatrics Levels IIIC and IIID)22; community NICUs provide unrestricted care and ventilation to infants of all gestational ages but are limited to surgery of only stable infants or those with a patent ductus arteriosus (equivalent to American Academy of Pediatrics Level IIIA and IIIB)22; intermediate NICUs (equivalent to American Academy of Pediatrics Level II) provide care to a variably restricted population, ventilate only up to a specified number of hours, and refer all complicated cases to a higher level of care22; and unclassified NICUs include NICUs that have not sought CCS certification because they do not participate in the voluntary CCS certification program.
The primary independent variable of interest, participant status in 1 or more toolkit introductory workshops or Web casts, was categorized into 3 groups: (see Fig 1: Project Time line Periods): (1) nonexposed, which included nonparticipants during all years of the study and participants during their baseline year 2002; (2) participants during the dissemination and implementation years of 2003 and 2004, when participant infants were being treated at NICUs with 1 or more staff members who participated in a toolkit introductory session; and (3) participants during the evaluation years (2005–2006). NICUs joining CPQCC after 2002 were excluded because they lacked baseline data. Models were created for nosocomial infection, CoNS infection, and late bacterial infection. Analyses were performed using SAS version 9.1 (SAS, Cary, NC). We used PROC GLIMMIX for multivariable models to account for clustering within hospitals.
FIGURE 1
FIGURE 1
Project time line periods: 54 continuous CPQCC member NICUs 2002–2006. “Nonparticipants” indicates infants cared solely at a NICU who never had a staff member participate in a Toolkit introductory session; “Participants” (more ...)
Institutional Review
The collaborative project was conceived, designed, and implemented with the sole purpose of quality improvement, and, for this reason, no review by an institutional review board was sought.23 All data collected were part of routine clinical care. All submitted and analyzed data contained no patient identifiers. Although each participant NICU was asked to identify its own improvement needs, they received no additional guidance from the project leadership. Data analysis for the study was approved by the University of California, San Francisco, Committee on Human Research.
Characteristics of the study cohort are shown in Tables 1 and and22 by quality-improvement participant status. More infants in the treatment cohort were born in regional centers. Quality-improvement participant hospitals had more infants born to Asian mothers, whereas non–quality-improvement participant hospitals had more infants born to white mothers and those with Hispanic ethnicity. The treatment group had a higher proportion of infants with congenital anomalies and of multiple gestations.
TABLE 1
TABLE 1
Hospital Characteristics of the Study Cohort
TABLE 2
TABLE 2
Patient Characteristics of the Study Cohort
In the years 2002–2006, 16.7% of infants born in the study cohort were diagnosed with a nosocomial infection, of which 37% were classified as having a late bacterial pathogen only, 46% with CoNS infections only, and 17% having both late bacterial pathogen and CoNS during the same hospitalization. For the whole study cohort, the nosocomial infection rate decreased from 16.9% in 2002 to 14.5% in 2006 (P = .02). The quality-improvement participants' nosocomial infection rate decreased from 15.6% in 2002 to 13.5% in 2006 (P = .09). The non–quality-improvement participants nosocomial infection rate decreased from 19.4% in 2002 to 16.4% in 2006 (P = .10).
After risk adjustment, quality-improvement participation was significantly associated with the reduction in nosocomial infection for the evaluation period 2005–2006 (odds ratio [OR]: 0.81 [95% confidence interval [CI]: 0.68–0.96]) (Table 3). Separate multivariable models were created for the outcomes of CoNS infection and for late bacterial pathogen infection. Quality-improvement participation was significantly associated with a decrease in CoNS infection for the evaluation period (OR: 0.78 [95% CI: 0.64–0.96]). There was no significant difference in late bacterial pathogen infection for quality-improvement participation in the evaluation period (OR: 0.95 [95% CI: 0.76–1.18]).
TABLE 3
TABLE 3
Multivariable Analysis of Risk of Nosocomial Infection in Very Low Birth Weight Infants, the CPQCC
Our evaluation showed that participation of NICU personnel in a brief, structured quality-improvement intervention was associated with decreased nosocomial infection overall and in 1 of 2 subcategories of nosocomial infection. Measurement was confounded by the indirect methods for discerning these outcomes and the potential for database definitions to bias the information available.
Our study could not directly address the central-line–associated bloodstream infection rate, the measure of most proximate interest to our intervention, using the available nosocomial infection event data as recorded with VON/CPQCC definitions. However, we incorporated 2 adjustments of these VON/CPQCC nosocomial infection variables to bring our measure closer to reflecting the outcome of interest. First, we excluded transferred infants to prevent duplicate counting and errors in assigning center responsibility for nosocomial infection events among those transferred. Second, we excluded infants who had abdominal surgery or necrotizing enterocolitis to avoid the confounding in measurement of nosocomial infection events possibly associated with translocation infections, which can be frequent in those settings.14,21,24,25 We found in secondary analysis that including those patients did not significantly alter our results because quality-improvement participation still was associated with reduced nosocomial infection when including those patients (OR: 0.83 [95% CI: 0.70–0.97]).
Limitations of our study were the inability to accommodate underreporting of multiorganism infections (reported as ranging from 3% to 10% in recent reports)8,2629 or specifying the denominator as number of line days because both data elements are not included in the VON/CPQCC data sets. Another limitation of the VON/CPQCC data definitions is that they prioritize recording late bacterial infection events over CoNS events in the case of multiorganism infections. If CoNS and a bacterial pathogen are cultured simultaneously, then the event is reported only as a late bacterial infection, ignoring the presence of the CoNS.
A strength of our study was the rich clinical and demographic data available for risk adjustment. As shown in Table 3, factors such as gender and surgery were significantly associated with nosocomial infection. By having our unit of analysis as the patient rather than the NICU, we were able to account for these risk factors at the individual level, giving a more accurate estimation of the impact of the intervention. Few studies of quality interventions collect detailed patient-level data that enable patient-specific risk adjustment to be made as used in this study and also account for clustering by the hospital.30,31 We did find moderate intra-cluster correlation, and therefore this was a statistical and practically important methodologic consideration. Accounting for clustering by hospital can selectively change the results of analyses on quality processes.32
The calculated ORs (Table 3) indicate that being admitted to a participating center during the intervention's evaluation phase was associated with a 24% decrease in nosocomial infection (OR: 0.81 [95% CI: 0.68–0.96]) compared with nonparticipants. Although the late bacterial infection events did not significantly change for quality-improvement participants, CoNS events decreased significantly, 22% risk decrease (OR: 0.78 {95% CI: 0.64–0.96). This finding is consistent with previous descriptions of the success described by nosocomial infection reduction programs in reducing CoNS bloodstream infections3339 and our own finding of an overall reduction in the composite metric of nosocomial infection.
Our intervention should be evaluated within the spectrum of methods used to influence clinical practice.30,40,41 These include traditional continuing medical education, practice guidelines, toolkit dissemination, and collaboratives. Traditional continuing medical education and nursing education operates without structured connections between authors and practitioners. Knowledge is broadcast (1-way communication), and desired outcomes are only diffusely defined. Continuing medical education evaluations suggest marginal effects on practice.31,42,43 Guidelines share characteristics of traditional continuing medical education, except that the knowledge production is targeted and outcomes are well defined. Evaluations show slightly better effects, with some efforts showing significant results.30,44
Toolkits represent an additional elaboration of guidelines but with features that specifically facilitate guideline implementation, such as exemplar policies, staff training aids, and quality audit materials. They combine both persuasive and instrumental knowledge elements deemed by their producers to be of import to their targeted audience.45 Although toolkits describe measureable outcomes, they may or may not be used to collect and analyze outcome data.
Collaboratives include both the programmatic elements of the toolkit methodology and the provision for ongoing communication between members. They structure ongoing communication among participants, thereby ensuring the social networking that is now increasingly recognized as essential to knowledge implementation.46,47 Collaboratives also enable ongoing evaluations of processes and outcomes. Finally, collaboratives provide structure to organizational learning at multiple levels (ie, as they become communities of practice).4851 The objectives evolve as members' practices evolve and face new challenges or attempt to incorporate newer methods and/or technologies.
Each of these knowledge dissemination methods requires increasing amounts of project leadership, support staff, and resources. Our study supplements this literature by indicating that even brief (1 hour), structured interventions (with dissemination-oriented toolkits) can produce demonstrable effects, with a resource effort somewhere between guideline production and collaborative operation.
Our findings are consistent with other studies of knowledge dissemination in neonatal medicine. Traditional nursing and continuing medical education, even when conducted with topical lectures given at the site of care, only variably produce the desired care process changes.52 When combined with clinical algorithms, yet another technique to operationalize guidelines, neonatal processes in particular51 and pediatric ones in general53 are demonstrably changed. Neonatal guidelines affect process but only inconsistently affect outcomes.54 In contrast, targeted neonatal collaboratives have consistently affected their targeted outcomes (age at surfactant administration38,54 and nosocomial infection or central-line–associated bloodstream infection reduction).38,39,56,57 Our study shows a positive effect on the outcome of interest, although we did not have access to corroborating process data and made no specific plans for follow-up.
Toolkits have become recognized as an efficient means to transmit implementable guidelines. Our toolkit has been acknowledged as a foundation document by several like-minded collaboratives.56,58,59 Even without the inclusion of means for continuing collaborative communication, which conceivably could be done at a small added cost, they aid assimilation of complex care practices. Additional studies are needed to better describe the benefits of varied quality-improvement models versus their resource inputs.
CONCLUSIONS
Brief, structured interventions can work and should be considered as part of the spectrum of interventions that knowledge dissemination managers and NICU quality-improvement leaders consider when designing practice-influencing projects because they balance factors such as the population to be served, the breadth and complexity of the topic addressed, the effects desired, and the resources available. Both methods and results are generalizable throughout the neonatal community in particular and in other intensive care environments.
ACKNOWLEDGMENTS
Partnered funding for this report was from each NICU's CPQCC membership dues; the National Institutes of Health, National Center for Research Resources, Office of the Director, University of California, San Francisco, Clinical and Translational Science Grant KL2 RR024130.
The contents of this article are solely the responsibility of the authors and do not necessarily represent the official views of the National Institutes of Health (to Henry C Lee).
 
FINANCIAL DISCLOSURE: David D Wirtschafter, MD, is the President of David D Wirtschafter, MD, Inc, a quality-improvement firm. It provides consulting services to the CCS, Department of Healthcare Services, State of California. Richard Powers, MD, is an employee of Pediatrix Neonatology Medical Group of San Jose, California. Janet Pettit MSN, NNP-BC, CNS, is a paid consultant to the CCS, Department of Healthcare Services, State of California. Mohammad Ahmad Subeh, MA, was an employee of the Perinatal Epidemiology and Health Outcomes Research Unit, Stanford University, Stanford, California. During this project, Jeffrey B Gould, MD, MPH, is a member of the Department of Pediatrics, Division of Neonatal and Developmental Medicine, Perinatal Epidemiology and Health Outcomes Research Unit, Stanford University, Stanford, California, and is the principal investigator for contracts relating to the operation of CPQCC from CCS.
 
CPQCCCalifornia Perinatal Quality Care Collaborative
VONVermont-Oxford Network
CoNScoagulase negative Staphylococcus
CCSCalifornia Children's Services
ORodds ratio
CIconfidence interval

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