Confirmation of the Validity of the Central-line Bundle as a Measure of a

Healthcare Intervention

Heather M. Gilmartin PhD, NP, CICPost-doctoral Nurse Fellow

Denver/Seattle Center of Innovation – Department of Veterans Affairs

Karen Sousa, PhD, RN, FAANProfessor and Associate Dean of Research and Extramural Affairs

University of Colorado, Anschutz College of Nursing

Disclaimer: The contents of this presentation do not represent the views of the Department of Veterans Affairs or the United States Government.

Objectives1. Define the central line (CL) bundle

and the influence of organizational context on healthcare interventions and outcomes

2. Discuss the methods to test and confirm the CL bundle as a latent variable model

What is a Central-line (CL)?• Long, thin tube

placed in a vein that ends near your heart

• Fluids, medications, blood products, monitoring, lab draws

• Used for critical patients or those who require long-term medications

Central-line Associated Bloodstream Infections (CLABSIs)

• The risk of CLABSIs in intensive care units are high (Klevens et al., 2007)

– 31,000 estimated deaths per year– $18,000 mean attributable cost per

CLABSI• Extended hospitalization• Greater risk for other complications• Loss of trust in healthcare system

IHI CL Bundle Perform hand hygiene prior to catheter

insertion Use maximum sterile barrier precautions

during insertion Use alcoholic chlorhexidine (CHG)

antiseptic for skin preparation Avoid use of femoral vein when possible Assess need for CL daily, remove

nonessential catheters

http://www.ihi.org/resources/Pages/Changes/ImplementtheCentralLineBundle.aspx

CL Bundle Program• Michigan Keystone Project: – 66% reduction in CLABSIs for

participating ICUs (Pronovost et al., 2006)– Reductions maintained 10 years after

initial study (Pronovost et al., 2015)

• Findings replicated in multiple settings

• Standard of practice for intensive care units (Marschall et al., 2014)

Intervention

Outcome

CL Bundle = Zero CLABSIs

Reality Check Organizations report programs are hard to fully implement and sustain (Dixon-Woods et al., 2011)

“Popular accounts of CL bundle program have often been simplistic and partial, perpetuating the myth that the program’s achievements can be traced to a “simple checklist” rather than a complex social intervention” (Bosk et al., 2009)

Clinical Example• Mr. Jones requires a CL for medication and

cardiac monitoring • Ideal situation:

– Surgical team present and all equipment at bedside– ICU nurse available to assist/monitor procedure– Hand hygiene performed– All staff don gloves/gown/mask/hat/eye protection– Patient prepped with barrier precautions and CHG – All others in room wearing a mask– Subclavian vein is chosen– Time out performed– Line placed successfully

Equipment not standardized and easy to

access

Nurses not included in

rounds

“Check the box”

culture

RN not comfortable speaking up

Maximum barrier precautions viewed as ridiculous

Little accountability

to safety processes

No policy

No training

What are the Challenges?

No belief in “Time Out”

Organizational Context• Organizational culture:– Perceived values and roles

• Organizational climate:– Practices and procedures

• Work environment:– Teamwork, leadership, communication,

resources• Structural characteristics:– Hospital size, teaching status, level of

technology

Understanding how and why programs work, not simply whether they work,

is crucial (Dixon-Woods et al., 2011)

Intervention

Outcome

Context

Learning Objective #2• Discuss the methods to test and

confirm the CL bundle as a latent variable model

Intervention

Outcome

Context

MethodsSample:• Prevention of Nosocomial Infection and Cost-

effectiveness-Refined (PNICER) Study (Stone et al., 2014)

• 614 U.S. hospitals reporting to NHSNMethods:• Secondary analysis using latent variable modeling• Sample randomly split for exploration/confirmationVariables:• CL bundle = healthcare intervention• CLABSI = outcome• Context = work environment + climate instruments

Factor Analysis • Multivariate statistical procedure• Tests how well measured variables

represent the number of constructs• Exploratory Factor Analysis:– Data explored for number of factors to

represent the data• Confirmatory Factor Analysis:– Number of factors specified – Confirms or rejects the theory

Exploratory Factor Analysis

Item Component 1Factor

LoadingHand Hygiene .950Max Barrier .957CHG .941Optimal Site .898Daily Check .823

Component Table Matrix

Explained variance 61.21%

Cronbach's alpha = .84

Confirmatory Factor Analysis

Implications for Research

Intervention

Outcome

Context

Implications for Practice

• The CL bundle is more than just a checklist

• Contextual factors need to be considered

• Investigate your environment – what are your barriers?

Future Research • Expand theory to other health outcomes– Other healthcare-associated infections– Falls/pressure ulcers– Medication errors

• Validation of existing contextual data sources to diagnose a units readiness to implement a new patient safety initiative– Annual Organizational Culture Survey – AHRQ Annual Patient Safety Culture Survey – Nurse Satisfaction Survey

Acknowledgements

• The authors would like to thank Dr. Pat Stone for use of the P-NICER data for secondary analysis, and the Infection Preventionists who responded to the survey.

• Funding for the P-NICER study was provided by the National Institute of Nursing Research (R01NR010107).

References• Bate, P. (2014). Context is everything. In J. R. Bamber (Ed.), Perspectives on context: A selection of essays considering the

role of context in successful quality improvement (pp. 1-30). London, England: Health Foundation.• Bosk, C.L., Dixon-Woods, M., Goeschel, C. A., & Pronovost, P.J. (2009). Reality check for checklists. The Lancet,

374(9688), 444-445. • Dixon-Woods, M., Bosk, C.L., Aveling, E.L., Goeschel, C.A., & Pronovost, P.J. (2011). Explaining Michigan: Developing an

ex post theory of a quality improvement program. Milbank Quarterly, 89(2), 167-205. doi: http://dx.doi.org/10.1111/j.1468-0009.2011.00625.x

• Furuya, E.Y., Dick, A., Perencevich, E.N., Pogorzelska, M., Goldmann, D., & Stone, P. (2011). Central line bundle implementation in US intensive care units and impact on bloodstream infections. PLoS ONE [Electronic Resource], 6(1), 1-6. doi: http://dx.doi.org/10.1371/journal.pone.0015452

• Klevens, R.M., Edwards, J.R., Richards, C.L., Horan, T., Gaynes, R.P., Pollock, D.A., & Cardo, D.M. (2002). Estimating healthcare-associated infections and deaths in US hospitals, 2002. Public Health Reports, 122, 160-166.

• Marschall, J., Mermel, L.A., Fakih, M., Hadaway, L., Kallen, A., O'Grady, N.P., . . . Yokoe, D.S. (2014). Strategies to prevent central line–associated bloodstream infections in acute care hospitals: 2014 pdate. Infection Control and Hospital Epidemiology, 35(7), 753-771. doi: 10.1086/676533

• Mitchell, P.H., Ferketich, S. , Jennings, B.M., & Care, American Academy of Nursing Expert Panel on Quality Health. (1998). Quality health outcomes model. Image - the Journal of Nursing Scholarship, 30(1), 43-46. doi: http://dx.doi.org/10.1111/j.1547-5069.1998.tb01234.x

• Pronovost, P., Goeschel, C.A., Colantuoni, E., Watson, S., Lubomski, L.H., Berenholtz, S., . . . Needham, D. (2010). Sustaining reductions in catheter related bloodstream infections in Michigan intensive care units: Observational study. British Medical Journal, 340(c309), 1-6. doi: http://dx.doi.org/10.1136/bmj.c309

• Stone, P., Pogorzelska-Maziarz, M., Herzig, C.T., Weiner, L.M., Furuya, E.Y., Dick, A., & Larson, E. (2014). State of infection prevention in US hospitals enrolled in the National Health and Safety Network. American Journal of Infection Control, 42(2), 94-99. doi: http://dx.doi.org/10.1016/j.ajic.2013.10.003

Thank you

Questions?