2.50
Hdl Handle:
http://hdl.handle.net/10755/621827
Category:
Full-text
Format:
Text-based Document
Type:
Presentation
Level of Evidence:
N/A
Research Approach:
N/A
Title:
The Development and Testing of a Measure for Turbulence in Intensive Care
Other Titles:
Creating a Culture of Patient Safety
Author(s):
Browne, Jennifer A.; Braden, Carrie Jo
Lead Author STTI Affiliation:
Beta Mu
Author Details:
Jennifer A. Browne, PhD, RN-BC, CCRN, Professional Experience: 2015-Current: Assistant Professor University of Incarnate Word, San Antonio, TX 2015-Current: Pool RN, Surgical Intensive Care, Northeast Baptist Hospital 2005-2015 Staff Nurse/ Weekend ICU Shift Supervisor, Baptist Health San Antonio 2009-2014 Adjunct Clinical Faculty Baptist School Health Professions 1994-2005 Clinical Informatics Coordinator Methodist Healthcare Systems San Antonio Author Summary: Dr. Browne has dedicated her career to improving the nurses' workplace. Her primary research focuses on understanding the workarounds that acute care nurses perform. She has spoken both nationally and internationally and her research has won awards at the Nursing Informatics Congress and AMIA. She is board certified in informatics and critical care. Dr. Browne is an Assistant Professor at The University of Incarnate Word and still works shifts in a local ICU.
Abstract:

Purpose:

Nursing workload is a valuable measure of a nurses’ work and is used to determine the needs of a unit and to bring some degree of standardization to staffing models and costs. Once a workload measure is in place, connections and correlations can be made between nurse staffing, performance measures and patient outcomes.1 Gaining a better understanding of nursing work has become especially important as leaders attempt to balance diminishing healthcare resources and cost containment with a need to promote clinical outcomes and patient safety..(Berry & Curry, 2012;  Myny, Van Hecke, De Bacquer, Verhaeghe, Gobert, Defloor & Van Goubergen, 2012).

While undertaking a model-building dissertation study, it became evident that the concept of workload did not describe all the activities nurses were performing. It was observed that some staff nurses with moderate to low workload assignments were exhibiting stress and were delayed with scheduled tasks. The nurses voiced frustration with work blockages such as incorrect medications delivered, missing supplies (i.e., wrong size ostomy bag) and equipment issues (i.e., broken bar code scanner). The activities undertaken to surmount barriers to completing patient care were not captured in standard workload measures. (Baernholdt, Cox & Scully, 2010)

Because the full extent of nurse activities could not be specified in the proposed model, a variable for turbulence was created in order to capture nurse activities not represented by workload. The purpose of this presentation is to report the completed validity and reliability testing of a measure for turbulence and, based on the identified characteristics, propose a turbulence definition. Recommendations for future research are influenced by the initial correlation findings between turbulence, workload and patient safety.

Literature Review:

    Environmental turbulence has been defined as “an interaction between individuals and their environment in response to instability and rapid changes in their internal and/or external environment affected by attributes of the individuals, groups and/or the organization with the potential to impact patient and nursing outcomes” (Bosco, 2007, p.13).  Turbulence is inclusive of internal factors with a notion of ineffective buffering of any disruptive force that may intrude upon the nurses’ ability to perform nursing practice and provide patient care. (Tillman, Salyer & Corely, 1997; Bosco, 2007).

 Jennings (2007) characterized turbulence as a loss of control due to simultaneous demands; difficult, or unfamiliar work; heavy patient loads; and excessive responsibility.  Turbulence attributes clustered into two themes: communication and workload. Unique stressors, exclusive to our conceptualization of turbulence were those items that grouped primarily under nursing communication: breakdowns, distractions, interruptions, loss of information during handoffs, cognitive stacking and impaired decision-making. (Salyer, 1995; Patterson & Wears, 2010; Rivera-Rodriguez & Karsh, 2010; Coiera, 2012; Hopkinson & Jennings, 2013; Park, Blegen, Spetz, Chapman & DeGroot, 2013).

 Methods:

This mixed methods study was conducted in collaboration with The American Association of Critical Care Nurses (AACN) and approved by The University of Texas Health Science Center IRB.  A 15 item turbulence scale was developed from the literature and tested in a mixed methods dissertation pilot with our local chapter of AACN. Clinical experts in critical care helped determine content validity. Reliability was tested using an interrater approach with critical care nurse raters scoring unique workload and turbulence components

The turbulence items were then administered as part of a national survey interested in assessment of a Health Information Technology Workaround Model. A voluntary survey was sent to all members of AACN. Respondents were asked if any of the 15 listed activities were present or impacted work on their unit during their workaround experience. Responses were on a Yes (1)/ No (0) scale. Workload was measured using acuity, staffing ratio, and the nurse’s perception of their workload (light, moderate and heavy).

 Results:

A sample of 307 AACN RN members responded to an email survey consisting of items measuring nurse characteristics, workload, turbulence/ problems and patient safety risk (or event) and workarounds. Open ended questions solicited narrative descriptions of the problems, work activities and workarounds encountered or performed by the nurses. The respondents were 87% female, and the majority were 45 years old or greater. Almost 50% of the nurses had a bachelor’s degree in nursing, and 20.6% an associate degree. Nurse experience was midway between proficient and expert. Intensive care specialties included adult, pediatric and neonatal. Patient acuity was reported as: 61.8% critical, 28.7% guarded. Workload of the nurse was reported as heavy (40%) and moderate (58%).

 

 The distribution characteristics for the turbulence items will be presented. Sudden changes in acuity, interruptions and distractions were reported by more than half of the respondents. Other frequently selected turbulence items included administrative demands, communication breakdowns, information overload, noise, transfers in and out of the unit and staff having to leave the unit. Triangulation methods resulted in inter-method agreement of all 15 of the turbulence characteristics. There were no outliers or additional attributes identified.

 

The minimum amount of data for factor analysis was satisfied with a final sample size of 296 (> 12 cases per variable). Using completed study data, consistency for the total scale indicated a Cronbach’s alpha of .75 (p<.01). The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was .77, above the recommended value of .6, therefore exploratory factor analysis of the 15 items was examined. Based on principal component extraction with varimax rotation, the five factor solution obtained had Eigen values greater than one and factor loadings ranging from .53 to .82. The 5 factors explained 54% of the variance. The criteria for the factor solutions are consistent with conventional statistical recommendations (Polit & Beck, 2008). Based on the analysis, the definition of turbulence offered by this work is: The degree to which the interaction between a nurse and attention diversion, resource inadequacy, communication breakdowns, sudden acuity increases and interpersonal relationships affects the nurses’ ability to practice or provide care.

Conclusion: 

Initial testing of a turbulence measure demonstrated reliability and validity and produced a preliminary definition based on essential attributes. Hyun, Bakken, Douglas and Stone (2008, p.8) state “staffing decisions that lack consideration of all relevant factors may result in poor patient outcomes”.  Workload, although widely used, does not tell the entire story and underestimates the totality of nurses’ tasks and responsibilities. When considering workload and turbulence, a broader understanding of nurse activities might provide us with alternative solutions beyond “staffing”. For example, workload (i.e., acuity, admissions and discharges) might be difficult to manipulate, but turbulence items, such as interruptions, loss of information, communication breakdowns and inadequate resources can be intervened upon. In the primary study we found that turbulence was most strongly correlated with safety hazards (= .41, N= 293, p= .000) whereas the association between workload and safety hazards (= .16, N= 29, p= .005) had the weakest relationship. The findings of this research will be presented and suggest that interventions aimed at turbulence reduction should result in better clinical outcomes and a reduction in safety risk.

Keywords:
Patient Safety; Turbulence; Workload
Repository Posting Date:
13-Jul-2017
Date of Publication:
13-Jul-2017
Other Identifiers:
INRC17S04
Conference Date:
2017
Conference Name:
28th International Nursing Research Congress
Conference Host:
Sigma Theta Tau International
Conference Location:
Dublin, Ireland
Description:
Event Theme: Influencing Global Health Through the Advancement of Nursing Scholarship

Full metadata record

DC FieldValue Language
dc.language.isoen_USen
dc.type.categoryFull-texten
dc.formatText-based Documenten
dc.typePresentationen
dc.evidence.levelN/Aen
dc.research.approachN/Aen
dc.titleThe Development and Testing of a Measure for Turbulence in Intensive Careen_US
dc.title.alternativeCreating a Culture of Patient Safetyen
dc.contributor.authorBrowne, Jennifer A.en
dc.contributor.authorBraden, Carrie Joen
dc.contributor.departmentBeta Muen
dc.author.detailsJennifer A. Browne, PhD, RN-BC, CCRN, Professional Experience: 2015-Current: Assistant Professor University of Incarnate Word, San Antonio, TX 2015-Current: Pool RN, Surgical Intensive Care, Northeast Baptist Hospital 2005-2015 Staff Nurse/ Weekend ICU Shift Supervisor, Baptist Health San Antonio 2009-2014 Adjunct Clinical Faculty Baptist School Health Professions 1994-2005 Clinical Informatics Coordinator Methodist Healthcare Systems San Antonio Author Summary: Dr. Browne has dedicated her career to improving the nurses' workplace. Her primary research focuses on understanding the workarounds that acute care nurses perform. She has spoken both nationally and internationally and her research has won awards at the Nursing Informatics Congress and AMIA. She is board certified in informatics and critical care. Dr. Browne is an Assistant Professor at The University of Incarnate Word and still works shifts in a local ICU.en
dc.identifier.urihttp://hdl.handle.net/10755/621827-
dc.description.abstract<p><strong>Purpose:</strong></p> <p>Nursing workload is a valuable measure of a nurses’ work and is used to determine the needs of a unit and to bring some degree of standardization to staffing models and costs. Once a workload measure is in place, connections and correlations can be made between nurse staffing, performance measures and patient outcomes.1 Gaining a better understanding of nursing work has become especially important as leaders attempt to balance diminishing healthcare resources and cost containment with a need to promote clinical outcomes and patient safety.<sup>.</sup>(Berry & Curry, 2012; <sup> </sup>Myny, Van Hecke, De Bacquer, Verhaeghe, Gobert, Defloor & Van Goubergen, 2012).</p> <p>While undertaking a model-building dissertation study, it became evident that the concept of workload did not describe all the activities nurses were performing. It was observed that some staff nurses with moderate to low workload assignments were exhibiting stress and were delayed with scheduled tasks. The nurses voiced frustration with work blockages such as incorrect medications delivered, missing supplies (i.e., wrong size ostomy bag) and equipment issues (i.e., broken bar code scanner). The activities undertaken to surmount barriers to completing patient care were not captured in standard workload measures. (Baernholdt, Cox & Scully, 2010)</p> <p>Because the full extent of nurse activities could not be specified in the proposed model, a variable for turbulence was created in order to capture nurse activities not represented by workload. The purpose of this presentation is to report the completed validity and reliability testing of a measure for turbulence and, based on the identified characteristics, propose a turbulence definition. Recommendations for future research are influenced by the initial correlation findings between turbulence, workload and patient safety.</p> <p>Literature Review:</p> <p> <sup> </sup> <sup> </sup>Environmental turbulence has been defined as “an interaction between individuals and their environment in response to instability and rapid changes in their internal and/or external environment affected by attributes of the individuals, groups and/or the organization with the potential to impact patient and nursing outcomes” (Bosco, 2007, p.13).<sup> </sup> Turbulence is inclusive of internal factors with a notion of ineffective buffering of any disruptive force that may intrude upon the nurses’ ability to perform nursing practice and provide patient care. (Tillman, Salyer & Corely, 1997; Bosco, 2007).</p> <p> Jennings (2007) characterized turbulence as a loss of control due to simultaneous demands; difficult, or unfamiliar work; heavy patient loads; and excessive responsibility.<sup> </sup> Turbulence attributes clustered into two themes: communication and workload. Unique stressors, exclusive to our conceptualization of turbulence were those items that grouped primarily under nursing communication: breakdowns, distractions, interruptions, loss of information during handoffs, cognitive stacking and impaired decision-making. (Salyer, 1995; Patterson & Wears, 2010; Rivera-Rodriguez & Karsh, 2010; Coiera, 2012; Hopkinson & Jennings, 2013; Park, Blegen, Spetz, Chapman & DeGroot, 2013).</p> <p> <strong>Methods:</strong></p> <p>This mixed methods study was conducted in collaboration with The American Association of Critical Care Nurses (AACN) and approved by The University of Texas Health Science Center IRB. <strong> </strong>A 15 item turbulence scale was developed from the literature and tested in a mixed methods dissertation pilot with our local chapter of AACN. Clinical experts in critical care helped determine content validity. Reliability was tested using an interrater approach with critical care nurse raters scoring unique workload and turbulence components</p> <p>The turbulence items were then administered as part of a national survey interested in assessment of a Health Information Technology Workaround Model. A voluntary survey was sent to all members of AACN. Respondents were asked if any of the 15 listed activities were present or impacted work on their unit during their workaround experience. Responses were on a Yes (1)/ No (0) scale. Workload was measured using acuity, staffing ratio, and the nurse’s perception of their workload (light, moderate and heavy).</p> <p> <strong>Results:</strong></p> <p>A sample of 307 AACN RN members responded to an email survey consisting of items measuring nurse characteristics, workload, turbulence/ problems and patient safety risk (or event) and workarounds. Open ended questions solicited narrative descriptions of the problems, work activities and workarounds encountered or performed by the nurses. The respondents were 87% female, and the majority were 45 years old or greater. Almost 50% of the nurses had a bachelor’s degree in nursing, and 20.6% an associate degree. Nurse experience was midway between proficient and expert. Intensive care specialties included adult, pediatric and neonatal. Patient acuity was reported as: 61.8% critical, 28.7% guarded. Workload of the nurse was reported as heavy (40%) and moderate (58%).</p> <p> </p> <p> The distribution characteristics for the turbulence items will be presented. Sudden changes in acuity, interruptions and distractions were reported by more than half of the respondents. Other frequently selected turbulence items included administrative demands, communication breakdowns, information overload, noise, transfers in and out of the unit and staff having to leave the unit. Triangulation methods resulted in inter-method agreement of all 15 of the turbulence characteristics. There were no outliers or additional attributes identified.</p> <p> </p> <p>The minimum amount of data for factor analysis was satisfied with a final sample size of 296 (> 12 cases per variable). Using completed study data, consistency for the total scale indicated a Cronbach’s alpha of .75 (p<.01). The Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy was .77, above the recommended value of .6, therefore exploratory factor analysis of the 15 items was examined. Based on principal component extraction with varimax rotation, the five factor solution obtained had Eigen values greater than one and factor loadings ranging from .53 to .82. The 5 factors explained 54% of the variance. The criteria for the factor solutions are consistent with conventional statistical recommendations (Polit & Beck, 2008). Based on the analysis, the definition of turbulence offered by this work is: The degree to which the interaction between a nurse and attention diversion, resource inadequacy, communication breakdowns, sudden acuity increases and interpersonal relationships affects the nurses’ ability to practice or provide care.</p> <p><strong>Conclusion: </strong></p> <p>Initial testing of a turbulence measure demonstrated reliability and validity and produced a preliminary definition based on essential attributes. Hyun, Bakken, Douglas and Stone (2008, p.8) state “staffing decisions that lack consideration of all relevant factors may result in poor patient outcomes”. <sup> </sup>Workload, although widely used, does not tell the entire story and underestimates the totality of nurses’ tasks and responsibilities. When considering workload and turbulence, a broader understanding of nurse activities might provide us with alternative solutions beyond “staffing”. For example, workload (i.e., acuity, admissions and discharges) might be difficult to manipulate, but turbulence items, such as interruptions, loss of information, communication breakdowns and inadequate resources can be intervened upon. In the primary study we found that turbulence was most strongly correlated with safety hazards (<em>r </em>= .41, N= 293, p= .000) whereas the association between workload and safety hazards (<em>r </em>= .16, N= 29, p= .005) had the weakest relationship. The findings of this research will be presented and suggest that interventions aimed at turbulence reduction should result in better clinical outcomes and a reduction in safety risk.</p>en
dc.subjectPatient Safetyen
dc.subjectTurbulenceen
dc.subjectWorkloaden
dc.date.available2017-07-13T16:36:02Z-
dc.date.issued2017-07-13-
dc.date.accessioned2017-07-13T16:36:02Z-
dc.conference.date2017en
dc.conference.name28th International Nursing Research Congressen
dc.conference.hostSigma Theta Tau Internationalen
dc.conference.locationDublin, Irelanden
dc.descriptionEvent Theme: Influencing Global Health Through the Advancement of Nursing Scholarshipen
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