Agility poet study: agility, patient outcomes, and environmental turbulence in acute care nursing practice settings, The

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(1)THE AGILITY POET STUDY: AGILITY, PATIENT OUTCOMES, AND ENVIRONMENTAL TURBULENCE IN ACUTE CARE NURSING PRACTICE SETTINGS by KARA ADAMS SNYDER BSN, University of Arizona, 1995 MS, University of Maryland at Baltimore, 2001. A thesis submitted to the faculty of the Graduate School of the University of Colorado Denver in partial fulfillment of the requirements for the degree of Doctor of Philosophy College of Nursing 2019.

(2) ii. This thesis for the Doctor of Philosophy degree by Kara Adams Snyder has been approved for the College of Nursing by. Joyce Verran, Chair John Welton, Advisor MaryBeth Makic Barbara Brewer. Date: May 17, 2019.

(3) iii Snyder, Kara Adams (Ph.D., College of Nursing) The Agility POET Study: Agility, Patient Outcomes, and Environmental Turbulence in Acute Care Nursing Practice Settings Thesis directed by Professor John Welton ABSTRACT The nursing environment has been cited as a pivotal organizational factor in safety and quality and yet the practice environment is described as turbulent, in a state of unrest, disturbance, agitation or commotion. Environmental turbulence (ET) is defined as an unstable and rapidly changing environment. In this environment, nurses are trying to meet and exceed safety standards and provide care to increasingly complex patients, despite resource scarcity and in the face of increasing interruptions and distractions. Given these circumstances, not surprisingly, ET has been negatively associated with outcomes. It is posited that agility is an organization-wide capability to cope flexibly with this type of unexpected change in order to survive unprecedented threats in the environment. Change is the antecedent for agile behaviors. Workforce agility (WFA) is an agility-oriented mindset of employees combined with proactive, adaptive, and generative behaviors they understand and embrace the essentiality of organizational agility. With changes in healthcare expected to persist and turbulence a new normal in nursing practice environments, developing agile behaviors in the workforce could indeed be the logical next step in administrative nursing practices. Thus far, agility in healthcare organizations has only been editorialized as a necessary characteristic to thrive in the future. The primary purpose of the Agility-Patient Outcomes and Environmental Turbulence (Agility POET) study was to test the propositions of the Agility POET framework in a.

(4) iv Nursing context. The study aimed to evaluate the relationship between agility, environmental turbulence and nursing team and patient satisfaction outcomes. It was the central hypothesis of this study that WFA would mediate the negative relationship between ET and outcomes, as measured by nursing team job satisfaction and patient satisfaction with nurse communication. As a prerequisite to examining the aforementioned relationships, this study aimed to test the individual and group-level psychometric properties of survey instruments (ET Composite Scale, Workforce agility scale, and nurse job satisfaction scale) in acute care hospital-based nurses and nursing units, respectively. This cross-sectional, exploratory study was conducted within a single, 28-hospital health system in the Western United States. Hospital-based nursing team members in six acute care facilities were surveyed using study instruments. Measures were aggregated at the unit level for analysis with unit-based outcomes. There were 16 units enrolled (29.1% enrollment rate), yielding a power of 41.7%. The psychometric properties of the ET Composite Scale and Nurse Job Satisfaction Scale were adequate for hypothesis testing, though the Workforce agility scale is a poor measure of nursing workgroups. The ET Composite Scale was identified as a two-factor structure, ETInternal and ET-External, which is consistent with the theoretical foundations of the concept. ET was found to have a negative relationship with job satisfaction (β=-0.677, p=.004) but not patient satisfaction with nurse communication (β=0.017, p=.957). WFA was neither a mediator nor moderator in the relationship between ET and outcomes. The study must be interpreted with the limits of sample size and WFA instrumentation. Future research on WFA is needed to clarify the concept in nursing. The form and content of this abstract are approved. I recommend its publication. Approved: John Welton.

(5) v DEDICATION To my daughter, Lauren, who has been my reminder each day of the beauty of love, the importance of being in the present moment, and the endurance of stick-to-itiveness. May God bless and keep you always May your wishes all come true May you always do for others And let others do for you May you build a ladder to the stars And climb on every rung May you stay forever young May you grow up to be righteous May you grow up to be true May you always know the truth And see the lights surrounding you May you always be courageous Stand upright and be strong May you stay forever young May your hands always be busy May your feet always be swift May you have a strong foundation When the winds of changes shift May your heart always be joyful May your song always be sung May you stay forever young - Bob Dylan.

(6) vi ACKNOWLEDGEMENTS As I have come to learn in Healthcare Systems Research, context is everything! I’m grateful for the village of scholars, friends, family members and colleagues who have provided the context in this adventure! I wish to thank my committee chair, Dr. Joyce Verran, for sharing her time and wisdom with me over the years and in particular, in the course of this work. My advisor, Dr. John Welton and committee members, Drs. Mary Beth Flynn Makic and Barbara Brewer, for their commitment to my learning and their perspectives that have shaped my thinking about nursing science for years to come. To Dr. Paula Meek who shared with me the need for endurance, the glasses to see things in new (and fashionable) ways, and the practical and exciting aspects of statistics. To Dr. Karen Johnson, who has been an advisor to me throughout my entire nursing career and encouraged my learning every step of the way. To Dr. Patricia Morton, who planted the seed a decade ago that doctoral education was possible and convinced me (over popcorn snacks) that it should be pursued. I wish to thank my husband for his unwavering support and encouragement. He is the consummate editor, listener to all of my crazy ideas, and cheerleader. I would like to thank my darling daughter, Lauren, for helping at every turn; and my parents and family, who have encouraged me to dream big and go for it all, yet to always remember to stop and smell the roses. I wish to thank my dear friends - Kolby, Lindsay, Jamie, Martha, and all my “junior high friends” - who have known exactly when I’ve needed a break to laugh. Many thanks to Lori Throne and Cathy Townsend, my leaders and mentors, who have helped facilitate my growth and learning as a nurse leader and supported me in this academic achievement..

(7) vii I dedicate this work to my patients, their families, and nurse, physician, and allied healthcare colleagues who keep me focused and grounded in the work we have ahead to revolutionize healthcare. This study has been approved by the Colorado Multiple Institutional Review Board, Approval #17-1692..

(8) viii TABLE OF CONTENTS CHAPTER I. INTRODUCTION ............................................................................................................. 15 Problem Statement............................................................................................................ 17 Significance ........................................................................................................................ 19 Purpose............................................................................................................................... 20 Specific Aims, Research Questions, and Hypotheses..................................................... 21 Background ....................................................................................................................... 22 Environmental Turbulence.............................................................................................. 22 Workforce Agility ........................................................................................................... 25 Individual Attributes ....................................................................................................... 28 Outcomes ........................................................................................................................ 30 Summary............................................................................................................................ 35 II. LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK ............................ 37 Environmental Turbulence .............................................................................................. 37 Workforce Agility ............................................................................................................. 39 Individual Attributes ........................................................................................................ 41 Years of Experience and Education ................................................................................ 41 Resilience ........................................................................................................................ 41 Outcomes ........................................................................................................................... 41 Nursing Team Job Satisfaction ....................................................................................... 42 Patient Satisfaction with Nurse Communication ............................................................ 42 Falls ................................................................................................................................. 43.

(9) ix Medication Errors ........................................................................................................... 43 Theoretical Framework .................................................................................................... 44 Theory of Human Work Organization ............................................................................ 44 Theory of Stress and Human Health ............................................................................... 46 Agility POET Theoretical Framework............................................................................ 47 Summary............................................................................................................................ 49 III. METHODS ..................................................................................................................... 51 Design ................................................................................................................................. 51 Setting and Sample ........................................................................................................... 51 Setting ............................................................................................................................. 51 Sample Size..................................................................................................................... 52 Study Population ............................................................................................................. 52 Recruitment ..................................................................................................................... 53 Data Sources and Collection Procedures ........................................................................ 54 Measures and Instruments............................................................................................... 56 Demographics ................................................................................................................. 56 Workforce Agility Scale ................................................................................................. 59 Job Satisfaction ............................................................................................................... 62 Patient Satisfaction with Nurse Communication ............................................................ 62 Analysis .............................................................................................................................. 63 Psychometric Properties.................................................................................................. 64 Inferential Statistics ........................................................................................................ 66 Human Subjects ................................................................................................................ 68.

(10) x Summary............................................................................................................................ 68 IV. RESULTS ........................................................................................................................ 71 Study Population ............................................................................................................... 71 Data Collection .................................................................................................................. 71 Timeline .......................................................................................................................... 72 Recruitment ..................................................................................................................... 72 Sample............................................................................................................................. 73 Data Preparation.............................................................................................................. 75 Demographics ................................................................................................................. 76 Research Question 1: Psychometric Properties ............................................................. 76 Descriptive Statistics....................................................................................................... 76 Reliability........................................................................................................................ 78 Validity ........................................................................................................................... 80 Workforce Agility Scale ................................................................................................. 84 Job Satisfaction ............................................................................................................... 85 Patient Satisfaction with Nurse Communication ............................................................ 86 Research Question 2: Model Testing............................................................................... 86 Mediation Results ........................................................................................................... 87 Moderation Results ......................................................................................................... 91 Summary............................................................................................................................ 91 V. DISCUSSION AND LIMITATIONS ............................................................................. 95 Findings Related to Psychometric Properties of Survey Instruments ......................... 95 Environmental Turbulence Psychometric Properties...................................................... 95.

(11) xi Workforce Agility Scale Psychometric Properties ......................................................... 96 Psychometric Properties of Patient Satisfaction with RN Communication and Job Satisfaction Scale ............................................................................................................ 97 Findings Related to Hypothesized Relationships ........................................................... 98 Environmental Turbulence and Outcomes...................................................................... 98 Workforce Agility as Mediator or Moderator ................................................................. 99 Discussion .......................................................................................................................... 99 Limitations ...................................................................................................................... 99 Recommendations for Future Research ........................................................................ 100 Conclusion ....................................................................................................................... 101 REFERENCES.................................................................................................................... 102.

(12) xii LIST OF TABLES TABLE Table 1. Definitions of Core Study Concepts ......................................................................... 44 Table 2. Individual and Group-Level Inclusion and Exclusion Criteria ................................. 53 Table 3. Summary of Instrument Psychometric Properties .................................................... 57 Table 4. Statistical Tests Applied to Research Study Questions ............................................ 69 Table 5. Organizational Characteristics .................................................................................. 74 Table 6. Demographics of Enrolled Units (n=16) .................................................................. 77 Table 7. Descriptive Statistics of Scales and Sub-Scales ....................................................... 78 Table 8. Analysis of Variance (ANOVA) for Job Satisfaction and Environmental Turbulence and Workforce Agility Sub-Scales in Enrolled Nursing Units ............................................... 79 Table 9. Individual Level Reliability Statistics....................................................................... 79 Table 10. Group Level Reliability: ICC(2)* and rwg(J)............................................................. 80 Table 12. Three Composite Measures of Environmental Turbulence .................................... 84 Table 13. Exploratory Factor Analysis of Patient Satisfaction with Nurse Communication . 86 Table 14. Descriptive Statistics of Model Variables .............................................................. 87 Table 15. Pearson Correlations of Environmental Turbulence and Workforce Agility ......... 87 Table 16. Workforce Agility as a Mediator of Environmental Turbulence and Outcomes .... 89 Table 17. Workforce Agility as Moderator of Environmental Turbulence and Outcomes .... 94.

(13) xiii LIST OF FIGURES FIGURE Figure 1. Conceptual Framework of Agility, Patient Outcomes, and Environmental Turbulence (Agility POET) .................................................................................................... 16 Figure 2. Research Study Model of Workforce Agility as a Mediator / Moderator of Environmental Turbulence and Outcomes of Patient Satisfaction with RN Communication and Job Satisfaction ................................................................................................................ 17 Figure 3. The Human Work Organization Theory.................................................................. 45 Figure 4. Theory of Stress and Human Health ....................................................................... 47 Figure 5. Agility POET Research Study Framework: Mediator and Moderator .................... 49 Figure 6. Mediator Model with Path Equations ...................................................................... 88 Figure 7. Mediation Model of Environmental Turbulence 1, Workforce Agility, and Job and Patient Satisfaction.................................................................................................................. 89 Figure 8. Moderator Model with Path Equations.................................................................... 90 Figure 9. Moderation Model of Environmental Turbulence-1, Workforce Agility, and Job and Patient Satisfaction.................................................................................................................. 91.

(14) xiv LIST OF APPENDICES Appendix A: Invitation to Participate ................................................................................... 119 Appendix B: Staff Survey ..................................................................................................... 120 Appendix C: Colorado Multiple Institutional Review Board Approvals ............................. 128 Appendix D: WFA Proactivity Item Means ......................................................................... 131 Appendix E: Analysis of Variance of Workforce Agility Scale Items ................................. 132.

(15) CHAPTER I INTRODUCTION Turmoil and change are pervasive within the healthcare system, contributing to a state of chaos, instability, and perceptions among nurses of uncertainty, a state which characterizes environmental turbulence (ET) (Jennings, 2008). ET is expected to persist and likely cannot be fully eliminated from the nurse practice environment (NPE) (Jennings, 2008; Salyer, 1995). ET has been shown to have negative relationships with nurse performance and job satisfaction yet there remains a paucity of evidence examining ways to mitigate turbulence (Geddes, Salyer, & Mark, 1999; Pape, 2003; Salyer, 1995; Tillman, Salyer, Corley, & Mark, 1997). Agility is posited to be an organization-wide capability to cope flexibly with unexpected change in order to survive unprecedented threats in the environment (Breu, Hemingway, Strathern, & Bridger, 2002). Change, in fact, is the antecedent for agile behaviors in the workgroup (Breu et al., 2002). Agility in healthcare organizations has, to this point, only been editorialized as a necessary characteristic to thrive in the future (Garrett & McDaniel, 2001; Tillman et al., 1997). ET and agility come together conceptually in states of unpredictable change: where dynamic change is characteristic of ET, agile behaviors can manifest those changes for the betterment of the organization. Whereas ET and nurse outcomes have demonstrated a negative relationship, there are limited data examining the relationship between ET and patient outcomes. There is currently no healthcare or nursing literature that empirically evaluates agility in nursing or its relationships with environmental turbulence and outcomes. A conceptual framework was developed to propose relationships among Agility, Patient Outcomes, and Environmental Turbulence (Agility POET) as well as individual nurse attributes (Figure 1). The primary purpose of this study is to test a portion of the Agility POET framework in an acute care nursing context that examines the.

(16) 16 position of Workforce agility (WFA) (Figure 2). Specifically, the aim of this study was to analyze the relationships among WFA, ET, and outcomes of nursing team job satisfaction (JS) and patient satisfaction with nurse communication (PS-RN Com) in acute care nursing units. It was the central hypothesis of this study that WFA would be a partial mediator of the relationship between ET and outcomes. Data from this study are intended to describe the current state and therefore guide future research on NPEs and workforce characteristics.. Figure 1. Conceptual Framework of Agility, Patient Outcomes, and Environmental Turbulence (Agility POET).

(17) 17. Figure 2. Research Study Model of Workforce Agility as a Mediator / Moderator of Environmental Turbulence and Outcomes of Patient Satisfaction with RN Communication and Job Satisfaction Problem Statement The NPE has been shown to have a significant effect on patient outcomes, such as mortality and length of stay (Aiken, Clarke, Sloane, Lake, & Cheney, 2008; Flynn, Liang, Dickson, & Aiken, 2010; Kutney-Lee, Wu, Sloane, & Aiken, 2013; Silber et al., 2016). The NPE has been cited as a pivotal organizational factor in safety and quality and yet it is described as turbulent (Jennings, 2008; L. Lin & Liang, 2007). ET has been defined as an unstable and rapidly changing environment in nursing units (Salyer, 1995). The cumulative exposure of ET yields a chronic condition in the NPE that disrupts the homeostasis of the nursing unit with poor.

(18) 18 outcomes, such as increased nurse burnout and poor nurse communication (Garrett & McDaniel, 2001; Salyer, 1995). While much work has been done to understand the NPE, complexity theory suggests that turbulence cannot be avoided (McDaniel, Jordan, & Fleeman, 2003), and yet the effect of ET is intolerable for patient quality, patient safety, and nurse outcomes. In fact, Effken et al. (2005) emphasized that decreasing workload, unit turbulence, and nursing culture yielded the most likely changes to improving patient safety and quality outcomes. Using computational modeling of virtual and acute care nursing units, Effken et al. (2005) concluded that turbulence could not be fully eliminated. If outcome improvement is to be realized insofar as ET is concerned, strategies to mitigate its effect are warranted. Turbulent environments have provided some organizations the stimulus to exploit change for the betterment of the organization (Alavi, Abd. Wahab, Muhamad, & Arbab Shirani, 2014; Alavi & Wahab, 2013). Commonly, healthcare organizations are not able to respond quickly enough to cope with the pace of change (Breu et al., 2002; Shirey, 2015). Maneuverability in time of phenomenal change is key. Where ET is characterized as both external and internal sources of change, uncertainty, and unpredictability, an agile workforce demonstrates proactive, adaptive, and resilient behaviors to sense and respond to that change and unpredictability (Alavi & Wahab, 2013; Salyer, 1995). Constructs of an agile workforce include proactive, adaptable, and resilient behaviors in workers who sense and anticipate change and seize opportunities for the betterment of the organization. Studies in business, manufacturing and industrial engineering examining the effect of agility have demonstrated improved customer-perceived value, improved organizational performance, and superior environmental responsiveness (Breu et al., 2002; Nejatian & Zarei, 2013; Sherehiy & Karwowski, 2014). Thus far, agility in healthcare organizations has been only.

(19) 19 editorialized as a necessary characteristic to thrive in the future, though an agile workforce holds promise for mitigating threats to outcomes, such as a turbulent NPE (Garrett & McDaniel, 2001; Tillman et al., 1997). There is not currently any healthcare or nursing literature that empirically evaluates agility in nursing or its relationship with environmental turbulence and outcomes. Significance Health expenditures in the United States have risen to $2.9 trillion and 32% of those dollars are going to hospital-based care ("HHS Strategic Plan," 2015). Unsafe care is attributable to nearly 100,000 deaths and $100 billion annually in the United States and unfortunately the five-year evaluation of the impact of the seminal Institute of Medicine’s report, To Err is Human, demonstrated that healthcare is only mildly safer (Kohn, Corrigan, & Donaldson, 2000; Leape & Berwick, 2005). Despite projects in the wake of “pay-for-performance” and public reporting, health care professionals continue to struggle with creating a highly reliable and safe health care experience for patients (Berwick, Nolan, & Whittington, 2008). Suffice it to say, the human and financial cost of unsafe care is untenable, requiring a multidisciplinary, multilevel approach to make strides in making safer care (IOM, 2011). Developing the nursing workforce and improving the nursing practice environment have the potential to improve healthcare quality and safety (Hoff, Jameson, Hannan, & Flink, 2004). Another report from the Institute of Medicine was conducted in response to the IOM’s report To Err is Human (Kohn et al., 2000), characterizing the typical practice environment for nurses as having many serious threats to patient safety (Page, 2004). Similarly, Hall, Doran, and Pink (2008) emphasized that higher perceptions of the work environment existed following work place redesign with the involvement of direct care nurses. Boyle (2004) found that nursing units with high scores of autonomy, collaboration, support or practice control had improved safety..

(20) 20 Kramer, Maguire, and Brewer (2011) confirmed that nurses’ ratings of quality of patient care correlated with the quality of the work environment. Taken together, the autonomous, collaborative role of the nurse improves the practice environment, which facilitates improved outcomes for patients, signaling perhaps a need for a more agile workforce. The Institute of Medicine’s Future of Nursing report calls upon nurses to be full partners in redesigning health care in the United States, taking full responsibility for identifying and solving problems that keep outcomes from being fully realized (IOM, 2011). Nurses are trying to meet and exceed safety standards and provide care to increasingly complex patients, despite resource scarcity and in the face of more interruptions and distractions, all the while in a healthcare context filled with change (Jennings, 2008; Pape, 2003; Tillman, Salyer, Corley, & Mark, 1997). In an era of mergers and acquisitions and rapidly shifting healthcare policies and patient population characteristics, more research is needed to help mitigate the effects that ET has on outcomes. The Agility POET study is the first study to examine the relationships among WFA, ET, JS, and PS-RN Com. Purpose The purpose of this study was to examine a portion of the Agility POET conceptual framework (Figure 1) and specifically examining the relationships among ET, WFA, and outcomes of JS and PS-RN Com in acute care nursing units (Figure 2). Fundamental to examining these propositions and a prerequisite to theory testing, was the evaluation of the individual and group-level psychometric properties of survey instruments used to measure the phenomena of interest. Thus, individual and group-level psychometric properties of study instruments were analyzed. The findings of this study were intended to help inform future.

(21) 21 research of the effect of ET in acute care nursing units on patient quality and safety outcomes and begin to address the lack of empirical literature on WFA in acute care nursing units. Specific Aims, Research Questions, and Hypotheses Aim 1:. Test the individual and group-level psychometric properties of survey instruments (ET Composite Scale, Workforce Agility Scale, and Nurse Job Satisfaction Scale) in acute care hospital-based nurses and nursing units, respectively. RQ1:. What is the individual and group-level reliability and validity of survey instruments used in the Agility POET study, including ET Composite Scale, Workforce Agility Scale, and Nurse Job Satisfaction Scale? H1a:. The ET Composite Scale, Workforce Agility Scale, and Nurse Job Satisfaction Scale will demonstrate reliability at the individual level, as measured by Cronbach’s alpha, and at the group level, as measured by the Intraclass Coefficient (2) and rwg(J).. H1b:. The Workforce Agility Scale will demonstrate construct validity as a two-factor structure as examined with exploratory factor analysis.. Aim 2:. Test the propositions within the model of agility, patient outcomes (patient satisfaction with nurse communication), nursing team job satisfaction and environmental turbulence (Agility POET) RQ2a:. What is the relationship between ET, as measured by the ET composite scale, and outcomes, as measured by unit-level nursing team job.

(22) 22 satisfaction and patient satisfaction with RN communication in acute care nursing units? H2a-1:. There will be a negative relationship between ET and nursing team job satisfaction.. H2a-2:. There will be a negative relationship between ET and patient satisfaction with RN communication.. RQ2b:. What is the relationship between ET and WFA in acute care nursing units? H2b:. There will be a positive relationship between ET and WFA in acute care nursing units. RQ2c:. Does WFA, as measured by the Workforce Agility Scale, mediate or moderate the relationship between ET and outcomes in acute care nursing units? H2c:. WFA will be a partial mediator of the relationship between ET and outcomes in acute care nursing units. Background. Environmental Turbulence Both internal and external sources of turbulence are at play in the NPE (Jennings, 2008). As open systems, it is plausible, if not expected, that change in the external environment affects the natural homeostasis of the internal nursing practice environment (Geddes et al., 1999; Salyer, 1996). External sources of ET include a hospital’s hectic conditions, rapid growth of large healthcare organizations, changing health policies, and shifts in the characteristics of the patient population (Jennings, 2008). Given these circumstances, not surprisingly, ET has been negatively associated with quality and safety outcomes (Begun & Kaissi, 2004; Bosco, 2007;.

(23) 23 Breu, Hemingway, Strathern, & Bridger, 2002; Salyer, 1995). As healthcare organizations deal with changes in the external environment (turbulence), uncertainty in the internal environment is created (Garrett & McDaniel, 2001). Thus, perceived environmental uncertainty (PEU) is the individual psychological reaction to ET (Salyer, 1995). Salyer (1995) described the effect of environmental turbulence on individual nurses’ job performance. The researcher examined propositions from the theory of stress and human health across the four stages in the theoretical framework: 1) environmental turbulence as the potential stressor, as measured by day-to-day change in patient acuity, day-to-day change in unit occupancy, and number of admissions to, discharges from, and transfers on/off a unit in a 24hour period; 2) perceived environmental uncertainty as the psychological reaction, as measured by the perceived environmental uncertainty scale; 3) hardiness, ambiguity, and quality of support system as the potential mediators, and finally; 4) nurse performance as the behavioral consequence (Salyer, 1995). Salyer (1995) found that the number of admissions and discharges had a direct negative relationship with PEU (β=-.454, p<.0001) and nurse-patient interpersonal relationships and communication skills (β=-.272, p<.01). Through PEU, an indirect negative relationship is calculated with ET and technical skill performance (β=-.139) and implementation of the nursing process (β=-.345), indicating that the product of both the environment itself as a stressor and the nurses’ psychological reaction to the environment had a negative relationship with nursing behaviors (Salyer, 1995). Tolerance of ambiguity appeared to mediate the relationship between ET and interpersonal relationships and communication (β=-.187, direct path β=-.272, Δ=0.085), suggesting that the ability of nurses to perceive the uncertainty and tolerate ambiguity in the environment buffered some of the negative impact that a turbulent environment had on outcomes (Salyer, 1995)..

(24) 24 Garrett and McDaniel (2001) also used the theory of stress and human health to examine relationships of environmental uncertainty (potential stressor), social climate (psychological reaction), nurses’ personal characteristics (mediators), and burnout (consequences) among staff nurses. Environmental uncertainty was measured as the daily sum total of admissions, discharges, and transfers in and out of a unit divided by the midnight census, and finally dividing by 31, thus creating a daily activity score per day for each unit (Garrett & McDaniel, 2001; Tillman et al., 1997). PEU predicted all three components of burnout as measured by the Maslach Burnout Inventory, including emotional exhaustion (β=0.35, p<0.01), depersonalization (β=0.26, p<0.01), and personal accomplishment (β=-0.23, p<0.04) (Garrett & McDaniel, 2001). The three constructs of social climate suggested supportive workplaces to be protective against burnout, specifically that involvement and supervisor support had a negative relationship with emotional exhaustion (β=-0.31, p=.02, β=.33, p<0.01, respectively) and depersonalization (β=0.60, p<0.01, β=0.25, p=0.04, respectively) (Garrett & McDaniel, 2001). Using phenomenologic inquiry, Tillman et al. (1997) described that staff nurses amidst turbulent practice environments experienced ineffective buffering of disruptive forces in the environment and poor control over nursing practice. Ultimately, the authors suggested the important role of nursing administrators in proactively engaging and communicating directly with staff on the positive advocacy work being done on a systems level to mitigate turbulence (Tillman et al., 1997). Theory generative work by nature of the qualitative design, the level of analysis, similar to other aforementioned studies, remained at the individual nurse level and did not examine turbulence as a group-level phenomenon. In a study of the relationship between organizational, unit, and patient characteristics and measured at the group level, turbulence in the environment was found to have significant effects.

(25) 25 on medication errors (β=0.42), falls without injury (β=0.32), symptom management (β=-0.31), and likeliness to recommend to others (β=-0.37) (J. A. Verran, Lamb, Effken, Brewer, & Shea, 2004), suggesting the persistent negative outcomes associated with ET when measured as a unitlevel phenomena. Characterized as an unstable and rapidly changing environment, Salyer (1995) posited that the environmental turbulence is expected to persist. The results of the research by Salyer (1995) and Garrett and McDaniel (2001) provide insight into the measurement and consequences of ET and PEU. Both Salyer (1995) and Garrett and McDaniel (2001) showed the mediating effect of personal or team characteristics on outcomes, yet neither provided an analysis of an organizational-level approach to mitigating the effect of ET and PEU on outcomes. Both studies examined the phenomena at the individual level of analysis. The group-level study by Verran and colleagues (2004) showed similar consequences of ET when measured as a nursing unit phenomena, but it is unclear how to mitigate the effect of ET in nursing units. Workforce Agility Business leaders are required to continuously anticipate and adjust to deep secular trends to flourish and have the capacity to change before the case for change is desperately obvious. Agility is an organization-wide capability to cope flexibly with unexpected change in order to survive unprecedented threats from the business environment. Change is the antecedent for agile behaviors. Actively taking advantage of opportunities and positively countering competitive threats that arise from frequent, and sometimes large and unpredictable changes or a turbulent work environment typify agile behaviors. Agility was coined as a phrase in the 1950s as the ability of an aircraft to maneuver quickly (Breu et al., 2002). Since then, the research on agility has been applied to a number of.

(26) 26 agility sub-types, including movement and athletic performance, learning agility, software (information technology) agility, supply chain agility, organizational agility and Workforce agility. To appreciate the nature of WFA, a description of the different agility sub-types is provided. Agility in athletic performance has been studied with key factors for improving agile performance being perceptual ability of the athlete, the ground covering, the athlete’s footwear, and the athlete’s ability to quickly respond (João et al., 2014; Jovanovic, Sporis, Omrcen, & Fiorentini, 2011; Sheppard & Young, 2006). Learning agility has been posited as a construct relating to the willingness to learn from experience and apply that learning in new conditions (De Meuse, Dai, & Hallenbeck, 2010). Agility in software development came into the literature following the publication of the “Manifesto for Agile Software Development” and is based upon the principles of individuals and interactions over processes and tools; working software over comprehensive documentation; customer collaboration over contract negotiation; and responding to change over following a plan (Beck et al., 2001). Studies since then have focused on the outcomes of an agile software development strategy across a variety of organizations with positive, negative and neutral results (Dingsøyr, Nerur, Balijepally, & Moe, 2012; Dybå & Dingsøyr, 2008). Interestingly, lack of concept development and theoretical foundation of agile software development were cited as causes for the variation in outcomes and also the focus of future research (Dingsøyr et al., 2012; Dybå & Dingsøyr, 2008). Supply chain agility is a natural response to a “just-in-time” delivery system for supplies, which favor delivery of supplies tailored to customer need (Swafford, Ghosh, & Murthy, 2006). Determinants of supply chain agility include four agility enablers: flexibility, responsiveness, competency and cost (Agarwal,.

(27) 27 Shankar, & Tiwari, 2007; C.-T. C. Lin, Hero; Chu, Po-Young, 2006; Samantra, Datta, Mishra, & Mahapatra, 2013). Organizational agility was introduced formally in manufacturing enterprises with the Iacocca Institute’s seminal publication describing agility as the 21st century manufacturing enterprise strategy (Nagel & Dove, 1991). This publication was the product of thought-leaders in the manufacturing industry that projected organizational agility as a key attribute for thriving in a competitive environment (Nagel & Dove, 1991). Through qualitative and quantitative analysis, Charbonnier-Voirin (2011) found proactivity of the organization as the capacity of scanning and innovation in the face of change. Arteta and Giachetti (2004) tested the link between complexity, ease of change, and agility, and suggested in the theoretical framework that change preceded agility in the context of complexity. In the information technology industry, Kassim and Zain (2004) describe four principles as drivers of agility, including enriching customers, mastering change, leveraging resources, and cooperating to compete. In testing the model, the authors found overall good model fit (CFI=0.92), a four factor solution for measuring agility (factor loadings > 0.6), and reliability of sub-scales (enriching customers, α= 0.7, mastering change, α =0.8, leveraging resources, α =0.89, and cooperate to compete, 0.75) (Kassim & Zain, 2004). McCann (2004) has described the term “sense-making” as it pertains to an organization’s ability to perceive, understand, and incorporate change. This early work gave way to a need for clarity of the concept and a more robust measure of agility across companies. Sherehiy, Karwowski, and Layer (2007) performed a concept analysis in manufacturing and industrial engineering literature and, similar to previous literature, described that agility is the organization’s ability to adjust to changes. Taken together, literature for organizational agility.

(28) 28 is pretty consistent that for agility to occur, changes in the forms of environmental turbulence, market forces or policy pressures, as examples, must be present. (Crocitto & Youssef, 2003; Jin & Deliang, 2014; Kassim & Zain, 2004; Khoshsima, 2003; Nejatian & Zarei, 2013; Nijssen & Paauwe, 2012; Sherehiy & Karwowski, 2014; Vinodh, Aravindraj, Pushkar, & Kishore, 2012; Worley & Lawler, 2010). The impact of leadership style on organizational agility was studied by de Oliveira, Valentina, and Possamai (2012). While change is still present for agility to occur, the authors found that leadership style influenced the agility of an organization and ultimately improved project performance (de Oliveira et al., 2012). Agility has also been studied as it pertains to WFA. Agile workforces are thought to capitalize on skills by proactively developing a skills base just ahead of need (Breu et al., 2002; Yusuf, Sarhadi, & Gunasekaran, 1999). Additionally, WFA has been considered in the context of cross-training where workers are placed in areas with the greatest needs (Gel, Hopp, & Van Oyen, 2007; Hopp & Van Oyen, 2004). Individual WFA is conceptualized as observable agile behaviors at work, and is not limited to a specific personality types or traits (Sherehiy & Karwowski, 2014). Individual Attributes Attributes of individual nurses included in the Agility POET theory include years of experience (in the nursing unit, in the hospital, or in the nursing profession), time since completion of highest degree, and resilience. Resilience. Resilience is considered the positive adjustment to adversity (McAllister, 2013). Rutter (1985) describes resilience as an individual characteristic, varying among individuals with context, time age, gender, cultural origin, and within an individual that’s subjected to different circumstances in life. Exploring resilience from a strength and wellbeing.

(29) 29 framework, resilience has been considered an individual attribute that may help nurses achieve and maintain professional self-efficacy and longevity in the workforce (McAllister, 2013). In a grounded theory examination of resilience in patients with low chances of survival but high quality of life, Denz-Penhey and Murdoch (2008) identified attributes of resilience, including internal locus of control, staying calm, sense of humor, optimism, ability to transcend, connectedness (i.e., to social, cultural, and physical environments), and generativity. In a national survey of intensive care nurses, Mealer, Jones, Newman, et al. (2012) found that higher levels of resilience (defined as Connor-Davidson Resilience Scale > 92) were associated with lower prevalence of posttraumatic stress disorder (8%, vs. 25%, p<0.001), fewer symptoms of anxiety (8%, vs. 21%, p=0.003), less depression (2%, vs. 14%, p<0.001), and lower rates of burnout syndrome in all three dimensions (61%, vs. 85%, p<0.001), suggesting a protective nature of resilience in individuals. Charney (2004) and Adams, Camarillo, Lewis, and McNish (2010) found that resilience could also be learned. Mealer, Jones, and Moss (2012) found in a qualitative analysis that positive support systems, attention to physical well being, and development of active coping facilitated development of resilience in nurses. The ConnorDavidson Resilience Scale has been used to measure resilience with a higher score indicating a higher score in individuals and has demonstrated reliability (α=0.89, ICC=0.87), convergent validity, and a five-factor structure for measurement in healthcare workers as well as the population at large (Connor & Davidson, 2003). Mealer et al. (2014) constructed an intervention to bolster resiliency in critical care nurses and found in a pilot study that an intervention was both feasible and helpful in reducing symptoms of posttraumatic stress disorder, though recognized the need for a larger randomized study and the importance of organizational factors in designing such a program..

(30) 30 Resilience has been examined as it applies to a larger organization, such as a healthcare system, specifically as it pertains to patient safety work, emphasizing the ability of organizations to monitor, adapt, and act on failures in patient safety situations (Carthey, De Leval, & Reason, 2001; Jeffcott, Ibrahim, & Cameron, 2009). Amidst financial turbulence, resilient organizations are thought to flourish (S. Thomas et al., 2013). While these aforementioned studies suggest resilience as a characteristic of organizations, there is no study suggesting resilience as a trait amongst individuals in a group that could be measured at a group level. Further exploration of the concept is necessary before examining resilience at a group level and therefore resilience is situated as an individual attribute in the theoretical framework (Figure 1). Outcomes Nurse job satisfaction. JS is considered to be the affective response someone has to their job (Lu, Barriball, Zhang, & While, 2012). Job satisfaction is defined loosely as the nursing team’s general opinion about the satisfaction with their position (Forbes & Taunton, 1994). Among the many positive predictors of JS are positive working conditions, nurse autonomy, and authentic leadership (Hayes, Bonner, & Pryor, 2010; Kutney-Lee et al., 2013; Lu et al., 2012; Van Bogaert, Meulemans, Clarke, Vermeyen, & Van de Heyning, 2009). What’s more, higher levels of nurse JS have been reported to increase intention to stay, decrease turnover, and improve quality and safety outcomes of patients (Castaneda & Scanlan, 2013; Choi & Boyle, 2013; Kutney-Lee et al., 2013; Lu et al., 2012; Van Bogaert et al., 2009). A JS scale was developed by Delaney and Huber (1996) as part of the Nursing Management Minimum Data Set to provide nurse leaders a veritable set of vital signs upon which management decisions could be made. Improvements in the nursing practice environment have been associated with lower rates of job dissatisfaction (Kutney-Lee et al., 2013). Kanai‐Pak, Aiken, Sloane, and Poghosyan.

(31) 31 (2008) indicated that the practice environment in terms of poorer staffing, weak relationships with support staff, poor communication and teamwork among staff, and inadequacy of resources had higher levels of burnout and job dissatisfaction and poorer quality of patient care. Higher levels of employee engagement have been shown to have higher levels of job satisfaction and WFA (Alavi & Wahab, 2013; Laschinger & Leiter, 2006; Muduli, 2013; Sumukadas & Sawhney, 2004). Patient satisfaction with nurse communication. Patient Satisfaction (PS) contributes to 30% of value-based purchasing reimbursements to hospitals. The Centers of Medicare and Medicaid Services (CMS) require hospitals to collect and report patient satisfaction as an indicator of quality. The entire PS survey has 11 domains, including communication with nurses, communication with doctors, responsiveness of hospital staff, pain management, communication about medicines, cleanliness of the environment, quietness of the environment, discharge information, care transition, hospital rating, and likelihood to recommend. PS is an overall quality of care measure, and, to that end, is predicted by many modifiable and non-modifiable factors. As a broad proxy for measuring hospital quality, PS has been shown to correlated with other important quality indices. In a study of PS and quality and efficiency outcomes, Tsai, Orav, and Jha (2015) discovered that facilities with higher PS had lower length of stay (7.1 days vs. 7.7 days, p<0.001), lower risk-adjusted perioperative mortality rates (3.1% vs. 3.6%, p<0.001), and lower risk-adjusted 30-day readmission rates (12.3% vs. 13.6%, p<0.001) as compared to the lower PS scoring facilities. Similarly, Kennedy, Tevis, and Kent (2014) found in a national study of University Healthsystem Consortium facilities that higher scores of likelihood to recommend was associated with a lower mortality index of all admissions (p<0.001). In a systematic review.

(32) 32 of 55 studies of the links between PS and clinical effectiveness and patient safety, Doyle, Lennox, and Bell (2013) found a consistent theme in all studies that supports the inclusion of patient experience as a central pillar of quality in healthcare. In a national study examining the predictors of PS, hospitals with the Magnet credential had higher rates of PS than non-Magnet facilities (Stimpfel, Sloane, McHugh, & Aiken, 2016). While specific initiatives have had demonstrable effects on PS, such as bedside shift report (Radtke, 2013), the nursing practice environment has been shown to significantly influence PS. In their cross-sectional study of nurse-report of missed nursing care and PS as measured by HCAHPS, Lake, Germack, and Viscardi (2016) found a negative relationship between missed nursing care planning and communication with likelihood to recommend the hospital (β=-2.57, 95% CI -3.65 to -1.49, p<0.001), nurse communication (β=-1.41, 95% CI -2.21 to -0.62, p<0.01), patient receiving help when they wanted it (β=-1.49, 95% CI -2.39 to -0.59, p<0.001), and, among other items, staff always explaining medication (β=-1.3, 95% CI -2.05 to -0.56, p<0.01). Similar findings were found for nurse-report for missed clinical care. Unfortunately, missed nursing care has also been correlated with other adverse events (Kalisch, Xie, & Dabney, 2014). Hessels, Flynn, Cimiotti, Cadmus, and Gershon (2015) analyzed nursing practice environment survey data in a single state and found a moderate to strong effect on missed nursing care in all five domains of the nursing practice environment survey (β = -0.47 to -0.77, p<.01). Taken together, a poor practice environment potentiates missed nursing care, which is negatively related to PS. Turbulence in the practice environment could be the mechanism by which the practice environment contributes to missed nursing care. Falls. Falls in the acute care setting remain one of the most common patient safety events, 30% of which result in injury to the patient (Choi & Boyle, 2013). Patient factors have.

(33) 33 been studied extensively and individual level interventions have been shown to reduce fall rates (Miake-Lye, Hempel, Ganz, & Shekelle, 2013). Team and organizational factors have also been shown to impact fall rates. Lake, Shang, Klaus, and Dunton (2010) reported that the fall rate was 5% lower in Magnet than non-Magnet hospitals and that nursing staffing mix and staffing levels were positively related to lower fall rates. Choi and Boyle (2013) found that higher levels of RN workgroup job satisfaction were associated with lower fall rates in a variety of nursing unit specialties. The percentage of nurses with a BSN or higher and higher RN years of experience has been shown to have a positive relationship with lower unit-level fall rates (Choi & Boyle, 2013). Job satisfaction has been shown to be a predictor of lower fall rates (Choi & Boyle, 2013). Falls have been described as a sensitive indicator of nursing quality (Lake et al., 2010). Medication errors. Rates of medication errors in the hospital inpatient setting have been reported between 4.8% and 5.3% (Wittich, Burkle, & Lanier, 2014). Rates of medication error are difficult to determine because only those discovered, whether near miss events or those that cause direct patient harm, are reported. In fact, one limitation of medication error as an outcome measurement for patients safety and quality is that it is generally based upon reported errors, unless prospective observation models are used to collect the information (Holmström, Laaksonen, & Airaksinen, 2015). Not all medication errors cause harm; in fact most do not. Bates, Boyle, Vander Vliet, Schneider, and Leape (1995) found that harm to patients from medication errors resulted in less than 1% of all medication errors. The hospital setting is the most common site for medication errors, as compared to outpatient, skilled nursing or other settings (American Society of Health-System, 1993). Hofmann and Mark (2006) examined a model of safety climate and medication errors, finding that job satisfaction found a predictive relationship between safety climate, job.

(34) 34 satisfaction, and medication errors, suggesting the interplay of the culture, staff satisfaction and adverse outcomes. Distractions and interruptions have been linked to increased medication errors (Brady, Malone, & Fleming, 2009; Pape, 2003; Westbrook, Woods, Rob, Dunsmuir, & Day, 2010). Duffield et al. (2011) found that unit complexity (churn, resource availability) resulted in untoward outcomes, such a higher incidents of medication errors. Other data suggest that amidst turbulence in the environment, a checklist or protocol may be able to focus the care to a few key elements (Gawande, 2010). Protocols to manage each individual component of care have been shown, nearly unequivocally, to improve outcomes (Pronovost et al., 2006). The airline industry has been explored as a parallel to healthcare for hospital safety. While useful in the application at the individual level, changes and disruptions are occurring all around the individual that can go unnoticed. In other words, it might be a comfortable position when we know the safety hazards, but what about the hazards we don’t know about? Qin and Nembhard (2010) posit agility as a competency that involves actively taking advantage of opportunities (i.e., safety hazards), which arise from frequent, and sometimes large and unpredictable changes. Research on the topic of organizational agility in manufacturing and industrial engineering, business, and information technology has exploded, with a crude estimate of over 25,000 GoogleScholar search results since 1991. Unfortunately, there is paucity of evidence in healthcare explicitly pertaining to organizational agility, its measurement, or the impact of organizational agility on patient outcomes. Organizational agility as an organizational characteristic in business and manufacturing has potential in healthcare for outcome improvement. Nursing knowledge is gained through clarification of the concept and elaborating our understanding of agility and how this concept may be studied in the context of healthcare as.

(35) 35 a potential characteristic of nurses (WFA) to improve the outcomes of patients, families, and communities. Breu et al. (2002) suggest that, in the context of information communication technology, businesses that acknowledge and even embrace environmental turbulence are compelled to become more agile organizations vis à vis employee behaviors. Shirey (2015) describes elements of key competencies for strategic agility for nursing leaders, though cites the need for nursing leaders to examine the experiences and outcomes of nimble business strategies. Nejatian and Zarei (2013), Nijssen and Paauwe (2012), Kassim and Zain (2004), and Worley and Lawler (2010) have all studied the positive effect of agility on organization-level outcomes, but have focused on the organization and not on the behaviors of the workers in groups. Sherehiy and Karwowski (2014) examined the relationship between WFA, an organization’s agile strategy, and work organization and discovered the organization’s agile strategy to be antecedent to WFA in small to medium sized manufacturing firms, though they did not study the effect that WFA would have on the outcomes for the organization. While intriguing, the findings of Sherehiy and Karwowski (2014) are generalizable only for manufacturing firms. What remains unknown is the effect of WFA in a nursing context. There has been no data examining the relationship between ET and WFA in a healthcare or Nnursing context. The Agility POET study will help to fill this gap and will examine the relationship WFA has with ET and patient outcomes. Summary The practice environment of nurses is a pivotal factor in patient quality and safety, and yet the environment is described as turbulent, where it is in a state of instability and rapid change. Turbulence in the practice environment has deleterious effects on patients and staff..

(36) 36 Furthermore, turbulence is expected to persist and cannot be fully eliminated. Strategies to mitigate the effect of turbulence are warranted. In fact, turbulence is in some industries an impetus for expression of agile behaviors in the workforce. An agile workforce has been described as proactive, adaptive, and resilient. Change is the antecedent of agility: without change, there can be no agile behaviors in the workforce. In a turbulent nursing practice environment, it’s plausible that agile behaviors exist, however, there are no data in healthcare or nursing describing the agility of the workforce. Ultimately, it was the goal of this study to test a portion of the Agility POET conceptual framework in effort to begin to understand the position of WFA in the relationship between ET and outcomes in an acute care nursing practice environment. It is hypothesized that an agile workforce will partially mediate the relationship between ET and outcomes..

(37) 37 CHAPTER II LITERATURE REVIEW AND CONCEPTUAL FRAMEWORK A literature review of the concepts in the conceptual framework is provided in the discussion that follows and Table 1 summarizes the definitions. Environmental Turbulence Environmental turbulence (ET) is defined as an unstable and rapidly changing environment (Jennings, 2008; Salyer, 1995). The concept of turbulence arose from aviation where it was used to describe wind current and patterns, with three main conditions that cause turbulence: convective currents, obstructions to wind flow, and wind shear (Bosco, 2007). All of these conditions can occur without warning and contribute to a “bumpy ride.” The ebb and flow of direct patient care (convective currents), the barriers to care (obstruction to wind flow), and changes in patient condition (wind shear) are just a few examples of how this term crosses over to the hospital environment (Bosco, 2007). External sources of ET include hospitals’ hectic conditions, rapid growth of large healthcare organizations, changing health policies, and shifts in the characteristics of the patient population (Jennings, 2008). Internal sources of ET may include unit-level changes, dynamism, and availability of resources (Brewer & Verran, 2013). Both internal and external sources of ET interact in open systems; thus, change in the external environment affects changes in the internal environment (Geddes et al., 1999; Salyer, 1996). Individuals can have a response to the turbulence in the environment. Salyer (1996) described this response as perceived environmental uncertainty (PEU). Laschinger and Leiter (2006) examined a model of the nursing practice environment and patient safety outcomes with the mediating role of burnout and engagement processes. The results suggested good model fit (χ2=16,557.35, df = 1,346, CFI = .907, IFI = .907, RMSEA = .037) that the nursing practice environment has a negative relationship with nurse-report of.

(38) 38 adverse events and that when nurses perceive a supportive practice environment, these outcomes improve. The patterns we might observe in nursing practicing in a turbulent practice environment can take different phenotypes. Interruptions during medication administration occur 67.1% of the time and made a significant difference in the perceived cognitive load of the nurse also increased for mental demand (𝑥=25, CI=19-31, p=.0024), effort (𝑥=28, CI=21-34, p=.0044), and frustration (𝑥=23, CI=16-30, p=.0010), compared to episodes of administration with no interruptions (L. Thomas, Donohue-Porter, & Stein Fishbein, 2017). Interruptions have been associated with higher rates of procedural failures (ß=0.41, SE, 0.08, p<.001) and clinical errors (ß=0.18, SE, 0.05, p<.001), outcomes that persisted as interruptions increased (Westbrook et al., 2010). Many stopgap approaches to improving medication errors have been reported. In an attempt to reduce interruptions, Pape and colleagues (2003) devised a protocol where nurses wore a special vest, which showed a significantly fewer number of distractions between groups (F(2,21)=68.229, p=.000) but were not fully eliminated for each medication administration (𝑥=8, SD=4.5). Nursing peer review to the medication error, implementation of bar code medication administration practices, or instituting a new policy or competency to shore up medication administration practices have also been reported and while successful to a certain degree, have not fully eliminated the problem (Hewitt, Tower, & Latimer, 2015; Kelly, Harrington, Matos, Turner, & Johnson, 2016). Missed nursing care has been associated with poor outcomes. Kalisch and colleagues sought to understand predictors of missed nursing care at an organizational level and found overall teamwork to be negatively correlated with missed nursing care (r=-.37, p<.001) (Kalisch, Tschannen, Lee, & Friese, 2011)..

(39) 39 Alternatively, we can observe the interactions within the environment, such as support service response times to the medication questions, accessibility issues with supplies for medication preparation, the distance from the patient room to the medication room, and the interruptions of patient requests that are met along the way (Brewer & Verran, 2013). When we seek to understand the context of practice, we can appreciate complexity systems (Jordon, Lanham, Anderson, & McDaniel, 2010; McDaniel et al., 2003). Workforce Agility Agility is rooted in aviation science where an agile aircraft is one that can maneuver quickly (Breu et al., 2002). Agility has been applied to a number of topics, including movement and athletic performance, learning agility, software (information technology) agility, supply chain agility, organizational agility, and WFA. Agile workforces are thought to capitalize on skills by proactively developing skills base just ahead of need (Breu et al., 2002; Yusuf et al., 1999). Some studies have conceptualized WFA as cross-training among different sub-specialties and demonstrated variable results (Gel et al., 2007; Hopp & Van Oyen, 2004; Iravani & Krishnamurthy, 2007). Dyer and Shafer (2003) speculated WFA as an agility-oriented mindset of employees that had proactive, adaptive and generative behaviors who understand and embrace the essentiality or organizational agility. More specifically, Dyer and Shafer (2003) posit proactive employees initiate and improvise, adaptive employees assume multiple roles (leader, minor team-player, individual contributor) and spontaneously collaborate with others, and generative employees simultaneously learn and educate. Breu et al. (2002) examined WFA in information communication technology firms and through exploratory and confirmatory factor analyses found that intelligence, competencies,.

(40) 40 collaboration, culture, and information systems were attributes of an agile workforce. In this study, intelligence (the collective environmental responsiveness of a workforce in terms of its ability to read and interpret external change and to adjust objectives accordingly) and competencies (acquisition of skills) were identified as the strongest determinants of WFA (Breu et al., 2002). Griffin and Hesketh (2003) described WFA as a latent variable with the constructs of proactivity, resiliency, and adaptability. Sherehiy and Karwowski (2014) included these constructs in the WAS with reliability (Cronbach’s Alpha) as 0.854, 0.867, and 0.711, for proactivity, resiliency, and adaptability, respectively. WFA has been shown to be consequential to an organization’s agile strategy, implying that the context of agility is relevant for the presence or absence of an agile workforce. Gunasekaran (1999) describes that a company that decides to be agile should be agile in all its parts, implying that WFA is not isolated to an individual. The operational definition of WFA for the Agility POET study is rooted in the aforementioned research by Sherehiy and Karwowski (2014). The authors studied the concept among employees of manufacturing and industrial firms, yet found that the organizational agility strategy of the firm had a positive relationship with the presence of an agile workforce (Sherehiy & Karwowski, 2014). The relationship between organization and WFA recognizes the importance of the group (or organizational) context for the presence (or absence) of WFA. Thus, the Agility POET derives WFA in nursing as group-level phenomena, where WFA is a characteristic of nursing team members in acute care nursing units. Resilience is one construct of WFA. Literature examining resilience in nursing has focused on the individual nurse, and not an attribute of the Nursing workgroup (Arfanis & Smith, 2012; D. Jackson, Firtko, & Edenborough, 2007; Mealer, Jones, Newman, et al., 2012)..

(41) 41 Resilience is included in the Agility POET framework as an individual attribute in the first stage of the model and items pertaining to resilience in the workforce agility scale are removed for the purpose of this study. Individual Attributes The first stage of the Agility POET framework includes individual attributes, namely years of experience and time since highest nursing degree. Years of Experience and Education The years of experience pertain to three specific time measurements: years of experience in the unit, hospital and nursing profession (Kanai‐Pak et al., 2008). Education time pertains to the years since completion of the highest degree (Effken et al., 2011). Resilience In a broad context, resilience is the ability to adapt to change and to recover quickly from stressors (Garcia-Dia, DiNapoli, Garcia-Ona, Jakubowski, & O'Flaherty, 2013). In a nursing context, resilience is thought of as the adaptability to an ever-changing healthcare landscape and ability to recover quickly from workplace stressors (Pipe et al., 2012). D. Jackson et al. (2007) found resilience to be a strategy for responding to workplace adversity, and specifically applied to building positive relationships, developing emotional insight and becoming more reflective in practice. Outcomes The Agility POET conceptual framework posits outcomes of ET and WFA in stage III of the framework. The outcomes of interest in the framework include Nursing Team Job Satisfaction, Patient satisfaction with RN communication (PS-RNCom), Unit Medication Error Rates, and Unit Patient Fall Rates..

(42) 42 Nursing Team Job Satisfaction Job satisfaction (JS) is considered to be the affective response someone has to their job (Lu et al., 2012). JS is defined loosely as the nursing team’s general opinion about the satisfaction with their position (Forbes & Taunton, 1994). Fung‐kam (1998) described that JS results from the comparison of perceived outcomes with those that are desired. There is not one standard conceptual or operational definition in the literature, but one characteristic prevails: JS is considered to be highly subjective and varies over time. Some operational definitions also include overall life satisfaction in the measure of JS as life satisfaction has been shown to be tightly related to JS (Hayes et al., 2010). The JS scale was developed by Delaney and Huber (1996) as part of the Nursing Management Minimum Data Set to provide nurse leaders a veritable set of vital signs upon which management decisions could be made. Patient Satisfaction with Nurse Communication As an outcome of quality, satisfaction with communication has correlated with health status, adherence to treatment, and understanding information (McFarland, Shen, & Holcombe, 2016). With such a strong relationship with critical health elements, the patient satisfaction survey is required by the Centers for Medicare and Medicaid services and is used to determine 30% of hospital value-based purchasing reimbursements to hospitals (McFarland et al., 2016). Hospital Consumer Assessments of Healthcare Providers and Systems (HCAHPS) surveys are completed by patients or their families after hospital discharge and are used to measure and subsequently improve quality of care. The required HCAHPS survey has 11 domains, one of which being patient satisfaction with nurse communication (PS-RN Com). Nurse communication is made up of four questions..

(43) 43 Falls A fall is defined as a sudden, unintended, and uncontrolled, downward displacement of a patient’s body to the ground or other object (Choi & Boyle, 2013). Purposeful falls are not included in the definition. Patient falls are typically reported through a hospital’s patient safety event reporting tool. The number of events are aggregated, typically by the patient care unit and reported as a rate of the number of falls per 1000 patient days (Miake-Lye et al., 2013). Patient falls have been further categorized into falls with injury and falls without injury. For the purposes of standardizing definitions, any reported fall will be included in the rate of falls per 1000 patient days. Medication Errors Bates et al. (1995) defined a medication error as “any error occurring in the medication use process” with an emphasis placed on the delivery phase of medication administration (p. 199). The American Society of Health System Pharmacists published a guideline for categorizing medication errors: prescribing, omission, timing, use of an unauthorized drug, improper dosing, wrong dosage form, wrong drug preparation, wrong administration technique, deteriorated drug, monitoring, compliance, and other errors (American Society of HealthSystem, 1993; Wittich et al., 2014). Pape (2003) more narrowly defined medication administration errors as a breach in any one of the seven rights of the medication administration process (right patient, right drug, right dose, right time, right route, right reason, and right documentation) in her study examining distractions during the medication administration process. Medication errors are typically reported into the organization’s patient safety event reporting tool. For the purpose of this study, any medication error reported through the patient safety event reporting tool will be included and reported per 1000 patient days..

(44) 44 Table 1. Definitions of Core Study Concepts Organizing Concept Conceptual Definition Category Individual Years of 3 specific time measurements: years of experience in the Attributes Experience unit, hospital, and nursing profession Time Since Highest Degree. Years since completion of the highest degree. Resilience. Environmental Turbulence. Ability to function effectively under stress, despite environmental turbulence, or when strategies applied to solve a problem have failed; infers a positive attitude to changes, tolerance of uncertainty and to stressful situations Staff perceptions of frequency of change and its predictability. Environmental Dynamism Accessibility. Job Satisfaction. The availability of equipment, supplies, and other components of care required for care of patients The geographic distance staff travel to provide patient care; related to the size of the patient care unit The existence of adequate support services that respond quickly to issues to reduce the need for nursing hours The volume of patients per day A person is the initiator of activities, which have positive effects on the environment The changing or modifying of oneself or one’s behavior to better fit a new environment; includes interpersonal and cultural adaptability when dealing with people or the constant learning of new skills, tasks, technologies, and procedures The affective response one has to the job. Patient Satisfaction with Nurse Communication. Patient report of their satisfaction with nursing communication as measured by Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS). Distance. Workforce Agility. Support Service Response Size Proactivity Adaptability. Outcomes. (American Society of Health-System, 1993; Brewer & Verran, 2013; Choi & Boyle, 2013; Delaney & Huber, 1996; Sherehiy & Karwowski, 2014; Stimpfel et al., 2016). Theoretical Framework Theory of Human Work Organization Sherehiy and Karwowski (2014) proposed the Human Work Organization (HWO) Theory to explain the relationship between an organization’s agile strategy, WFA, and work.

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