The Verran Professional Governance Scale: Confirmatory and Exploratory Analysis.

This article describes psychometric testing and refinement of the Verran Professional Governance Scale (VPGS), which measures behaviors associated with professional governance. Phase 1 reduced the items on the scale based on floor and ceiling effects and redundancy of items. Phase 2 examined structural construct validity using exploratory (EFA) and confirmatory factor analysis (CFA). The final 22-item instrument demonstrates satisfactory internal consistencies and fit indices and significant positive correlation between the VPGS, job satisfaction, and control over nursing practice.

Consensus achievement of leadership, organisational and individual factors that influence safety climate: Implications for nursing management.

AIM: To validate a framework of factors that influence the relationship of transformational leadership and safety climate, and to enable testing of safety chain factors by generating hypotheses regarding their mediating and moderating effects. BACKGROUND: Understanding the patient safety chain and mechanisms by which leaders affect a strong climate of safety is essential to transformational leadership practice, education, and research. METHODS: A systematic review of leadership and safety literature was used to develop an organising framework of factors proposed to influence the climate of safety. A panel of 25 international experts in leadership and safety engaged a three-round modified Delphi study with Likert-scored surveys. RESULTS: Eighty per cent of participating experts from six countries were retained to the final survey round. Consensus (>66% agreement) was achieved on 40 factors believed to influence safety climate in the acute care setting. CONCLUSIONS: Consensus regarding specific factors that play important roles in an organisation's climate of safety can be reached. Generally, the demonstration of leadership commitment to safety is key to cultivating a culture of patient safety. IMPLICATIONS FOR NURSING MANAGEMENT: Transformational nurse leaders should consider and employ all three categories of factors in daily leadership activities and decision-making to drive a strong climate of patient safety.

Evolution of Structural Empowerment: Moving From Shared to Professional Governance.

OBJECTIVE: The aim of this study is to describe the maturation of the concept of shared governance to professional governance as a framework for structural empowerment. BACKGROUND: An analysis of the literature and concept clarification of structural empowerment and shared governance demonstrate that the concept and attributes of shared governance have evolved toward professional governance. METHODS: A comprehensive, deductive literature review and concept clarification of structural empowerment, shared governance, and related constructs was completed. RESULTS: The concept and practice of shared governance has matured to a concept of professional governance with the attributes of accountability, professional obligation, collateral relationships, and effective decision-making.

Measuring nursing unit environments with four composite measure.

Understanding the context in which nurses work is an important step to designing work environments in which nurses can achieve targeted quality. Developing a usable instrument for describing the work environment and the relationship to staffing is essential for the development of evidence-based staffing decisions. The major implications of the research reported here are that the work environment of nurses, while complex, can be modeled with composite variables that reflect various dimensions of that environment. This ability to model the environment with fewer variables enhances the interpretation of environmental factors that have the greatest impact on patient outcomes. This reduction is valuable to the clinician, manager, and administrator in determining the key factors that need to be altered in the work environment to improve the quality of the patient experience.

Simulating nursing unit performance with OrgAhead: strengths and challenges.

In this article, we briefly describe our use of a computational modeling tool, OrgAhead, details of which have been reported previously, then discuss several of the challenges computational modeling presented and our solutions. We used OrgAhead to simulate 39 nursing units in 13 Arizona hospitals and then predict changes to improve overall patient quality and safety outcomes. Creating the virtual units required (1) collecting data from managers, staff, patients, and quality and information services on each of the units; (2) mapping specific data elements (eg, control over nursing practice, nursingworkload, patient complexity, turbulence, orientation/tenure, education) to OrgAhead's parameters and variables; and then (3) validating that the newly created virtual units performed functionally like the actual units (eg, actual patient medication errors and fall rates correlated with the accuracy outcome variable in OrgAhead). Validation studies demonstrated acceptable correspondence between actual and virtual units. For all but the highest performing unit, we generated strategies that improved virtual performance and could reasonably be implemented on actual units to improve outcomes. Nurse managers, to whom we reported the results, responded positively to the unit-specific recommendations, which other methods cannot provide. In the end, resolving the modeling challenges we encountered has improved OrgAhead's functionality and usability.

Nurse managers' decisions: fast and favoring remediation.

How do nurse managers make decisions about quality issues on their units? We asked 10 nurse managers in 3 Arizona hospitals to describe how they resolved a recent quality issue. The managers tended to use a linear, but cognitively expensive strategy, often jumping from problem to solution without a clear goal and selecting solutions biased toward remedial education. Decision support tools should help managers think more systemically and efficiently, while encouraging consideration of more alternatives to reach targeted goals.

Accurate assessment of clinical nurses' work environments: response rate needed.

Improvement of hospital unit work environments is key to quality patient care, productivity, nurse retention, and job satisfaction. Accurate measurement of such environments is necessary prior to introduction and evaluation of improvement structures and strategies. Characteristics and attributes of work environments are group level phenomena. Accurate assessment of these phenomena requires survey response rates of sufficient size to ensure sample representativeness and data that can reliably be aggregated to group level. What is the sufficient response rate? This question was answered through psychometric testing of five random samples from the population of 23 M.D. Anderson Cancer Center clinical units that had 100% response rates on an environmental survey. Response rates of 40% or more had acceptable psychometric properties for unit-specific scales.

Professional Governance Scale: Instrument Development and Content Validity Testing.

Instrument development and content validity testing resulted in a new instrument to measure the relatively new concept of professional governance. Professional governance is defined as the accountability, professional obligation, collateral relationships and decision making of a professional, foundational to autonomous practice and achievement of exemplary empirical outcomes. Fourteen experts with subject matter expertise either in measurement development or in creating professional practice environments assessed the validity of the proposed items and the instrument. The resulting Professional Governance Scale consisted of 75 items that adequately covered all attributes and their characteristics and had a Relevancy Mean Individual Content Validity Index of 95.

Using OrgAhead, a computational modeling program, to improve patient care unit safety and quality outcomes.

As part of ongoing research to investigate the impact of patient characteristics, organization characteristics and patient unit characteristics on safety and quality outcomes, we used a computational modeling program, OrgAhead, to model patient care units' achievement of patient safety (medication errors and falls) and quality outcomes. We tuned OrgAhead using data we collected from 32 units in 12 hospitals in Arizona. Validation studies demonstrated acceptable levels of correspondence between actual and virtual patient units. In this paper, we report how we used OrgAhead to develop testable hypotheses about the kinds of innovations that nurse managers might realistically implement on their patient care units to improve quality and safety outcomes. Our focus was on unit-level innovations that are likely to be easier for managers to implement. For all but the highest performing unit (for which we encountered a ceiling effect), we were able to generate practical strategies that improved performance of the virtual units that could be implemented by actual units to improve safety and quality outcomes. Nurse managers have responded enthusiastically to the additional decision support for quality improvement.

Development of an Instrument to Measure the Unintended Consequences of EHRs.

This article augments the existing body of literature through examining the creation and design of an instrument measuring unintended consequences (UCs) of electronic health records (EHRs). Data from a previous qualitative study that explored nurses' perceptions of EHR effectiveness as a communication system were analyzed using a theoretical model focused on decision making. The qualitative data, informed by the model, were then organized into an instrument seeking to quantitatively measure nurses' experiences with UCs of EHRs. The model assisted in revealing patterns in nurses' perceptions of the effectiveness of the EHR as a communication system that ultimately strengthened the development of the instrument. Instrumentation from qualitative data has long been considered an acceptable and positive approach to scale development. The process for accomplishing this goal has often been omitted from the literature. We contend that other researchers will find this methods article informative for similar undertakings.

Using computational modeling to improve patient care unit safety and quality outcomes.

As part of ongoing research to investigate the impact of patient characteristics, organization characteristics and patient unit characteristics on safety and quality outcomes, we are using a computational modeling program, OrgAhead, to model patient care units' achievement of patient safety (medication errors and falls) and quality outcomes. We tuned OrgAhead using data we collected from 16 units in 5 hospitals. Subsequent validation studies demonstrated acceptable levels of correspondence between actual and virtual patient units. In this paper, we report on our initial efforts to use OrgAhead to develop testable hypotheses about the kinds of innovations that nurse managers might realistically implement on their patient care units to improve quality and safety outcomes. Our focus is on unit-level innovations that are likely to be easier for managers to implement. For all but the highest performing unit (for which we encountered a ceiling effect), we were able to generate practical strategies that improved performance of the virtual units by 6-8 percentage points. Nurse Managers have responded enthusiastically to the additional decision support for quality improvement

Using Cognitive Work Analysis to fit decision support tools to nurse managers' work flow.

PURPOSE: To better understand the environmental constraints on nurse managers that impact their need for and use of decision support tools, we conducted a Cognitive Work Analysis (CWA). A complete CWA includes system analyses at five levels: work domain, decision-making procedures, decision-making strategies, social organization/collaboration, and worker skill level. Here we describe the results of the Work Domain Analysis (WDA) portion in detail then integrate the WDA with other portions of the CWA, reported previously, to generate a more complete picture of the nurse manager's work domain. METHODS: Data for the WDA were obtained from semi-structured interviews with nurse managers, division directors, CNOs, and other managers (n = 20) on 10 patient care units in three Arizona hospitals. The WDA described the nurse manager's environment in terms of the constraints it imposes on the nurse manager's ability to achieve targeted outcomes through organizational goals and priorities, functions, processes, as well as work objects and resources (e.g., people, equipment, technology, and data). Constraints were identified and summarized through qualitative thematic analysis. RESULTS: The results highlight the competing priorities, and external and internal constraints that today's nurse managers must satisfy as they try to improve quality and safety outcomes on their units. Nurse managers receive a great deal of data, much in electronic format. Although dashboards were perceived as helpful because they integrated some data elements, no decision support tools were available to help nurse managers with planning or answering "what if" questions. The results suggest both the need for additional decision support to manage the growing complexity of the environment, and the constraints the environment places on the design of that technology if it is to be effective. Limitations of the study include the small homogeneous sample and the reliance on interview data targeting safety and quality.

Using ORA to explore the relationship of nursing unit communication to patient safety and quality outcomes.

PURPOSE: We used ORA, a dynamic network analysis tool, to identify patient care unit communication patterns associated with patient safety and quality outcomes. Although ORA had previously had limited use in healthcare, we felt it could effectively model communication on patient care units. METHODS: Using a survey methodology, we collected communication network data from nursing staff on seven patient care units on two different days. Patient outcome data were collected via a separate survey. Results of the staff survey were used to represent the communication networks for each unit in ORA. We then used ORA's analysis capability to generate communication metrics for each unit. ORA's visualization capability was used to better understand the metrics. RESULTS: We identified communication patterns that correlated with two safety (falls and medication errors) and three quality (e.g., symptom management, complex self care, and patient satisfaction) outcome measures. Communication patterns differed substantially by shift. CONCLUSION: The results demonstrate the utility of ORA for healthcare research and the relationship of nursing unit communication patterns to patient safety and quality outcomes.

The Systems Research Organizing Model: a conceptual perspective for facilities design.

PURPOSE: The purpose of this article is to (1) demonstrate the utility of the Systems Research Organizing Model (SROM) for evidence-based design; (2) explicate the SROM; and (3) demonstrate how the SROM can advance the science of healthcare design. BACKGROUND: Grounded in systems science and adapted from the Quality Health Outcomes Model, the SROM was originally designed to assist in the organization of nursing systems research. It is useful for research in other fields as well because it serves as a potential framework for new investigations, allows delineation of key factors in previous research studies, and allows for the synthesis of a body of research knowledge. By means of the latter function, it helps identify knowledge that is ready to be translated to the practice environment. MODEL DESIGN: The SROM is a fully justified model with four core constructs: client, context, action focus, and outcomes. Feedback loops in the model reflect the interrelatedness of the core constructs and recognize the complex nature of the healthcare environment. CONCLUSIONS: The SROM may be useful for organizing research studies of interest to healthcare design scientists and practitioners. This framework has promise for organizing studies, identifying gaps in current research studies, and synthesizing multiple studies for application to practice.

Social relations modeling in telehomecare.

Telehomecare usage requires that patients, home-helpers and nurses interact as a group using remote communication technology. Group interaction produces many levels of social variance that contribute to outcomes. It is unknown how social variances in remote interaction influence outcomes. Social Relations Model (SRM) approach is currently used to analyze individual, relational and group influences on family outcomes. SRM applied to telehomecare groups contributes to better understanding of the influence of remote relationships on patient outcomes.

Public health nursing: the generalist in a specialized environment.

In implementing a generalist model of public health nursing (the Comprehensive Multi-level Nursing Practice Model) in a rural county health department, a research team encountered critical challenges. The framework for the model was a philosophy of public health nursing practice and action research to support the public health nurse generalist role. Challenges in implementing the model stemmed from conflicts between the research team and the health department that were rooted in philosophical differences about how to implement care and the nature of nursing and the public health nursing role. Key factors were the subtle forces operating in the public health environment that constrain the public health nurse generalist role. Based on conflicts that arose in implementing the model, implications for public health nursing practice are in opportunities to influence policy at health department and other levels and responsibility for assuring professional practice.

Using computational modeling to transform nursing data into actionable information.

Transforming organizational research data into actionable information nurses can use to improve patient outcomes remains a challenge. Available data are numerous, at multiple levels of analysis, and snapshots in time, which makes application difficult in a dynamically changing healthcare system. One potential solution is computational modeling. We describe our use of OrgAhead, a theoretically based computational modeling program developed at Carnegie Mellon University, to transform data into actionable nursing information. We calibrated the model by using data from 16 actual patient care units to adjust model parameters until performance of simulated units ordered in the same way as observed performance of the actual units 80% of the time. In future research, we will use OrgAhead to generate hypotheses about changes nurses might make to improve patient outcomes, help nurses use these hypotheses to identify and implement changes on their units, and then measure the impact of those changes on patient outcomes.

Using computational modeling to study the impact of workplace characteristics on patient safety outcomes.

How do patient characteristics, organization characteristics and patient care unit characteristics interact to affect quality, safety, and cost outcomes? What changes can nurse managers make on their units that will optimize outcomes for their patients? To answer these questions, we are collecting data from 35 nursing units in 12 hospitals in Arizona, and using the results as a basis for computational modeling. Although it has been used in clinical research, until now computational modeling has had little application to healthcare or nursing organizations. In this poster session, we describe our application of Orgahead, a computational modeling program.