This paper presents a discussion and model for measuring organizational change impact through widening perspectives on change processes.
This paper is based on a mixed-method inductive case study of a regional Queensland hospital forced to restructure operations and organization due to a significant site and services expansion.
Measuring the impact of change on stakeholders is often an afterthought, with preference given to the execution and planning of organizational change models. The impact of change on stakeholders can reveal negative effects on organizational performance, staff engagement, and change success. These negative outcomes may be mitigated by adopting a broad scope to change management that allows for impact measurements, flexible change model adoption, execution, and iterative feedback that is spread throughout the change process.
A single case study limits analytical generalizability. The theoretical framework presented requires validation across diverse organizational settings. Future research could investigate applicability in varied organizational structures and change scenarios.
Findings suggest that employing approaches to change, like the one presented, may increase change success and mitigate negative organizational change impact. This is particularly critical in healthcare, where staff and patient well-being are paramount to planned organizational change success.
Findings suggest that employing broad change management models, like the one presented, may increase change success and mitigate negative organizational change impact. This is particularly critical in healthcare, where staff and patient well-being are paramount to planned organizational change success.
This paper addresses an identified gap in the literature regarding change measurement, specifically within healthcare and large institutional forced expansion contexts. We propose using an accessible model that integrates change management steps that move beyond the boundaries of traditionally rigid and limiting planned organizational change approaches.
Introduction
To accommodate the increasing healthcare demand in rising populations, existing hospitals are undergoing expansion and redevelopment of sites and services (Pomare et al., 2019). Capacity-driven expansions often impact staffing organizational design. In many cases, organizational change is planned and executed ahead of physical site changes. This paper explores planned organizational change and presents a model for measuring and managing planned organizational change based upon a review of change management literature and findings from a hospital-based case study.
Literature review
Standard change management theories and practices, when viewed through the lens of planned organizational change management (POCM) models, concentrate on the strategic aspects and execution of change management frameworks, and often include assessments of organizational readiness. In their organizational readiness for change (ORC) research in healthcare settings, Boyacı and Söyük (2025) note that openness to change can vary across employees, and change success relies heavily on planning and preparation; adding that more situational research is required. Similarly, Caci et al. (2025) suggest that researchers need to conduct further change management research within healthcare settings; pointing out that measuring change at multiple stages, not just at the beginning, is needed to determine change readiness and effectiveness.
Given the need for change management research in healthcare, we explore how hospitals can benefit from the impact of organizational change, including restructuring staff roles and responsibilities. While exploring benefits we extend the application of ORC theory (Boyacı and Söyük, 2025). With assistance and permission from a multi-site regional Australian public hospital undergoing expansion, a study was conducted to answer the following research question:
How might the impact of demand-driven organizational restructures in healthcare settings be progressively measured and adequately adjusted?
By answering this research question within this case study, we present a change management model that may be adopted to measure the impact of change. We believe our model may suit a variety of change management scenarios, contributing to discourse around change readiness and planning.
Methodology
Driven by demographic data, the hospital (in this case study) was forced to restructure their organization to accommodate multi-site modifications and a 70% increase in full-time equivalent staff. The organizational restructure was planned and executed within 24 months. After this time, we (the researchers) were invited to explore and report on the impact of the planned organizational change. The sample respondents of the study were the senior staff members within the hospital. A total of 134 eligible employees were pre-selected by the hospital, including 26 executive staff members, 108 management, and other key staff. Likert scale and open question surveys were emailed to the names provided, and 56 usable surveys completed. Following the surveys, seven one-on-one interviews were conducted. Using thematic analysis to review interview outcomes, researchers also used hospital change planning documentation to validate and track the change management process, giving researchers three points of data suggested in case study research approaches (Yin, 2018). An example of a quantitative question on the Likert scale is “the restructure has created an improvement in reporting.” An example of a qualitative open-ended question is “If you were leading the organizational structure change initiative, what would you have done differently?”
Findings
First, documentation revealed that seven organizational priorities were guiding the change initiative. The seven identified priorities are communication, role clarification, reporting, support mechanisms, establishment of service lines, consultative decision-making, and governance (including fairness and justice). Respondents in the survey noted six more priorities not in the original documentation, showing further changes that could have been part of the change management plan. The six additional priorities were purpose, financial performance, productivity, issue resolution, patient care and staff satisfaction. This suggests that if more staff had been involved in creating and implementing the changes, especially the articulation of a clear purpose for the restructure, a more complete list of priorities could have been developed and communicated prior to the change initiative.
Second, findings revealed a significant disconnect between planned and perceived outcomes. While most respondents agreed that the change was necessary, only 39% felt the change objectives were clearly communicated. Third, findings suggested that support mechanisms provided by the hospital change managers were undesirable, with just half of the respondents reporting they felt adequately supported throughout the change process. Fourth, only 40% of respondents believed the changes were fairly and justly implemented, highlighting negative feelings among staff – a change-related factor often referred to as valence in change literature (Caci et al., 2025).
With the literature, research question, and four significant case study findings in mind, we present the following change impact measurement model (Table 1).
Model for measuring impact of organizational change
| Change phase | Key questions |
|---|---|
| 1. Planning Consideration through key questioning |
|
| 2. Adoption Change model adoption through inquiry | Select formal change approaches by asking: How can the change best be managed … … as a successful project? … expecting resistance? … interpreting and adjusting for time length and additional change priorities? … treating feedback as opportunity to allow change to emerge from the bottom-up? |
| Change phase | Key actions |
| 3. Implementation Execution through measured action |
|
| 4. Adaption Change Phase 3 through feedback |
|
In this model, five key questions are asked during planning (Phase 1) which precede and inform the adoption of a formal change management initiative (Phase 2). Both initial phases are guided by key questions. Once one or more change models are adopted, an implementation phase (Phase 3) is executed along with monitoring strategies, mitigation steps, and effective communication; this leads to adaption (Phase 4) which includes further monitoring, measuring, and change direction via a feedback loop back to implementation (Phase 3). The final two phases are guided by key actions
Change impact measurement model
The effectiveness and value of an impact measurement device depend on the change approach adopted (Rosenbaum et al., 2018). When a formal, intentional change model is chosen and managed, measuring its impact may be an important part of the process, particularly under an interpretive, emergent, less rigid approach. “We believe that the change model presented (Table 1) may assist in planning, adopting, implementing, and adapting to internal change feedback and external change forces throughout the change process.”
Conclusion
In answer to the question “How might the impact of demand-driven organizational restructures in healthcare settings be progressively measured and adequately adjusted?” we suggest that if organizations only wish to measure change based upon the ability to plan and execute necessary planned changes (using either a bespoke or formal change model) organizations may gladly report change success. However, if organizations broaden their view on successful and effective change to include the planning through considerations, change model adoption through inquiry, change implementation accompanied by measurement and adaptation through feedback, they will be compelled to report change success progressively and may avoid negative impact on both staff and organizational performance. This builds on ORC theory by improving the “readiness” of the organization ahead of the change initiative.
In conclusion, we believe that if those leading change in the case study hospital had approached change using a change impact measurement model, such as the one presented in this paper, several issues may have been mitigated. Mitigated issues may include comprehensive change priorities; improved communication around the necessity of the change; greater staff support during the change; and an increase sense of justice and fairness among staff.
Limitations and further research
External healthcare change factors beyond our control occurred during the case study. A change in leadership along with the COVID-19 pandemic impacted continuity of the project. These factors created limitations on the collection of data and the feedback within it. Further research is needed on similar organizational change cases in healthcare settings. Further, the change model presented (Table 1) warrants further validation across change scenarios in other sectors and settings to assess its feasibility and practical value.
