Change Frameworks for Complex Change: PCMH Transformation With Kotter’s 8 Steps (DNP Signature Assignment Example)

Signature Assignment: The Impact of Change Frameworks in Supporting Complex Change Initiatives

As addressed in the weekly readings, promoting a culture of success, fostering leadership and professional capacity, and building a process of continuous improvement are empirical for the growth of healthcare facilities. By supporting and empowering the workforce and developing policies that promote a culture of health and wellness, population health outcomes may be enhanced. The purpose of this Signature Assignment is to describe and analyze the variables embedded in change frameworks to support complex adaptive change initiatives and drive population health improvement outcomes.

1. Identify a system-wide transformation project or workflow improvement process at a healthcare facility (for example, the patient-centered medical home model, an electronic medical record system, or an end-of-life and healthcare proxy process). Describe (a) the project or process, (b) the healthcare facility, (c) the population that may be positively impacted and (d) the staff involved and impacted.
2. Select one framework: Switch, Lewin’s Change Management Model, Kotter Eight-Step Change Model, or McKinsey 7-S Model. (a) Describe the variables embedded in the framework; (b) depict prospective implementation challenges, limitations, and/or barriers; (c) describe a variable or concept that you would propose and should be considered in this framework.
3. Describe a formative and summative evaluation process: (a) formative evaluation processes; (b) summative evaluation processes; (c) dissemination of findings and outcomes at a Board meeting and/or Advisory Board meeting.

Specifications: 2,500 words; title page and reference page in APA style (not counted); at least six scholarly sources; peer-reviewed articles only, published 2021–2026, from North American journals only (no European journals).

Original example for study purposes (about 2,500 words). The facility is fictional.

The Impact of Change Frameworks in Supporting Complex Change Initiatives

Health care organizations operate as complex adaptive systems in which clinicians, staff, patients, technology and policy interact in ways that are difficult to predict. Transforming such systems requires more than a good idea; it requires a structured approach to leading people through change while continuously learning and adjusting. This paper describes a system-wide transformation to the patient-centered medical home (PCMH) model at a federally qualified health center, applies Kotter’s eight-step change model to guide implementation, analyzes the framework’s variables and challenges, proposes an additional variable focused on workforce well-being and equity, and outlines formative and summative evaluation and board-level dissemination.

The System-Wide Transformation Project

Description of the project. The proposed project is the transformation of primary care delivery to the PCMH model. A PCMH organizes care around the patient through team-based care, continuity with a personal clinician and care team, enhanced access, care coordination across settings, population health management using registries, and a commitment to quality improvement and patient experience. Implementation will include forming care teams (teamlets) of a primary care clinician, registered nurse, medical assistant and shared care coordinator; empanelment of every patient to a care team; daily team huddles; registries for chronic conditions such as diabetes and hypertension; same-day appointments and patient portal messaging; standardized workflows for transitions of care after hospital and emergency department visits; and regular collection of patient experience data. The organization will pursue PCMH recognition from a national accrediting body as a milestone.

Evidence supports this transformation. In a study of 34 primary care offices serving about 171,000 patients, PCMH implementation combined with financial incentives was associated with improved rates of diabetes control, hypertension control and breast and colorectal cancer screening, although staff satisfaction and work-life balance did not improve (Fortuna et al., 2021). This finding is important: the model can improve population health, but leaders must pay deliberate attention to the workforce experience during the change. Continuity of care, a core PCMH feature, is also a focus of research in federally qualified health centers, where investigators have examined relationships between patient–provider continuity and PCMH recognition (Simon et al., 2025).

Description of the facility. The setting is Riverside Community Health Center, a fictional federally qualified health center (FQHC) with three urban clinic sites and one mobile unit. It serves about 18,000 patients annually and offers primary care, behavioral health, dental and pharmacy services. As an FQHC, it receives federal funding to serve medically underserved communities, provides care regardless of ability to pay using a sliding fee scale and is governed by a community board on which patients make up the majority. Currently, care is organized around individual clinicians, patients often see whichever clinician is available, chronic disease outcomes lag state benchmarks and staff report fragmented workflows.

Population positively affected. Riverside’s patient population is predominantly low-income, with about 60% covered by Medicaid, 20% uninsured and 12% covered by Medicare. Approximately half of patients identify as Hispanic or Latino and a quarter as Black, and about one-third prefer a language other than English. High rates of diabetes, hypertension, depression and obesity, combined with social needs such as housing instability and food insecurity, make this population especially likely to benefit from team-based, coordinated care. Expected benefits include improved continuity, better control of chronic conditions, higher preventive screening rates, fewer avoidable emergency department visits and stronger connections to behavioral health and social services. Prior evaluations of PCMH programs, including a statewide multi-payer initiative examined for its effects on antihypertensive medication adherence, illustrate the model’s focus on population-level chronic disease outcomes (Fakeye et al., 2022).

Staff involved and affected. The transformation affects nearly every role. Physicians, nurse practitioners and physician assistants will lead care teams and manage defined panels. Registered nurses will expand into care management, triage and patient education. Medical assistants will take on pre-visit planning, standing orders and screening outreach. Care coordinators and community health workers will address transitions and social needs. Behavioral health clinicians will integrate into teams, and front-desk staff will manage scheduling for continuity and same-day access. Information technology and data analysts will build registries and dashboards, and leaders will guide the process. Research in Veterans Health Administration PCMH teams found that clinicians relied heavily on teammates and that nurses reported high levels of reliance placed on them, but participants raised concerns about unclear roles and the need for a team leader (Wakefield et al., 2022). Further work has examined how primary care staff perceive their responsibilities in PCMH teams (Wakefield et al., 2024). Clarifying roles and scope of practice will therefore be essential.

Selected Framework: Kotter’s Eight-Step Change Model

Kotter’s eight-step model was selected because the PCMH transformation is large, multi-site and culture-changing, and the model provides a clear sequence for building urgency, leadership and sustained change. It has been applied successfully to complex redesign efforts in academic health settings; for example, a department used Kotter’s framework to restructure its graduate medical education recruitment process by forming a guiding coalition, communicating a vision and generating short-term wins (Miles et al., 2023).

Variables embedded in the framework. Each step contains variables that leaders must manage:

1. Create a sense of urgency. Variables include the strength of the case for change and the credibility of data. Riverside leaders will share chronic disease outcomes, patient experience scores, continuity rates and patient stories at all-staff meetings.
2. Build a guiding coalition. Variables include the coalition’s composition, authority and trust. The coalition will include the chief medical officer, director of nursing, a medical assistant lead, a front-desk supervisor, a behavioral health clinician, a data analyst and a patient board member.
3. Form a strategic vision and initiatives. Variables include clarity and alignment with mission. The vision is “Every patient has a team that knows them and helps them stay healthy.”
4. Communicate the vision and enlist volunteers. Variables include frequency, channels and two-way dialogue: daily huddles, monthly town halls, newsletters and a feedback channel.
5. Enable action by removing barriers. Variables include structures, systems, skills and resources: redesigning job descriptions, building EHR registries, adjusting schedules and training staff.
6. Generate short-term wins. Variables include visibility and timing: a pilot team at one site will aim to increase hypertension control and same-day access within six months and share results.
7. Sustain acceleration. Variables include momentum and spread: lessons from the pilot will guide rollout to all teams and sites.
8. Institute change. Variables include culture, policies and reinforcement: new workflows will be written into policy, hiring and onboarding will emphasize team-based care, and recognition will reward team outcomes.

Implementation challenges, limitations and barriers. Several challenges are likely. Workforce strain and change fatigue are major risks, especially in FQHCs with high turnover. Fortuna et al. (2021) found that PCMH implementation did not improve staff satisfaction or work-life balance and that clinicians reported mostly nonsignificant declines, suggesting that transformation can add burden. Role confusion may arise as tasks shift among team members (Wakefield et al., 2022). Technology and data limitations, such as incomplete registries or poorly designed EHR templates, can slow progress. Financial constraints are significant, because new roles and training require investment while reimbursement for care coordination may be limited. Patient engagement barriers, including language, transportation, work schedules and mistrust, may limit the benefits of continuity and access changes. Measurement burden also matters; practices pursuing PCMH recognition must collect patient experience data and often choose survey tools based on cost, external program requirements and benchmarking needs (Quigley et al., 2023).

Kotter’s model also has inherent limitations. It is linear and top-down, assuming that change proceeds in sequence, whereas complex adaptive systems often require iterative cycles and adjustments. It emphasizes leadership and communication but gives less guidance on measurement, frontline co-design and the emotional effects of change. It also focuses on organizational change and does not explicitly address patients, communities or equity, which are central to population health.

A proposed variable: workforce well-being and equity engagement. I propose adding a variable that runs through all eight steps: workforce well-being and equity engagement. This variable has two dimensions. First, leaders would monitor staff well-being, workload and burnout during the transformation and adjust pacing, staffing and support, recognizing that the PCMH may not automatically improve staff experience (Fortuna et al., 2021). Second, the change effort would actively involve patients and community members, especially those facing the greatest barriers, in designing workflows and evaluating results. In practice, this means including frontline staff and patient representatives in the guiding coalition, using staff pulse surveys and patient feedback in every phase, and stratifying outcomes by race, ethnicity, language and payer to ensure that improvements reach all groups. Evidence-based change models increasingly integrate attention to the people affected by change rather than leadership actions alone; for example, change management models have been developed to guide implementation in geriatric nursing programs (Gilmartin, 2023). Adding this variable makes Kotter’s framework better suited to complex adaptive health systems and population health goals.

Formative and Summative Evaluation

Formative evaluation. Formative evaluation occurs during implementation to guide improvement. Riverside will use Plan-Do-Study-Act cycles at the pilot site, with monthly reviews by the guiding coalition. Process measures will include the percentage of patients empaneled to a team, huddle completion rates, the percentage of visits with the patient’s own team (continuity), registry completeness, time to third-next-available appointment, completion of transition-of-care follow-up within seven days, and staff training completion. Staff experience will be measured through brief monthly pulse surveys on workload, role clarity and burnout, and through focus groups with each role. Patient feedback will be gathered through short surveys and a patient advisory group. Findings will be used to adjust workflows, staffing and communication before spreading to other sites.

Summative evaluation. Summative evaluation will assess outcomes after 18 to 24 months. Clinical outcome measures will include the percentage of patients with diabetes with HbA1c below 8%, hypertension control below 140/90 mm Hg, depression screening and follow-up, and breast, cervical and colorectal cancer screening rates. Utilization measures will include avoidable emergency department visits and hospital readmissions. Patient experience will be measured with a standardized survey, and continuity will be compared with baseline (Simon et al., 2025). Workforce outcomes will include turnover, burnout and satisfaction. Financial measures will include changes in revenue, value-based incentive payments and cost per patient. All outcomes will be stratified by demographics and payer to evaluate equity. Achieving PCMH recognition will serve as an additional milestone.

Dissemination to the board and advisory board. Results will be shared with Riverside’s governing board, whose patient majority makes it especially important to present findings in clear, accessible language. Quarterly dashboards will display key measures with targets and trends, along with brief patient and staff stories that illustrate impact. A summative report after the evaluation period will summarize outcomes, equity results, costs, lessons learned and recommendations for sustaining and expanding the model. A patient and community advisory board will review findings and help interpret results, especially where disparities persist. Findings will also be shared with staff at town halls to recognize their contributions and, where appropriate, at state primary care association meetings or in professional publications to contribute to the evidence base.

Conclusion

Transforming primary care into a patient-centered medical home is a complex change that touches every role and process in an FQHC. Kotter’s eight-step model offers a clear structure for creating urgency, building leadership coalitions, communicating a vision and anchoring change in culture. However, its linear, leader-focused design must be complemented by attention to workforce well-being and meaningful engagement of patients and communities. With rigorous formative and summative evaluation and transparent reporting to governing and advisory boards, Riverside can use this framework to drive measurable improvements in population health while supporting the people who deliver care.

References

Fakeye, O. A., Khanna, N., Hsu, Y.-J., & Marsteller, J. A. (2022). Impact of a statewide multi-payer patient-centered medical home program on antihypertensive medication adherence. Population Health Management, 25(3), 309–316. https://doi.org/10.1089/pop.2021.0172

Fortuna, R. J., Johnson, W., Clark, J. S., Messing, S., Flynn, S., & Judge, S. R. (2021). Impact of patient-centered medical home transformation on providers, staff, and quality. Population Health Management, 24(2), 207–213. https://doi.org/10.1089/pop.2020.0007

Gilmartin, M. J. (2023). An evidence-based change management model to guide NICHE implementation efforts. Geriatric Nursing, 49, 212–215. https://doi.org/10.1016/j.gerinurse.2022.12.004

Miles, M. C., Richardson, K. M., Wolfe, R., Hairston, K., Cleveland, M., Kelly, C., Lippert, J., Mastandrea, N., & Pruitt, Z. (2023). Using Kotter’s change management framework to redesign departmental GME recruitment. Journal of Graduate Medical Education, 15(1), 98–104. https://doi.org/10.4300/JGME-D-22-00191.1

Quigley, D. D., Qureshi, N., & Hays, R. D. (2023). Reasons primary care practices chose patient experience surveys during patient-centered medical home transformation. Journal of Ambulatory Care Management, 46(1), 34–44. https://doi.org/10.1097/JAC.0000000000000442

Simon, J., Panzer, J., Ekong, A., Liss, D. T., Sinsky, C. A., & Wright, K. M. (2025). Continuity of care in federally qualified health centers: Examining patient-provider relationships and patient centered medical home recognition. Journal of the American Board of Family Medicine, 38(3), 490–499. https://doi.org/10.3122/jabfm.2024.240365R1

Wakefield, B. J., Farag, A., Paez, M. B., & Stewart, G. L. (2024). Perceptions of responsibilities by primary care staff in a patient-centered medical home. JONA: The Journal of Nursing Administration, 54(6), 333–340. https://doi.org/10.1097/NNA.0000000000001435

Wakefield, B. J., Lampman, M. A., Paez, M. B., Farag, A., Ferguson, H., & Stewart, G. L. (2022). Delegation of work within a patient-centered medical home. JONA: The Journal of Nursing Administration, 52(12), 679–684. https://doi.org/10.1097/NNA.0000000000001231