A Nursing Care Coordination Theory for Chronic Illness Management

Thesis Abstract

Chronic illness imposes complex, fragmented care demands that disrupt continuity and heighten patient burden, underscoring the need for a formalized nursing care coordination framework to optimize outcomes across primary, secondary, and community settings. This study aims to develop and validate a Nursing Care Coordination Theory (NCC Theory) for chronic illness management that delineates core constructs, relationships, and processes underpinning seamless, patient-centered care. Specific objectives are (1) to identify determinants of effective care coordination from patient, caregiver, and clinician perspectives; (2) to articulate a theoretical model integrating professional practice, information exchange, and system-level facilitators and barriers; (3) to evaluate the model’s predictive utility for care continuity, patient self-management, health-related quality of life, and healthcare utilization; and (4) to derive testable propositions and measurement indicators for empirical validation in future research. The study employs a mixed-methods, multi-phase design guided by grounded theory and structuration theory to ensure theoretical rigor and practical applicability. Phase 1 comprises semi-structured interviews with 40 patients with chronic non-communicable diseases (e.g., diabetes, heart failure) and 20 nurse case managers from urban primary care clinics, augmented by 30 family caregivers. Phase 2 uses a Delphi panel of 18 clinical experts to refine the proposed constructs and relationships. Phase 3 collects cross-sectional survey data from 320 patients, 120 nurses, and 120 primary care coordinators to test the NCC Theory’s propositions. Instrumentation for patients includes the Care Coordination Effectiveness Scale, the Self-Management Scale, the EQ-5D-5L for health-related quality of life, and healthcare utilization records (hospitalizations, emergency visits) from electronic health records. Nurse and coordinator instruments assess perceived coordination quality, information exchange, role clarity, and workload, with validity and reliability evaluated via face validity, exploratory and confirmatory factor analyses, Cronbach’s alpha, and test-retest reliability. Data analysis proceeds in three strands qualitative data will be analyzed using thematic analysis and open coding in NVivo to identify core themes; quantitative data will be analyzed using structural equation modeling (SEM) to test the NCC Theory’s structural relationships and latent variables, complemented by hierarchical linear modeling (HLM) to account for clustered data at the clinic level; and model fit will be evaluated using CFI, TLI, RMSEA, and SRMR criteria. Mediation and moderation analyses will explore how organizational context, information systems, and patient activation influence outcomes. Key expected findings include identification of core constructs—Care Coordination Competence (nurses’ knowledge and skills), Information Continuity (shared records and timely communication), Patient Engagement (activation and self-management), and System Alignment (policies, roles, and workflows)—and their interdependencies. It is anticipated that higher perceived coordination quality will be associated with improved self-management, higher quality of life, and reduced unplanned healthcare utilization, with patient activation mediating several of these relationships. The model is expected to demonstrate robust fit across diverse chronic conditions and settings, with context-specific variations elucidated through multi-site analysis. The study contributes to knowledge by offering a theoretically grounded, empirically validated NCC Theory that explicates the mechanisms by which nursing care coordination influences chronic illness outcomes. It integrates concepts from interprofessional collaboration, information continuity, patient activation, and healthcare system theory to provide a comprehensive framework for practice, measurement, and policy. The findings will inform the development of standardized care coordination protocols, nursing education curricula, and informatics-enabled interventions (e.g., interoperable health records, care plans) that can be scaled across health systems. Practical implications include guiding nurse-led care coordination programs, optimizing referral pathways, and reducing unnecessary service utilization through enhanced continuity of care. In conclusion, the anticipated results will advance nursing science by articulating a parsimonious yet comprehensive theory of care coordination for chronic illness management, with validated measurement strategies and actionable recommendations for clinical practice, training, and health system design. Policy-relevant recommendations will emphasize investment in interoperable information systems, defined care coordination roles, and performance metrics that reflect patient-centered outcomes and system efficiency.