Healthcare Continuity in Crisis: Addressing Gaps in Longitudinal Care Through Inferential Statistics.

Continuity of care is vital to improving outcomes for an aging US population increasingly burdened by chronic conditions. However, systemic fragmentation remains pervasive, exacerbated by disjointed care transitions, misaligned incentives, and inadequate communication across providers and care settings. This study investigates the role of transitional care management (TCM) services, Medicare-reimbursed follow-up visits after hospital discharge, as a potential proxy for continuity of care. Using 2022 publicly available Centers for Medicare and Medicaid Services (CMS) data, the study evaluates whether higher state-level utilization of TCM services correlates with lower rates of potentially avoidable hospitalizations, measured through prevention quality indicators (PQIs). Contrary to the hypothesis, regression analyses revealed a statistically significant positive association between the TCM-discharge ratio and PQI rates in five of 12 indicators, including urinary tract infection, uncontrolled diabetes, and composite PQI measures. This suggests that TCM services may be employed more reactively in high-burden states rather than preventively. Furthermore, urbanization and physician density showed mixed associations with PQIs, while poverty level consistently correlated with higher avoidable hospitalizations across all models, highlighting structural inequities in access and quality. The study's findings challenge assumptions that increased follow-up care alone reduces hospitalizations. Instead, they suggest that isolated interventions such as TCM are insufficient unless embedded within broader, longitudinal care frameworks. Barriers to continuity identified include the undervaluation of evaluation and management services, lack of cross-provider communication, underuse of claims data for identifying high-risk patients, and fragmentation caused by non-traditional care settings such as urgent care and retail clinics. Meanwhile, opportunities for strengthening care continuity include integrating social determinants of health (SDOH) into clinical care, leveraging health information technology, and enhancing patient trust and engagement. The implications are multifaceted. First, structural drivers such as poverty and health workforce shortages play a more significant role than follow-up alone. Second, policy and reimbursement frameworks must shift toward models that incentivize proactive, coordinated, and relationship-based care. Finally, longitudinal research using patient-level data is needed to better understand causal pathways and inform evidence-based strategies for embedding continuity within evolving healthcare delivery models. This study advances the dialogue on continuity of care by empirically analyzing a national, policy-relevant dataset and drawing attention to the complex interplay among clinical interventions, socioeconomic context, and health system structure. It underscores that continuity is not merely a billing code or a visit count but a system-wide commitment requiring coordinated action from clinicians, payers, and policymakers.