Patient safety is a critical concern in healthcare, with communication playing a pivotal role in ensuring positive outcomes. Despite its importance, communication breakdowns continue to be a leading cause of adverse events in hospitals Therefore, understanding the nuances of patient-healthcare provider communication and its influence on patient safety is imperative for improving healthcare delivery. The purpose of this study is to investigate the influence of patient-healthcare provider communication on hospital patient safety. Specifically, the study aims to:

1. Identify key communication factors contributing to hospital safety incidents (as measured by hospital associated infection rate)
2. Examine the association among nurse-patient communication, doctor-patient communication, communication about medication, responsiveness of hospital staff, transition of care, and overall hospital rating.

Methods

A comprehensive retrospective analysis was conducted utilizing datasets obtained from the Center for Medicare & Medicaid Services (CMS), specifically reports from the fiscal year 2023. Patient satisfaction scores pertaining to communication aspects were gleaned from Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS), while indicators of patient safety were derived from six healthcare-associated infection measures. Structural equation modeling (SEM) analyses will be conducted to answer the research questions. Two distinct SEMs will be executed: the first utilizing hospital baseline data, and the second leveraging hospital performance data.

Expected Outcomes

The sample size is sufficient with 2517 hospitals. We expect a significant correlation between positive patient perceptions of communication with healthcare providers and reduced infection rates. Furthermore, we anticipate a significant association between different types of communications and overall hospital rating.

Social determinants of health inequalities (SDoH) are known to affect lower-income demographics, related economic minorities, and other vulnerable populations adversely and disproportionately. Therefore, chronic diseases like type-2 Diabetes Mellitus (T2DM), coupled with protracted exposure to upstream SDoH, exacerbate chronic diseases. This study evaluated the influence of SDoH on the incidence/prevalence of T2DM in the US. Using the 2018 and 2023 Health County Rankings datasets, we evaluated whether a statistically predictable relationship existed between T2DM prevalence and contextually found SDoH in the US. We performed geospatial and geostatistical analyses via ordinary least squared-based multiple linear, geographically weighted, and multiscale geographically weighted regression models. The results showed that contextually found SDoH adversely influenced the prevalence of T2DM in the US, especially in historically marginalized populations, with F(1,15)= 475.23, adj-R²=0.73, and p <.001 for the MLR model; AICc= 3,267 and adj-R²= 0.853 for the GWR model; and ACIc= 3,173 adj-R²= 0.857 for the MGWR model. These adverse effects was significant in females, Latinos, and African American populations in the US. They remain poor, underserved, and with higher odds of developing cognitive decline, a clinical manifestation of Alzheimer’s disease and related dementias (ADRD). Moreover, the geospatial and geostatistical evaluation depicts a disproportionately higher T2DM prevalence among the said population and in US areas historically identified with higher Latino and African American populations. These results should help contextualize public health interventions optimizing human and economic resources in the implementation of culturally sensitive strategies of health promotion through a sustainable approach to positive social change.