Objective: To examine primary care (PC) team members' characteristics associated with video use at the Veterans Health Administration (VA).
Methods: VA electronic data were used to identify PC team characteristics associated with any video-based PC visit, during the three-year study period (3/15/2019-3/15/2022). Multilevel mixed-effects logistic regression models on repeated yearly observations were used, adjusting for patient- and healthcare system-level characteristics, and study year.
Objective: To evaluate racial and ethnic differences in patient experience among VA primary care users at the Veterans Integrated Service Network (VISN) level.
Data Source And Study Setting: We performed a secondary analysis of the VA Survey of Healthcare Experiences of Patients-Patient Centered Medical Home for fiscal years 2016-2019.
Study Design: We compared 28 patient experience measures (six each in the domains of access and care coordination, 16 in the domain of person-centered care) between minoritized racial and ethnic groups (American Indian or Alaska Native [AIAN], Asian, Black, Hispanic, Multi-Race, Native Hawaiian or Other Pacific Islander [NHOPI]) and White Veterans.
J Am Med Dir Assoc
February 2024
Objective: To examine the role of patient-perceived access to primary care in mediating and moderating racial and ethnic disparities in hypertension control and diabetes control among Veterans Health Administration (VA) users.
Data Source And Study Setting: We performed a secondary analysis of national VA user administrative data for fiscal years 2016-2019.
Study Design: Our primary exposure was race or ethnicity and primary outcomes were binary indicators of hypertension control (<140/90 mmHg) and diabetes control (HgbA1c < 9%) among patients with known disease.
Context: Surges in the ongoing coronavirus-19 (COVID-19) pandemic and accompanying increases in hospitalizations continue to strain hospital systems. Identifying hospital-level characteristics associated with COVID-19 hospitalization rates and clusters of hospitalization "hot spots" can help with hospital system planning and resource allocation.
Objective: To identify (1) hospital catchment area-level characteristics associated with higher COVID-19 hospitalization rates and (2) geographic regions with high and low COVID-19 hospitalization rates across catchment areas during COVID-19 Omicron surge (December 20, 2021-April 3, 2022).