Publications

BACKGROUND

Mobile medical clinics have been used for decades to provide primary and preventive care to underserved populations. While several studies have examined their return on investment and impact on chronic disease management outcomes in the Mid-Atlantic and East Coast regions of the United States, little is known about the characteristics and clinical outcomes of adults who receive care aboard mobile clinics on the West Coast region. Guided by the Anderson Behavioral Model, this study describes the predisposing, enabling, and need factors associated with mobile medical clinic use among mobile medical clinic patients in Southern California and examines the relationship between mobile clinic utilization and presence and control of diabetes and hypertension.

METHODS

We conducted a retrospective cohort study of 411 adults who received care in four mobile clinic locations in Southern California from January 1, 2018, to December 31, 2019. Data were collected from patient charts on predisposing (e.g., sex, race, age), enabling (e.g., insurance and housing status), and need (e.g., chronic illness) factors based on Andersen's Behavioral Model. Zero-truncated negative binomial regression was used to examine the association of chronic illness (hypertension and diabetes) with number of clinic visits, accounting for potential confounding factors.

RESULTS

Over the course of the 2-year study period, 411 patients made 1790 visits to the mobile medical clinic. The majority of patients were female (68%), Hispanic (78%), married (47%), with a mean age of 50 (SD = 11). Forty-four percent had hypertension and 29% had diabetes. Frequency of mobile clinic utilization was significantly associated with chronic illness. Patients with hypertension and diabetes had 1.22 and 1.61 times the rate of mobile medical clinic visit than those without those conditions, respectively (IRR = 1.61, 95% CI, 1.36-1.92; 1.22, 95% CI, 1.02-1.45).

CONCLUSIONS

Mobile clinics serve as an important system of health care delivery, especially for adults with uncontrolled diabetes and hypertension.

The use of the Confusion Assessment Method (CAM) for delirium assessment in real-life can be inconsistent. We examined the impact of a protocol on delirium screening and detection in hospitalized older adults using the CAM. We analyzed data from 32,338 admissions to a quaternary hospital between 2018 and 2022. We assessed the percentage of admissions screened for delirium, adherence to daily screening, positive screening, and overlap with ICD-10 coding. The percentage of admissions screened for delirium increased from 74% in 2018 to 98.7% in 2022. Adherence to daily screening was achieved in 24.5% of admissions, and the percentage of positive screenings fluctuated between 8.4% and 11.5%. Among the admissions with a delirium-related ICD-10 code, 32% had a positive screening, 62% were negative, and 6% remained unscreened. While implementing a protocol increased the proportion of admissions screened for delirium, adherence to daily screening and consistency of positive delirium screenings remain areas for improvement.