Clinic Type and Patient Characteristics Affecting Time to Resolution After an Abnormal Cancer-Screening Exam

Abstract

Research shows that multilevel factors influence health care delivery and patient outcomes. The goal of this study was to examine how clinic type (primary care clinic within an academic medical center (AMC) or federally-qualified health center (FQHC)) and patient characteristics influence time to resolution (TTR) among individuals enrolled in a patient navigation (PN) intervention. Data were obtained from the Ohio Patient Navigation Research Project, a group randomized trial in which 862 patients from 18 clinics in Columbus, OH participated. Patient's TTR after an abnormal breast, cervical, or colorectal test and the clinics' patient and provider characteristics were obtained. Descriptive statistics and Cox shared frailty proportional hazards regression models of TTR were used to analyze the data. The mean patient age was 44.8 years and 71% of patients were White. In models adjusted for study arm, the interaction between time and study arm and a clinic random effect, FQHC patients had a 39% lower rate of resolution than AMC patients (HR = 0.61, p = 0.004); college educated patients had an 87% higher rate of resolution than patients with less than a high school education (HR = 1.87, p = 0.0007); privately insured patients had a 79% higher rate of resolution than uninsured patients (HR = 1.79, p < 0.0001); patients with annual incomes ≥ $50,000 had a 51% higher rate of resolution than patients with annual incomes < $10,000 (HR = 1.51, p = 0.02); and there was a 4% increase in the rate of resolution for each five year increase in patient age (HR = 1.04, p = 0.004). After using multiple imputation to impute income and insurance status where missing, factors that potentially confounded the effect of clinic type on TTR were assessed using forward selection. After adjustment for patient insurance status, education level and age, clinic type was not significantly associated with TTR. Controlling for clinic type, patient insurance status and age were significantly associated with TTR (p = 0.005 and p = 0.01, respectively) and patient education level was marginally significant (p = 0.06). These results suggest that TTR among individuals participating in PN programs is influenced by multiple socioeconomic (SES) patient-level factors rather than clinic type. Consequently, PN interventions should be tailored to address SES factors that influence TTR within patient populations.