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

Abstract

Background Research shows that multilevel factors influence healthcare delivery and patient outcomes. The study goal was to examine how clinic type (academic medical center (AMC) or federally-qualified health center (FQHC)) and patient characteristics influence time to resolution (TTR) among individuals with an abnormal cancer screening test enrolled in a patient navigation (PN) intervention. Methods Data were obtained from the Ohio Patient Navigation Research Project, a group-randomized trial of 862 patients from 18 clinics in Columbus, Ohio. Patient’s TTR after an abnormal breast, cervical, or colorectal screening test and the clinics’ patient and provider characteristics were obtained. Descriptive statistics and Cox shared frailty proportional hazards regression models of TTR were used. Results The mean patient age was 44.8 years and 71% of patients were white. In models adjusted for study arm, FQHC patients had a 39% lower rate of resolution than AMC patients (P=0.004). Patient factors of having a college education, private insurance, higher income, and being older were significantly associated with lower TTR. After adjustment for factors that substantially impacted the effect of clinic type (patient insurance status, education level and age), clinic type was not significantly associated with TTR. Conclusions These results suggest that TTR among individuals participating in PN programs is influenced by multiple socioeconomic patient-level factors rather than clinic type. Consequently, PN interventions should be tailored to address SES factors that influence TTR. Impact These results provide clues regarding where to target PN interventions and the importance of recognizing predictors of TTR according to clinic type.

Effects of program scale-up on time to resolution for patients with abnormal screening mammography results

“…Further, TTR following an abnormal screening result followed patterns similar to national-level NBCCEDP data. (5, 12, 18, 23)…”

“…Other literature has found that TTR is associated with patient characteristics such as age, race-ethnicity, poverty level, insurance status, and BI-RAD category of abnormal screening result;(5, 12, 18) therefore, we also evaluated these variables as potential covariates, in addition to language preference and patient-reported health status (symptomatic/asymptomatic) at intake.…”

“…(15) At the system-level, the prevalence and types of barriers to timely follow-up may vary across clinics, even within integrated healthcare systems. (16, 17) Screening delivery programs able to address these multi-level factors (18) may be well-positioned to expand program reach (i.e. scale up) into similarly situated communities.…”