A cluster-randomized trial of a primary care informatics-based system for breast cancer screening

Abstract

Background: Information technology offers the promise, as yet unfulfilled, of delivering efficient, evidence-based health care.

Objective: To evaluate whether a primary care network-based informatics intervention can improve breast cancer screening rates.

Design: Cluster-randomized controlled trial of 12 primary care practices conducted from March 20, 2007 to March 19, 2008.

Patients: Women 42-69 years old with no record of a mammogram in the prior 2 years.

Interventions: In intervention practices, a population-based informatics system was implemented that: connected overdue patients to appropriate care providers, presented providers with a Web-based list of their overdue patients in a non-visit-based setting, and enabled "one-click" mammography ordering or documented deferral reasons. Patients selected for mammography received automatically generated letters and follow-up phone calls. All practices had electronic health record reminders about breast cancer screening available during clinical encounters.

Main measures: The primary outcome was the proportion of overdue women undergoing mammography at 1-year follow-up.

Key results: Baseline mammography rates in intervention and control practices did not differ (79.5% vs 79.3%, p = 0.73). Among 3,054 women in intervention practices and 3,676 women in control practices overdue for mammograms, intervention patients were somewhat younger, more likely to be non-Hispanic white, and have health insurance. Most intervention providers used the system (65 of 70 providers, 92.9%). Action was taken for 2,652 (86.8%) intervention patients [2,274 (74.5%) contacted and 378 (12.4%) deferred]. After 1 year, mammography rates were significantly higher in the intervention arm (31.4% vs 23.3% in control arm, p < 0.001 after adjustment for baseline differences; 8.1% absolute difference, 95% CI 5.1-11.2%). All demographic subgroups benefited from the intervention. Intervention patients completed screening sooner than control patients (p < 0.001).

Conclusions: A novel population-based informatics system functioning as part of a non-visit-based care model increased mammography screening rates in intervention practices.

Trial registration: ClinicalTrials.gov; NCT00462891.

Figure 1

CONSORT diagram for cluster randomized trials depicting the flow of study practice clusters and patients through eligibility assessment, randomization, intervention, and outcome analysis.

Figure 2

Kaplan-Meier curve of time to mammography completion during the 1st year of follow-up among women overdue for breast cancer screening in intervention and control groups. The time from the start of the study to the point when 20% of patients had completed screening is depicted by the horizontal line. The difference between the intervention and control populations is depicted by the vertical lines.

Figure 3

Adjusted odds ratios and unadjusted rates for breast cancer screening in intervention and control groups in patient and practice subgroups. Odds ratios compare patients in intervention and control groups controlling for patient age, patient-physician connectedness, race/ethnicity, English language proficiency, practice type (health center vs non-health center), and number of months since last practice visit using cluster analysis with generalized estimating equation methods. For each subgroup analysis, the analogous covariable was removed from the model.