Date of Completion


Embargo Period



public health; mHealth; risk screening; urban health; health disparities; health information technology; screening; primary care

Major Advisor

Robert A. Aseltine

Associate Advisor

Nicholas Warren

Associate Advisor

Bruce Gould

Field of Study

Public Health


Doctor of Philosophy

Open Access

Open Access


Background: Urban, underserved populations experience considerable disparities in the screening, prevention, and treatment of chronic disease, including behavioral health disorders. Screening patients for such problems is widely recommended, yet is challenging to do in a brief primary care encounter, particularly for this complex patient population. Electronic risk screening provides one method of eliminating disparities in the identification of risks, while limiting burden on providers.

Objectives: 1) Screening data were compared to EHR data to assess differences in the prevalence of 12 risk factors and clustering of risks; 2) Patients screening positive for behavioral health problems were followed to determine rates of follow-up care, and the rate of newly identified cases in the intervention group; and 3) Successes and challenges in the implementation process were reviewed.

Design: A quasi-experimental design was used to assess prevalence rates of 12 health risks using an electronic tablet-based screening questionnaire.

Sample: Intervention (n=473) and control (n=260) patients were selected from two urban, safety net primary care practices in Connecticut, the majority of whom were non-white and using public insurances.

Results: There was a statistically significant increase in the identified prevalence rates of health risks in the intervention group compared with the control, but most patients had more than one medical risk. For behavioral health disorders in one clinic, follow up rates were statistically significantly higher in the intervention group relative to controls, but were low overall. While the risk screening intervention was largely successful, challenges included: integration of technological environments, limited clinical resources, and barriers in clinic workflow.

Conclusions: This tablet-based electronic screening tool identified higher rates of disorders than have been previously reported for this population. Electronic risk screening using patient-reported outcome measures offers an efficient approach to improving the identification of behavioral health problems, improving rates of follow-up care, and establishing population public health surveillance. Study-based recommendations are made for the successful future implementation of mHealth screening, including: integration of technological systems, establishment of a critical care pathways, inclusion of all levels of staff on workflow process development, identification of a project champion, and development of standing orders to improve follow up.