Social determinants of health (SDOH) represent the broad, systemic conditions—such as socioeconomic status, education, neighborhood environment, and access to services—in which people are born, grow, live, work, and age, fundamentally shaping their overall health and well-being. Within this macro framework, unmet social needs (also termed health-related social needs) are the specific, actionable manifestations that individuals encounter when these systemic conditions are unfavorable or insufficient, including challenges like food insecurity, housing instability, transportation barriers, and limited access to essential services. When these individual-level needs remain unaddressed, they have a direct, measurable, and adverse effect on individual health outcomes and the overall quality of care received. Systematic detection of these unmet social needs is therefore critical, especially for historically marginalized populations that face significant health and socioeconomic challenges. While traditional paper-based methods for screening have historically struggled with scalability, documentation issues, resource demands, and inefficient follow-ups, the concurrent rise of digital health technologies (DHTs)—such as mobile applications, electronic health records (EHRs), and web-based platforms—presents scalable and efficient opportunities to identify and detect these critical needs. Integrating this social needs data into EHRs not only enables health care providers to better track changes in patients’ circumstances but also facilitates more personalized care plans, enhances patient engagement, and streamlines referral processes to community resources.
The primary objective of this scoping review was systematically defined through two main aims: (1) to examine the types of DHT interventions documented in the literature for screening and identifying unmet social needs among populations facing health and socioeconomic challenges, and (2) to explore the associated trends, effects, challenges, and limitations related to the use of DHTs for identifying and addressing these needs. The review followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. The eligibility criteria were structured using the PICO framework, focusing on populations that prospectively reported one or more social needs, and interventions involving technology (e.g., tablets, mobile apps, chatbots, kiosks, computers, and patient portals) for screening. The authors conducted a comprehensive search across major scientific databases, including MEDLINE, Embase, Scopus, ACM Digital Library, and Web of Science, for studies published between 2010 and 2025. The stringent inclusion criteria required studies to feature prospectively collected data, report social need components, and demonstrate a DHT-based screening method. After an extensive selection process, which included the removal of 1180 duplicates and the systematic review of titles, abstracts, and full texts, 14 studies were included for final data extraction.
The findings reveal a limited but rapidly evolving landscape of technological applications. The majority of the included studies were conducted in the United States (71%), with the remainder occurring in Canada, Spain, and the United Kingdom. Participant sample sizes varied widely, ranging from 13 to 826 patients. The most frequently assessed social needs were food insecurity (71% of studies) and housing instability (64%), followed by health care accessibility (57%) and transportation (50%). In terms of technology, tablet PC surveys were the most common DHT used (43%), serving as the platform for self-assessment surveys. Other less common, but highly innovative, DHTs were also identified, including chatbots (14%), software/web apps (14%), and text messaging services (14%). These digital tools were deployed across diverse groups, such as refugees using computer-assisted psychosocial risk assessment and patients in emergency departments. Notable novel approaches included the use of chatbots leveraging natural language processing to enhance user engagement and sophisticated software designed for multidimensional risk appraisal in older adults. Across the studies, the most common outcome reported was the ratio or percentage of total patients screened (79%).
DHTs demonstrate clear opportunities for enhancing social needs screening. They can significantly ease the screening process, leading to an increased number of completed screenings. For example, one study observed that implementing tablet-based screening increased administration rates from 45% to 90%. Furthermore, for sensitive topics, patients may feel greater comfort self-reporting information via a DHT, potentially avoiding direct human interaction. Conversational DHTs, such as chatbots, specifically showed promise by improving screening engagement and comprehension of social needs content, particularly among participants with low health literacy. Personalization features—including language options and location awareness—were noted as contributors to the adoption of these tools, especially within marginalized groups. However, the review also highlights several critical challenges and limitations. The effectiveness of DHT screening yielded mixed outcomes, and concerns were consistently noted regarding the limited generalizability due to small sample sizes and single-site study designs. Major technical and practical barriers included persistent integration issues with existing medical record systems (EHRs) and difficulties in documentation and efficient management of positive screenings. Perhaps most crucially, the inability to track resource map use or assess successful linkages to community-based organizations after screening was frequently cited as a barrier to determining long-term impact. The authors conclude that while DHTs are playing a pivotal role in improving the identification of unmet social needs, their implementation must be thoughtful to prevent the exacerbation of existing health disparities. Future research must shift focus to systematically tracking the complete care continuum, from initial identification to the successful reception of services and subsequent improvements in health and social outcomes.
Reference: Sezgin, E., Jackson, D. I., Boch, S., Davenport, M., Skeens, M., Dolce, M., Frankin, B., Militello, L. K., Lyman, E., & Kelleher, K. (2025). Digital Health Technologies for Screening and Identifying Unmet Social Needs: Scoping Review. Journal of Medical Internet Research, 27, e78793. https://doi.org/10.2196/78793