This qualitative study used semistructured interviews to collect data following ethics approval (2023‐006) from the institutional review board of Stevens Institute of Technology. The interview questions focused on identifying challenges and needs in digital health for the care of children with medical complexity (Multimedia Appendix 1). Participation in the study was entirely voluntary, and participants were informed that the data would be reported anonymously. Data access was strictly limited to the study researchers. Each participant was given a US $30 Amazon gift card for completing the interview. We structured our methodology in alignment with the COREQ (Consolidated Criteria for Reporting Qualitative Research) checklist to ensure transparency [15]. The study team received verbal consent from all participants.

This qualitative study explored parents’ perspectives on how digital health technology supports them in providing care for children with medical complexity, and this study also has potential to shape the path for future enhanced digital health solutions designed for primary caregivers of children with medical complexity. Participants were recruited through the Statewide Parent Advocacy Network (SPAN) based in New Jersey [16]. SPAN is a community organization for children with special needs and children with medical complexity. It was founded by parents of children with special needs in 1987 to provide support to the families of these children and of children with medical complexity [16]. The staff has supported more than 500 families of children with medical complexity in New Jersey for many years, especially those from underserved communities. We designed a brochure and worked with SPAN members to distribute it to families of children with medical complexity from underserved communities who lacked access to medical services. Participants were family members identified as the primary caregivers for children with medical complexity; most were the children’s parents. We conducted semistructured interviews with primary family caregivers of children with medical complexity from underserved communities between October 2023 and March 2024. In this study, “underserved communities” refers to families who face structural and access-related barriers to specialized care for children with medical complexity, including provider shortages, geographic constraints, fragmented health systems, and challenges navigating services [17]. These barriers are often substantial enough that families rely on nonprofit or community-based organizations (SPAN) for additional support, care coordination, and resource access beyond what is available through the formal health care system. We also used snowball sampling techniques by asking for referrals from the participants. We used the theoretical data saturation approach to determine the final sample size [18]. Data saturation occurs when further interviews do not yield new themes or reveal new subthemes within the existing themes [19,20]. All interviews were conducted over Zoom (Zoom Video Communications) and were audio recorded.

An inductive, reflexive thematic analysis was conducted, with a codebook developed iteratively during analysis to support analytic transparency rather than to impose a priori coding structures. We used a constant comparative approach to collect and analyze data simultaneously. Transcripts were analyzed using inductive thematic analysis. The inductive approach focuses on identifying themes as they emerge from the data to understand the needs of children with medical complexity regarding technology preferences and challenges [21]. Inductive thematic analysis ensures that the themes are representative of participant responses and not shaped by a predefined hypothesis [22]. We used a line-by-line coding method [23]. The first author (FE) coded the data and created a codebook, which was then reviewed, refined, and validated by the second author (OA). We identified themes by comparing situations, suggestions, and experiences from the same and different individuals and gradually refined the coding schema [24]. The coding was performed using Microsoft Excel, which included both inductive analysis and participant demographics.

Participant demographics were documented to describe the sample. Table 1 presents a summary of the demographic characteristics of the participating caregivers and their children with medical complexity.

Most participants (15/19, 78.9%) were from New Jersey. However, through snowball sampling, in which existing participants referred others to the study, additional caregivers from California, Alaska, Colorado, and New York were included (4/19, 21.1%). Most (12/19, 63.2%) were African American, with others identifying as Hispanic (3/19, 15.8%) or White (4/19, 21.1%) individuals. Most caregivers were aged between 30 and 49 years. The study included 52.6% (10/19) female and 47.4% (9/19) male participants. All caregivers had 1 child with medical complexity except for one caregiver who had twins with medical complexity. The educational backgrounds of the participants included 10.5% (2/19) with master’s degrees, 73.7% (14/19) with bachelor’s degrees, and 15.8% (3/19) who had completed high school. Finally, most of the children (15/19, 78.9%) were boys. The largest age group was 12 to 14 years.

An inductive thematic analysis of the qualitative data revealed 2 primary themes related to current experiences with technology in the care for children with medical complexity and unmet needs that could be addressed through digital solutions. These themes were (1) virtual care and (2) consumer mobile health (mHealth) apps.

Caring for children with medical complexity involves navigating an extensive network of health care providers—primary care clinicians, specialists, and nurses—across multiple settings, including the home, school, clinics, and hospitals. This fragmentation increases the risk of care gaps over time [26-28]. Prior studies have shown that parents of children with medical complexity face multiple barriers to communication and information accessibility, including difficulties scheduling appointments; coordinating among health care providers; and obtaining clear, actionable health information [29-32]. Many are also tasked with administering complex medication regimens without formal training or having children with medical complexity–specific tools to ensure accuracy [33]. These challenges are even more pronounced for families in underserved communities.

Underserved populations who lack access to proper health care infrastructure are rapidly increasing their adoption of digital health tools to address gaps in care by overcoming barriers such as language and geography [34,35]. A previous study shows that further research is needed to evaluate the effectiveness of mHealth and virtual care and their impact on health care delivery in underserved communities [36]. In addition, digital health tools for the care for children with medical complexity should be shaped by the voices and experiences of families on the front lines of care to build systems that work for children with medical complexity [37]. A unique aspect of this study is its focus on children with medical complexity in underserved communities as a first step, revealing how caregiving challenges intersect with the realities of digital health use with the goal of advancing user-centered digital health solutions for parents of children with medical complexity.

Telehealth has been suggested as a possible way to address health care disparities among underserved urban populations who are often unable to access health care in a timely manner due to low physician-to-population ratios and limited specialty care [38]. Accordingly, telehealth is viewed as a strategy for improving access to care for rural and underserved populations by connecting them with primary care providers, specialists, and mental health services [39]. While virtual care offers a promising avenue for overcoming geographic and resource-related barriers [40], our findings demonstrate that it can also shift significant responsibility onto caregivers. Parents described the mental and emotional overload of acting as the primary information conduit between child and health care provider, particularly during remote visits.

Therefore, health literacy is essential for parents of children with medical complexity to make informed decisions and manage their children’s specialized care needs [41,42]. Low parental health literacy has been associated with limited health knowledge and poorer child health outcomes [43,44]. Consistent with this, our participants emphasized that integrating user-friendly vocabulary and parent-centered resources within telehealth platforms can reduce the cognitive burden on parents by enabling them to interpret information immediately while communicating with health care providers via telehealth and actively participate in their children’s care.

While parental understanding supports a child’s care, providers also need to adopt strategies that allow them to communicate effectively with nonverbal children with medical complexity during telehealth appointments. A previous study reported that medical providers’ communication strategies often failed to address the needs of nonverbal children with medical complexity, and that strategies such as warmly greeting patients and introducing themselves were sometimes skipped based on the false assumption that these patients could not engage in meaningful communication, which in turn diminished trust between patients and medical providers [45]. This supports our findings that telehealth tools need to be designed as child friendly and support nonverbal children with medical complexity to facilitate communication between patients and health care providers. These considerations were identified as critical for developing an inclusive telehealth tool and are often overlooked in current platforms.

In addition, mHealth is a type of digital health that refers to the use of mobile technologies to deliver health services. It is particularly valuable for improving health outcomes in patients with chronic conditions [12]. Families of children with medical complexity commonly struggle to accurately recall symptoms, clinical events, or over-the-counter medication use, highlighting the need for mHealth tools to document health events outside clinical settings [46]. Regarding caregiver needs, our participants sought mHealth solutions to reduce daily burden and empower decision-making. They envisioned tools consolidating digital health notebooks and medication management. These findings align with those of previous research on the potential of mHealth to empower patients through personalized, timely support [47,48] and integrate digital tools across home, health care, and school systems [49-52]. The desire for synchronized health technology highlights a critical gap in current systems as caregivers of children with medical complexity must repeatedly communicate the same information across providers, increasing workload and the risk of errors.

In addition to supporting day-to-day care, participants emphasized the need for digital technologies that facilitate decision-making for children with medical complexity as they transition to adult care. Few studies have examined the effectiveness of digital health interventions to assist adolescents and young adults with chronic conditions in facilitating self-management and transitioning to adult care [53,54]. There is an interest in using mHealth tools to facilitate the transition to adult care, but early co-design with users and collaboration with health care providers are needed to address varying preferences and needs [53].

Figure 1 summarizes the key challenges that parents of children with medical complexity face—managing complex needs, accessing specialized resources, and coping with emotional and physical burdens—that emerged from our findings. We also developed and listed targeted solutions and recommendations for researchers, health care providers, and software engineers to develop effective, user-friendly systems that better support families.

As part of the user-centered design approach, we developed key digital health functionalities to address participants’ needs and bridge gaps in the care for children with medical complexity (Table 4). Effective mHealth tools begin with a user-centered design approach that engages end users throughout development to ensure functionality, usability, and relevance [55-57]. Guided by this principle, we assessed the needs of parents of children with medical complexity and translated them into recommended mHealth platforms, including a description of their functionalities to inform the development of actionable software solutions. Technology developers must also ensure compliance with HIPAA (Health Insurance Portability and Accountability Act) alongside robust security, reliability, and usability in collaboration with health care leaders and policymakers [58-60]. In addition, expanding access to digital health tools in underserved communities requires investment in telehealth infrastructure, mobile-friendly screening tools, and community outreach programs that educate caregivers on how to use these technologies effectively [61].

To our knowledge, this is the first study to examine the needs and challenges related to digital health technology among parents of children with medical complexity in underserved communities. A key strength of this study is the inclusion of a relatively large sample of caregivers from underserved communities, a group that is frequently underrepresented in qualitative research on children with medical complexity. Although participants were recruited from underserved communities, the relatively high educational attainment among caregivers in our sample may limit the generalizability of the findings to caregivers with lower levels of education. Another limitation of this study is its reliance on Zoom interviews, which may have excluded participants with limited access to technology or who were uncomfortable with digital platforms. This could result in a sample that does not fully capture the experiences of parents who might prefer face-to-face communication.

Our study reinforces that parents in underserved communities are not resistant to digital health; rather, they are eager for solutions that are trustworthy, accessible, and tailored to the care of children with medical complexity. By addressing the intersecting barriers of medical complexity and systemic inequity, health care systems and technology developers can design digital tools that meaningfully enhance care coordination, reduce caregiver burden, and improve health outcomes. Future work should focus on co-design approaches with families of children with medical complexity, evaluation of tailored interventions, and longitudinal research to examine impacts on care transitions and health care use.