Digital transformation on patient experience and engagement: patient-centered strategy and the role of leadership support for innovation in Ugandan health facilities - Hannington Businge; James Kaconco; Jennifer Rose Aduwo (Journal of Health Organization and Management, 2026)
Purpose This study examines how managerial perception of digital transformation (DT), patient-centered strategy (PCS) and leadership support for innovation (LSUP) relate to patient experience and engagement (PXE) in Ugandan health facilities. Design/methodology/approach Drawing on the Technology–Organization–Environment (TOE) framework and Dynamic Capabilities Theory (DCT), the study adopts a mixed-methods design. Quantitative data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) for managerially perceived patient-centered outcomes, complemented by qualitative interviews from managers and patients to contextualize and explain the statistical relationships. Findings The results show that the direct effect of digital transformation on patient experience and engagement is not statistically significant (β = 0.207, p = 0.078). There is a strong, statistically significant effect of digital transformation on patient-centered strategy (β = 0.600, p < 0.001). Patient-centered strategy positively and significantly affects patient experience and engagement (β = 0.306, p = 0.046). Patient-centered strategy plays a meaningful mediating role in the relationship between Digital Transformation and Patient Experience. While leadership support for innovation on patient experience and engagement does not moderate the relationship (ß = 0.112, p = 0.294). Qualitative findings reveal that digital technologies primarily create value by enabling patient-centered care redesign rather than directly shaping patient perceptions. Research limitations/implications Despite offering valuable insights into the effects of digital transformation, patient-centered strategy and leadership support for innovation on patient experience and engagement in Ugandan health facilities, this study has several limitations. First, the cross-sectional design limits the ability to establish causal relationships, as the structural model identifies associations rather than causal effects; therefore, longitudinal studies are needed to capture the dynamic influence of digital adoption and strategic interventions over time. xD; xA; A limitation is the small, purposively selected sample of 67 senior leaders, which constrains statistical power and generalizability. Although supported by 48 key informant interviews from senior leaders and patients’ perspectives were incorporated. Though PLS-SEM accommodates small samples, caution is warranted in hypothesis testing (Hair et al., 2022). Although patient qualitative interviews strengthened contextual understanding and validation of findings, future studies could further enhance measurement precision by incorporating large-scale quantitative patient-reported outcome measures and patient satisfaction surveys directly into the structural model. Nonetheless, such samples are acceptable for exploratory digital health research, but findings require validation using larger, multi-stakeholder datasets (Dwivedi et al., 2023). Second, the study relied largely on self-reported data from healthcare providers and administrators, which may introduce response bias or social desirability effects. Although patient experience and engagement were conceptually addressed, patient-reported outcomes were not consistently measured, potentially limiting generalizability. Third, while Ugandan health facilities represent a relevant low- and middle-income country (LMIC) context, variations in infrastructure, digital literacy and organizational readiness may restrict the applicability of the findings to other LMIC settings. The non-significant results for H1 and H5 further suggest that technology and leadership effects may vary under different institutional conditions. Additionally, the study examined a limited set of variables, excluding factors such as organizational culture, staff workload, policy incentives and patient socioeconomic conditions. Finally, practical implementation challenges such as limited training, financial constraints and infrastructural gaps may affect the translation of these findings into practice, highlighting the need for context-sensitive implementation and further research. Practical implications The findings suggest that healthcare organizations in resource-constrained contexts should align digital initiatives with patient-centered strategies and leadership practices to realize experiential gains. Social implications By demonstrating how digital transformation and patient-centered strategies influence engagement and experience, the study has broad societal relevance. Effective deployment of digital health solutions, coupled with patient-focused organizational strategies, can improve access, equity and quality of care for underserved populations in LMICs. Enhanced patient engagement fosters trust, satisfaction, and adherence to treatment, ultimately contributing to better population health outcomes. Moreover, a culture of patient-centered innovation supports community empowerment, strengthens health system responsiveness and promotes social well-being, thereby addressing systemic healthcare disparities. Originality/value The study advances health management literature by integrating TOE and DCT to explain how digital transformation creates patient-centered value in LMIC healthcare settings.