The purpose of this scoping review was to identify and evaluate studies investigating the effectiveness and implementation strategies of digital technologies integrated with EHR to improve medication-related outcomes and promote health equity among hospitalised adults. The review was guided by two objectives: first, to appraise studies that evaluate the effectiveness of EHR-digital technology in hospital medication management, specifically examining medication-related and health equity outcomes.; second, to identify and analyse the factors influencing the implementation of EHR-digital technology within complex hospital systems.

Implications for Literature

Analysing 23 studies in 11 countries from 2008 to 2022, it was found that the studies used various research methodologies and investigated digital technologies such as CDSS, predictive analytics, real-time screening, and surveillance within EHR systems. These technologies demonstrated potential to reduce ADE, medication errors, medication discrepancies, potentially inappropriate medications, improve prescription accuracy, and optimise patient safety. Empirical support from recent meta-analyses and systematic reviews supports the efficacy of electronic prescribing, computerised order entry, and CDSS interventions [64,65,66].

The outcome measures were multifaceted and included metrics such as the rate of alert overrides, continuation of high-risk medication prescriptions, acceptance rates of automated recommendations, and the positive predictive value of triggers for the identification of ADE. The lack of a consistent definition of medication harm led to various approaches in its measurement and reporting [67, 68]. This inconsistency highlights the need for standardised definitions when developing EHR-digital technologies for medication management to enable more accurate reporting and comparison across studies.

Although these studies highlighted the role of EHR-digital technologies in improving medication safety, they also indicated the need for further research and system refinements. Issues such as alert fatigue from clinically irrelevant alerts, workflow assimilation, unstructured data, data quality, stakeholder approval, and the need for continuous staff training and support were identified [69,70,71]. Addressing these challenges is crucial to realise the full potential of these technologies. A comprehensive understanding and evaluation of these technologies in clinical settings is essential, focusing on factors that affect the trust of healthcare professionals, such as system design in alignment with clinical workflows, the clinical relevance of alerts, and adaptability to various clinical settings [72].

One of the key findings from this scoping review is the significant gap in focus on health equity. Despite the inclusion of 23 studies examining EHR-digital technologies and their effectiveness in medication management, none of these papers explored health and social determinants at any phase of the EHR-digital technology development, implementation, and evaluation. This represents a critical knowledge gap regarding the impact of these technologies on health equity. To address this, future studies must prioritise strategies and policies to leverage digital health solutions for equitable health outcomes in diverse patient populations [73].

Effectiveness of EHR-digital Technologies in Medication Management

The integration of digital technologies within EHR systems is a much-needed area of research, with CDSS, real-time surveillance, predictive analytics, and AI driving the advancement and transformation of medication management. This review of 23 studies demonstrates the adaptability of EHR-digital technologies to various research settings, objectives and highlights the complexity of comparing and synthesising findings.

Effective digital health technologies are contingent upon careful consideration of design, integration, and iterative improvements, informed by clinical feedback and ongoing technology advancements. A tailored and customised approach is necessary, as a single solution may not be universally applicable in different clinical settings.

The complexity of EHR-digital technologies is further complicated by the integration of internal and third-party developed CDSS [74, 75]. This poses challenges for seamless integration, as digital tools may not always align perfectly with the native functionalities of EHR systems [74, 75]. Given the persistent nature of medication harm, the development, implementation and evaluation of CDSS has become a moving target, adding layers of complexity for healthcare providers that want to keep up with the growing demands, evolving standards and obtaining the most benefits for patients from these digital tools [74, 75].

A persistent issue is the lack of standardisation in alert mechanisms, leading to inconsistencies in the usability and clinical relevance of alerts across different systems. Although some systems seamlessly integrate into healthcare professional decision-making processes, others contribute to alert fatigue, which can cause healthcare providers to overlook critical alerts [76]. Alert algorithms need to be refined to ensure they are sensitive and specific, minimising the noise of irrelevant alerts while maximising the signal of clinically relevant information. Effective integration and implementation of digital alert systems are crucial, requiring seamless interoperability, end-user training, and a culture of safety that supports technology-enhanced clinical judgment [1, 4, 8].

The potential of digital alert systems to predict and prevent medication errors represents a significant technological advance, however, improving prediction accuracy requires an iterative design process. This process should incorporate clinical feedback, ongoing performance evaluation, and the application of AI and ML algorithms capable of evolving with experience [77].

Standardisation is also essential to define medication harm, harm classification and measurement tools to enable accurate and timely identification, monitoring, and evaluation, thus improving the reliability of integration of healthcare technology [78].

The integration of AI into EHR has the potential to revolutionise medication management using advanced algorithms and machine learning to process complex patient data. These tools can detect drug interactions, assess medication safety, and offer personalised clinician recommendations [79]. However, the application of AI in healthcare needs to mitigate algorithmic bias, which can exacerbate health inequities [80, 81]. The use of diverse datasets that incorporate digital and social health determinants is vital to tackle such biases [80, 81]. Moreover, the inclusion of standardised disability data is essential in the development and validation of AI technologies, ensuring equitable health outcomes [80, 81].

Implications for Health Equity

The potential of digital healthcare technologies to enhance health equity is significant yet underexplored, with the literature exhibiting a critical research gap. A recent review highlighted a study conducted in an intensive care unit (ICU), which used a commercial EHR system to investigate the relationship between patient-identified race and the frequency of CDSS alert overrides, with a focus on drug-drug interaction alerts [74]. This study found a 1% higher rate of CDSS alert overrides for African-American patients compared to Caucasian patients (82.27% vs. 81.30%) [74]. This finding, although not fully explained, suggests that patient demographics may influence alert response behaviours, potentially influenced by factors such as polypharmacy or complex infusion regimens common in ICUs [74].

To achieve equity through digital innovations, intentional and informed efforts are needed. The Digital Health Equity Framework (DHEF) and the Health Equity Impact Assessment (HEIA) provide models for designing and evaluating digital health interventions with an equity focus [82, 83]. A study on a digital equity dashboard in an emergency department exemplifies how EHR data can inform interventions to reduce care disparities by analysing demographic and clinical variables [84].

Similarly, a digital equity dashboard for medication harm within EHR systems could highlight inequities across age, race, ethnicity, language, sexual orientation, gender identity, disability, and socioeconomic status. Engaging communities disproportionately affected by health inequities is crucial, as is incorporating their perspectives into research and monitoring digital technology performance to mitigate bias [33, 85, 86].

Interdisciplinary collaboration is essential to create digital health solutions that are not only technically robust, but also socially responsible and culturally sensitive. Health policy should address ethical considerations and allocate resources to technologies aimed at reducing health disparities, ensuring equitable access to technological advances [73].

Future research must use methodologies that assess the impact of digital technologies on diverse populations, including participatory design and longitudinal studies [87]. An international perspective is vital to share knowledge and strategies to address health inequities globally [88]. Ultimately, determining whether EHR-integrated digital tools can mitigate or exacerbate inequities in hospitalised patients is crucial to achieving the promise of technology in promoting equitable health outcomes.

Factors Influencing Implementation in Hospital Systems

Implementing EHR-digital technology in hospitals is complex and involves more than just the technology itself. Institutional readiness, staff proficiency, organisational culture, and commitment to digital initiatives are crucial to success. Implementation requires a holistic strategy that integrates training, support, and alignment with clinical objectives.

The CFIR reveals strengths and areas for improvement. While research often highlighted the novelty of technology [41,42,43,44,45,46, 48,49,50,51, 54,55,56,57,58,59,60, 62, 63], there was a deficit in evidence-based practice support, questioning the reliability and generalisability of interventions [46, 48, 51, 54, 55, 60, 63].

The advantages and adaptability of digital technologies were well documented [41,42,43,44,45, 49, 51, 54,55,56,57,58,59,60, 63], however, EHR-digital technology design and cost considerations, which are critical for user adoption and financial viability, were not adequately addressed. It is crucial to evaluate the cost effectiveness of these systems using extensive research methods, as the economic aspects of incorporating digital technologies into EHR systems can be substantial and diverse, potentially impeding further innovation.

Studies typically focused on IT infrastructure and neglected the influence of factors such as critical incidents, local attitudes, policies, relational dynamics, and resources. Organisational culture, particularly in terms of equity and centeredness, whether it is recipient, deliverer, or learning-oriented, was rarely discussed [39, 41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63, 89].

Effective internal communication is vital for technology integration. However, external factors, such as policies and laws, which have a significant impact, were often overlooked. Additionally, the variability in individual capabilities and motivations indicates the need for more customised EHR-digital technology implementation approaches.

Quality Assessment

The quality assessment of the studies indicates some significant strengths, such as clear research objectives that provide a solid foundation for the study focus and well-defined interventions and outcome metrics that enhance the reproducibility of the research and the credibility of the results. However, there are also some concerns, including potential selection bias due to ambiguous representativeness of study participants, and insufficient details on the inclusion of eligible participants and sample size calculation, which question the generalisability and applicability of the findings. Therefore, it is essential to develop improved reporting standards to address these gaps and strengthen the validity of future research efforts [90, 91].

Challenges and Limitations in the Integration of EHR-Digital Technology

Integrating digital technologies into EHR systems is challenging, as highlighted in the included studies. Key challenges include alert fatigue, usability issues in the interface, and the complexities of integrating digital technologies into established clinical workflows. The exploration of results is limited by methodological shortcomings, such as the overestimation of positive predictive values due to inconsistent definitions of medication harm [