The 2023 Global Ministerial Summit on Patient Safety declared “If it’s not safe, it’s
not care,” highlighting the crucial role of patient safety in healthcare. The Global
Patient Safety Action Plan 2021–2030 of the World Health Organization (WHO) underscores
the need for national policies and strategies for patient safety, surveillance, and
learning systems for safety incidents, and improved healthcare practices, technologies,
and medication use [1]. Recent technological advancements provide new opportunities
for improving patient safety by standardizing and streamlining clinical workflows
and reducing errors and costs by digitizing healthcare processes [2–4]. However, poorly
designed or implemented technological approaches can instead actually increase the
burden on clinicians, with alert fatigue and failure to respond to notifications by
overworked clinicians leading to more medical errors [5–7]. Various frameworks, models,
and methods have been developed to guide how to understand, design, and implement
technology, and find a balance between the benefits and successful adoption by clinicians.
This review evaluated the frameworks and models used to evaluate the impact of safety
technology use and adoption through change management in acute care settings.
Multiple theoretical and conceptual models have been introduced and used in health
informatics to understand and explore the relationship between clinicians and technology
and also to evaluate and assure the impact and successful adoption of technology in
practice. We identified several frameworks that were hybrid constructs of the technology
acceptance model (TAM), theory of planned behavior and intrinsic motivation, hybrid
theory of diffusion of innovation, sociotechnology analysis, organization theory,
and health-organization-technology (HOT)-fit model. These frameworks are based on
various theories such as those of planned behavior, reasoned action, sociotechnology,
longitudinal acceptance, diffusion of innovation, organization, Bandura’s social learning,
and intrinsic motivation. Focusing on the frameworks and models used frequently for
safety technology, we reviewed and compared seven frameworks and their constructors
or concepts that affected the ultimate purpose of improving patient clinical outcomes
and safety. We also added an introduction on the maturity models that are getting
attention in practice.
1. TAM and Diffusion of Innovation
The TAM has been widely used as a framework for understanding how users adopt and
use new technology [8]. It is rooted in the theories of planned behavior and reasoned
action and posits that user intentions in using technology are based on perceived
ease of use and usefulness. The TAM has been adapted to improve its accuracy by incorporating
factors such as task relevance, personal, organizational, and social factors, intrinsic
and extrinsic motivation, compatibility, attitude, and longitudinal usage. Another
theory, diffusion of innovation [9], focuses on how new technologies are adopted and
spread throughout communities and societies. The theory recognizes five adoption stages:
knowledge, persuasion, decision, implementation, and confirmation. Different factors
in each stage influence whether an individual or group will adopt the new technology,
including perceived advantages and disadvantages, social norms and networks, and its
complexity. Diffusion of innovation has been widely applied to understand the adoption
and use of healthcare technologies, including Electronic Health Records (EHRs), telemedicine,
and mobile health apps. Researchers have used this theory to identify barriers and
facilitators to adoption and to develop strategies for promoting adoption and use.
2. UTAUT
The Unified Theory of Acceptance and Use of Technology (UTAUT) is another frequently
used model in healthcare technology adoption [10]. It suggests that four key factors
influence user intentions to adopt technology: performance expectancy (perceived usefulness),
effort expectancy (perceived ease of use), social influence, and facilitating conditions.
It also considers the moderating effects of gender, age, experience, and voluntariness
of use. This theory has been applied to various healthcare technologies, such as clinical
decision support systems (CDSSs), adverse-event e-Reporting, and mobile EHR apps,
and has been found to be a useful framework for understanding technology adoption
and use in healthcare settings.
3. SEIPS Model and DeLone and McLean Information Systems (D&M IS) Success Model
The System Engineering Initiative for Patient Safety (SEIPS) model is a systems-based
framework for identifying healthcare factors contributing to patient safety incidents
[11]. The model includes five main components: person, task, technology, organization,
and environment. Person refers to the competencies, attitudes, and behaviors of individuals
involved in the healthcare process. Task refers to the activities and workflows involved
in the healthcare process. Technology includes the tools and equipment used in the
process. Organization contains the policies, procedures, and culture of the healthcare
organization. Environment designates the physical and social context in which the
healthcare process occurs. The SEIPS model is useful for identifying potential sources
of error and inefficiency in healthcare processes, and also for developing targeted
interventions to improve patient safety.
The D&M IS success model provides more-comprehensive categories for introducing information
systems into organizations, focusing on system, information, and service quality [12].
The extended version of D&M IS consists of six interrelated dimensions: system, information,
service quality, use, user satisfaction, and net benefits. The model explains the
construction of the systems according to information, system, and service quality
influencing intention to use, or use of the systems and user satisfaction. The consequences
of its use are noted through net benefits. A systematic review utilized both the SEIPS
and D&M IS models to classify antecedents toward safety technology use [13].
4. HOT-fit Model
The HOT-fit model is a comprehensive framework that integrates organizational and
technological factors affecting the success of health information technology (HIT)
implementation. It broadens the D&M IS success model by including organizational factors
and the concept of “fit” from the IT-organization fit model, and identifies the human,
technology, and organization domains and their interrelationships that affect HIT
usage. This model emphasizes the importance of the alignment among these dimensions
to achieve optimal outcomes. The HOT-fit model is useful for categorizing and identifying
the causes of the consequences of HIT implementation in healthcare. A previous study
used this model to identify the barriers and facilitators influencing medication-related
CDSS acceptance [14].
5. Sociotechnical Model
The theoretical sociotechnical framework underscores the interdependence between workplace
technology and social systems. It emphasizes the importance of aligning the technology,
people, and organizational context to achieve effective performance and satisfaction.
The model aims to optimize the interaction between the technical and social aspects
of work systems so that they are mutually reinforcing and work in harmony. It has
been applied to various industries, including healthcare, to identify the factors
influencing the successful adoption and use of new technologies. By considering the
broader organizational and social context and the technical aspects of the technology,
the sociotechnical model provides a holistic approach to technology implementation
and use.
The conceptual sociotechnical model of Sittig and Singh [15,16] broadens the sociotechnical
model by emphasizing the need to consider the relationships among the social, technical,
and organizational factors of HIT design, implementation, and use. It highlights the
importance of considering the social and organizational context in which HIT is implemented,
including the impact on workflow, communication, and the roles and responsibilities
of healthcare providers. This model also emphasizes the need for ongoing HIT evaluation
and adaptation to ensure that it aligns with the needs and goals of the healthcare
organization and stake-holders.
We have presented a brief overview of seven conceptual frameworks commonly used to
study patient safety technology use and adoption. MMs are frameworks that describe
the level of maturity of an organization in utilizing information systems and its
ability to continuously improve its processes [17]. The models differ from previously
reviewed frameworks, but they are useful to understand and explain the differences
between the technological and social contexts of each organization. Initially proposed
as a straightforward tool for identifying areas of organization software processes
that require improvements [18], maturity models have been developed for various domains,
including healthcare, with focuses on healthcare services, informatics, electronic
medical records, interoperability, and usability, such as the HIMSS Electronic Medical
Record Adoption Model and the maturity model of WHO for digital health [19,20].
The seven frameworks examine the relationship between technology characteristics and
the individual characteristics and behavioral intentions of using it, focusing on
six main related concepts (Table 1). Researchers have been concerned about barriers
to information technology implementation and adoption caused by the lack of theoretical
frameworks in health informatics. Clinical informaticians can utilize this review
to address these concerns. Ongoing rapid advances in patient safety technology make
theoretical frameworks increasingly necessary for inductively or deductively guiding
research and formulating research questions and research positions within existing
frameworks.