FACTORS INFLUENCING THE ACCEPTANCE OF HEALTHCARE INFORMATION TECHNOLOGIES: A META-ANALYSIS

User evaluations of a Dementia case management information system: A cross-sectional study

OBJECTIVE

To evaluate the acceptability of a recently developed electronic Dementia Case Management Information System (DCMIS) following hands-on use by dementia case managers.

METHODS

Dementia case managers from 28 community-based dementia care centers who had previously provided feedback about needs and wants of an electronic case management system were invited to participate (N =30). Following a training session, participants used the DCMIS to assess patients in two scenarios typical for case managers at our centers. Participants then evaluated their experience with a researcher-developed 25-item Technology Acceptance Model questionnaire (scored from 1 to 5). Multiple linear regression analysis examined significant associations between technology acceptance and variables of demographics and external factors (system quality and information, and job relevance) to identify predictors of acceptance of the DCMIS.

RESULTS

Acceptance and perceived usefulness of the DCMIS were high; mean scores were 4.05 (SD,0.62) and 4.15 (SD, 0.67), respectively. Job relevance was a significant predictor of perceived usefulness (β = 0.721, P <.001). System quality and information quality were significant predictors of perceived ease of use (β = 0.355, P =.03 and β = 0.395, P =.02, respectively); job relevance was also a predictor for behavioral intention to use (β = 0.487, P =.03).

CONCLUSIONS

The quantitative assessments of the DCMIS by the dementia case managers demonstrated most found the system to be useful. Factors that were predictors of acceptance suggest that the ability to easily access quality information and improved the ability of dementia case managers to perform their jobs contributed their willingness to view the DCMIS as a tool that could enhance workflow.

Best Practices in Organizing Digital Transformation: Qualitative Case Study in Dutch Hospital Care

BACKGROUND

The health care sector faces increasing pressure, with demand outpacing supply and multiple challenges in accessibility, affordability, and quality. The current organization of health care systems is unsustainable-exacerbated by labor shortages and escalating expenditures in Europe, particularly the Netherlands. To address these issues, hospitals are increasingly adopting digital transformation strategies. This digital transformation involves the systematic implementation of digital technologies and processes. To achieve high-quality hybrid care, hospitals must integrate digital health care seamlessly into existing workflows. However, there is no definitive strategy for implementing these transformations.

OBJECTIVE

This study examines how Dutch hospitals organize their digital transformation, the strategies they employ, and the best practices they follow, to provide evidence-based recommendations for hospitals embarking on similar initiatives.

METHODS

A qualitative multicase study was conducted using purposive sampling. A total of 11 Dutch hospitals were invited, and 8 participated. Professionals-project or program managers of digital care, or advisors in policy, management, strategy, or related positions-from these hospitals took part in semistructured interviews. Topics included digital transformation strategies, organizational structures, barriers and facilitators, and lessons learned. All interviews were recorded, transcribed verbatim, and analyzed using directed content analysis.

RESULTS

Although hospitals organize their digital transformation in different ways and with different teams or departments, they encounter similar facilitators and barriers. Inspired by the Consolidated Framework for Implementation Research, the ExpandNet Scaling Up framework, and the Hybrid Health Care Quality Assessment, these factors were grouped into the following categories: the structure of the digital program, cultural factors within the organization, financial factors (internal or external), political factors (internal or external), patient needs, resources and skills, and technical factors.

CONCLUSIONS

Despite variations in implementation, hospitals share key challenges and enablers in digital transformation. Common factors-such as organizational culture, financial resources, and technical infrastructure-may serve as foundational elements for effective digital transformation in hospital care.

Factors Influencing Health Care Technology Acceptance in Older Adults Based on the Technology Acceptance Model and the Unified Theory of Acceptance and Use of Technology: Meta-Analysis

BACKGROUND

The technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT) are widely used to examine health care technology acceptance among older adults. However, existing literature exhibits considerable heterogeneity, making it difficult to determine consistent predictors of acceptance and behavior.

OBJECTIVE

We aimed to (1) determine the influence of perceived usefulness (PU), perceived ease of use (PEOU), and social influence (SI) on the behavioral intention (BI) to use health care technology among older adults and (2) assess the moderating effects of age, gender, geographic region, type of health care technology, and presence of visual demonstrations.

METHODS

A systematic search was conducted across Google Scholar, Web of Science, Scopus, IEEE Xplore, and ProQuest databases on March 15, 2024, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Of the 1167 initially identified studies, 41 studies (11,574 participants; mean age 67.58, SD 4.76 years; and female:male ratio=2.00) met the inclusion criteria. The studies comprised 12 mobile health, 12 online or telemedicine, 9 wearable, and 8 home or institution hardware investigations, with 23 studies from Asia, 7 from Europe, 7 from African-Islamic regions, and 4 from the United States. Studies were eligible if they used the TAM or UTAUT, examined health care technology adoption among older adults, and reported zero-order correlations. Two independent reviewers screened studies, extracted data, and assessed methodological quality using the Newcastle-Ottawa Scale, evaluating selection, comparability, and outcome assessment with 34% (14/41) of studies rated as good quality and 66% (27/41) as satisfactory.

RESULTS

Random-effects meta-analysis revealed significant positive correlations for PU-BI (r=0.607, 95% CI 0.543-0.665; P<.001), PEOU-BI (r=0.525, 95% CI 0.462-0.583; P<.001), and SI-BI (r=0.551, 95% CI 0.468-0.624; P<.001). High heterogeneity was observed across studies (I²=95.9%, 93.6%, and 95.3% for PU-BI, PEOU-BI, and SI-BI, respectively). Moderator analyses revealed significant differences based on geographic region for PEOU-BI (Q=8.27; P=.04), with strongest effects in Europe (r=0.628) and weakest in African-Islamic regions (r=0.480). Technology type significantly moderated PU-BI (Q=8.08; P=.04) and SI-BI (Q=14.75; P=.002), with home or institutional hardware showing the strongest effects (PU-BI: r=0.736; SI-BI: r=0.690). Visual demonstrations significantly enhanced PU-BI (r=0.706 vs r=0.554; Q=4.24; P=.04) and SI-BI relationships (r=0.670 vs r=0.492; Q=4.38; P=.04). Age and gender showed no significant moderating effects.

CONCLUSIONS

The findings indicate that PU, PEOU, and SI significantly impact the acceptance of health care technology among older adults, with heterogeneity influenced by geographic region, type of technology, and presence of visual demonstrations. This suggests that tailored strategies for different types of technology and the use of visual demonstrations are important for enhancing adoption rates. Limitations include varying definitions of older adults across studies and the use of correlation coefficients rather than controlled effect sizes. Results should therefore be interpreted within specific contexts and populations.

Nurses' Perceptions of Facilitators and Barriers to Their Acceptance of Electronic Health Records: A Mixed-Method Systematic Review

BACKGROUND

International eHealth strategies incorporate the adoption of electronic health records to enhance the delivery of integrated healthcare and improve patient outcomes. Nurses' acceptance of electronic health records is crucial for their successful implementation.

AIM

To synthesise evidence from empirical studies to explore the nurses' perceptions of facilitators and barriers and the influence of moderating factors on their acceptance of electronic health records.

DESIGN

A convergent integrated mixed-method systematic review following the JBI methodology.

DATA SOURCES

CINAHL Plus with Full Text, Medline [EBSCO], ProQuest, PubMed, Scopus, Google Scholar and Open Grey were searched on 28 March 2023 for primary research studies published between 2018 and 2023.

REVIEW METHODS

Studies were screened by two independent reviewers adhering to predetermined inclusion criteria. A convergent integrated synthesis was conducted and deductive analysis was framed by The Unified Theory of Acceptance and Use of Technology model.

RESULTS

Thirteen studies were included and appraised using the mixed-method appraisal tool. Facilitators of nurses' acceptance of electronic health records included increased efficiency, improved access to information, management support and training. Nurses identified increased documentation burden, threats to patient confidentiality, difficult navigation and inadequate IT support and training as barriers to their acceptance. The influence of moderators on nurses' acceptance of electronic health records remains unclear.

CONCLUSION

This review provides insights into nurses' perceptions of factors influencing electronic health record acceptance. Addressing these issues during adoption and further exploring the impact of moderators can improve acceptance and minimise unintended consequences.

IMPLICATIONS

Nurse leaders are key in empowering nurses to accept electronic health records. The nursing profession must participate in all phases of electronic health record design and implementation to ensure that they complement nursing practice.

REPORTING METHOD

PRISMA 2020 Statement.

NO PATIENT OR PUBLICATION CONTRIBUTION

This is a review of primary research.

Exploring Healthcare Students' Intention to Use Virtual Reality Simulations in China: A Cross-sectional Study Applying the Technology Acceptance Model

This study aims to investigate healthcare students' intention to use virtual reality simulations. By using the Technology Acceptance Model, the research delves into the factors influencing students' acceptance and adoption of virtual reality simulations. Following a cross-sectional design, this article adheres to the STROBE Statement guidelines. The study included 632 undergraduate healthcare students from three universities in China. Data were collected through online questionnaires administered at three comprehensive universities in China between June 19, 2023, and January 15, 2024. Self-reported measurements were used, and hypotheses were analyzed using Amos software to construct a structural equation model. The study reveals positive correlations, indicating that habits are positively associated with perceived ease of use and perceived usefulness. Furthermore, system quality is positively correlated with perceived ease of use and perceived usefulness. Notably, perceived ease of use positively influences perceived usefulness, and both perceived ease of use and perceived usefulness are positively linked to intention to use. The findings suggest that educational institutions and educators should prioritize students' habits, platform system quality, perceived usefulness, and perceived ease of use to enhance healthcare students' intention to engage with virtual reality simulations.

Mobile Applications for Longitudinal Data Collection: Web-based Survey Study of Former Intensive Care Patients

PURPOSE

Mobile health plays an important role in providing individualized information about the health status of patients. Limited information exists on intensive care unit (ICU) patients with the risk of suffering from the post-intensive care syndrome (PICS), summarizing long-term physical, mental and cognitive impairment. This web-based survey study aims to identify specific needs of former ICU patients for utilizing a newly developed, so called Post-Intensive Care Outcome Surveillance (PICOS) app to collect relevant PICS-related parameters.

METHODS

A prototype app was developed following interaction principles for interactive systems of usability engineering. Patients from four different German hospitals were asked about demographics, interaction with technology and their perception of the prototype regarding hedonic motivation, perceived ease of use and performance expectancy.

RESULTS

123 patients participated in the survey; the majority owned and used smartphones. Nearly half of respondents would seek help from family members or caregivers using the app. There was a difference in affinity for technology for participants who own a smartphone and those who do not, t(116) = - 0.97, p = .335, and no significant difference in affinity for technology whether the participants would like support when using the app or not, t(97) = 1.81, p = .073. The average hedonic motivation for using the app was M = 4.44 (SD = 1.304).

CONCLUSION

This app prototype was perceived as both beneficial and easy to use, indicating its success among former ICU patients. Due to aging and ongoing health impairments, every second patient would need assistance with the initial use of the app.

A Pilot Study Toward Development of the Digital Literacy, Usability, and Acceptability of Technology Instrument for Healthcare

Electronic health record proficiency is critical for health professionals to deliver and document patient care. There is scarce research on this topic within undergraduate nursing student populations. The purpose of this study is to describe the psychometric evaluation of the Digital Literacy, Usability, and Acceptability of Technology Instrument for Healthcare. A cross-sectional pilot study for psychometric evaluation of the instrument was conducted using data collected through an emailed survey. Exploratory factor analysis, inter-item and adjusted item-total correlations, and Cronbach's α calculated subscale reliability. A total of 297 nursing students completed the survey. A seven-factor structure best fit the data: technology use-engagement, technology use-confidence, technology use-history, electronic health record-ease of use, electronic health record-comparability, and electronic health record-burden. Cronbach's α indicated good to very good internal consistency ( α = .68 to .89). The instrument effectively measured digital literacy, acceptance, and usability of an electronic health record and may be implemented with good to very good reliability across varied healthcare simulation and training experiences.

Predictors of Health Care Practitioners' Intention to Use AI-Enabled Clinical Decision Support Systems: Meta-Analysis Based on the Unified Theory of Acceptance and Use of Technology

BACKGROUND

Artificial intelligence-enabled clinical decision support systems (AI-CDSSs) offer potential for improving health care outcomes, but their adoption among health care practitioners remains limited.

OBJECTIVE

This meta-analysis identified predictors influencing health care practitioners' intention to use AI-CDSSs based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Additional predictors were examined based on existing empirical evidence.

METHODS

The literature search using electronic databases, forward searches, conference programs, and personal correspondence yielded 7731 results, of which 17 (0.22%) studies met the inclusion criteria. Random-effects meta-analysis, relative weight analyses, and meta-analytic moderation and mediation analyses were used to examine the relationships between relevant predictor variables and the intention to use AI-CDSSs.

RESULTS

The meta-analysis results supported the application of the UTAUT to the context of the intention to use AI-CDSSs. The results showed that performance expectancy (r=0.66), effort expectancy (r=0.55), social influence (r=0.66), and facilitating conditions (r=0.66) were positively associated with the intention to use AI-CDSSs, in line with the predictions of the UTAUT. The meta-analysis further identified positive attitude (r=0.63), trust (r=0.73), anxiety (r=-0.41), perceived risk (r=-0.21), and innovativeness (r=0.54) as additional relevant predictors. Trust emerged as the most influential predictor overall. The results of the moderation analyses show that the relationship between social influence and use intention becomes weaker with increasing age. In addition, the relationship between effort expectancy and use intention was stronger for diagnostic AI-CDSSs than for devices that combined diagnostic and treatment recommendations. Finally, the relationship between facilitating conditions and use intention was mediated through performance and effort expectancy.

CONCLUSIONS

This meta-analysis contributes to the understanding of the predictors of intention to use AI-CDSSs based on an extended UTAUT model. More research is needed to substantiate the identified relationships and explain the observed variations in effect sizes by identifying relevant moderating factors. The research findings bear important implications for the design and implementation of training programs for health care practitioners to ease the adoption of AI-CDSSs into their practice.

Healthcare information management and operational cost performance: empirical evidence

Healthcare knowledge management systems can mitigate hospitals' operational inefficiency. As a healthcare information technology, the electronic health record (EHR) receives much attention from medical institutions due to its considerable impact on operational cost performance. This paper focuses on EHR systems to address operational inefficiency by which patients pay more for health care services, and many U.S. hospitals are filing for bankruptcy. From the theoretical perspective of the practice-based view, this paper introduces a path to implement EHR systems for improving cost performance. The empirical investigation is archival data of 200 hospitals collected from the U.S. healthcare agencies. Findings contribute to prior work by hypothesizing moderating and mediating roles in EHR systems implementation. This paper introduces absorptive capacity and monitoring mechanisms as enablers of implementing EHR systems. The results showed that hospital monitoring strengthens the relationship between absorptive capacity and electronic health record systems implementation, which results in better operational cost performance. Theoretically, this study supports the long-term potential benefits of EHR adoption, and its findings are consistent with optimizing efficiency through data standardization and interoperability. From a practical perspective, this study supports hospitals' investments in evolving healthcare information technology systems through the development of a knowledge-based system employing EHR, particularly when hospitals are merging or need a financial strategic plan to control expenses.

A meta-analysis of technology acceptance in healthcare from the consumer's perspective

Consumer-oriented health care technologies are increasingly available and transforming global health delivery systems. However, there is a paucity of research that systematically investigates health care technology acceptance from the consumer's perspective. This study conducts a literature review and meta-analysis to examine consumers' adoption intentions toward health care technologies. The findings suggest that technology acceptance models are transferable to health care technology with modifications, and factors such as perceived risks, technology performance expectancy, consumer trust, and habit significantly correlate with consumers' adoption intentions. This study provides valuable insights into health care technology management and practical implications for health care service designers, providers, and regulatory authorities.

Exploring Patients' Intentions for Usage of Video Telemedicine Follow-Up Services: Cross-Sectional Study

Background: Data suggest that regarding completion rates and lower readmission rates, video telemedicine follow-up is as efficient as in-person consultations. However, evidence of patients' intention to adopt such service is lacking. The objective of this study was to determine the essential factors influencing Chinese patients' intention to adopt video telemedicine follow-up. Methods: The researchers extended the technology acceptance model (TAM) by incorporating trust, subjective norms (SNs), perceived risk (PR), and perceived disease threat (PDT). A survey was conducted with 793 Chinese patients, and the collected data were analyzed using the partial least-squares approach. Results: The study revealed that trust emerged as the strongest factor influencing patients' behavioral intention (BI) to use video telemedicine follow-up, followed by SNs, perceived ease of use (PEOU), and perceived usefulness (PU). PR and PDT had no significant influence on patients' intention to adopt video telemedicine follow-up. PEOU mediated the relationship between trust, SNs, and BI, and PU mediated the relationship between trust and BI. The study also found that gender, age, and usage experience moderated certain relationships in the model. Conclusions: Our findings support the use of the extended TAM in understanding individual's motivations for using video telemedicine follow-up in China. In addition, this study contributes to the existing literature on telemedicine promotion by identifying significant mediation mechanisms. These findings have practical implications for planning, creating, and implementing improved video telemedicine follow-up services.

Factors influencing telemedicine adoption among physicians in the Malaysian healthcare system: A revisit

Background

The Malaysian healthcare system is under strain due to an aging population, the rising prevalence of chronic diseases, and heavy workloads among physicians. As costs and requirements continue to rise, telemedicine is critical for bridging gaps in supply and demand. However, there are limited studies on telemedicine adoption among Malaysian physicians. Furthermore, the existing literature on telemedicine adoption does not contain a comprehensive framework that integrates the multidimensional social influence, and technological, clinical, and individual factors.

Objective

This research investigates the adoption of telemedicine among Malaysian physicians. It draws from the Technology Acceptance Model (TAM) and Kelman's Social Influence Theory.

Methods

A survey was conducted among 230 participants in hospitals located in Kuala Lumpur and Selangor. The data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM).

Results

The study identified crucial factors influencing telemedicine adoption, including informational influences, rewards, perceived ease of use, and usefulness. Meanwhile, the Importance-performance Map Analysis (IPMA) identified perceived ease of use as the most important factor for physicians, but the highest performance was patient's records.

Conclusions

The proposed integrated model enhances the understanding of telemedicine adoption and highlights the differential effects of individual, technological, clinical, and multidimensional social influence factors from the physicians' perspective. The findings can guide future studies and influence implementation strategies for telemedicine promotion in the Malaysian healthcare context. Hospitals should prioritize user-friendly technology and information provision, while telemedicine providers should enhance the accessibility of patient records to facilitate telemedicine adoption. Policymakers should consider supporting training programs that will boost physicians' confidence in effectively utilizing telemedicine.

From use, value and user-centered design to context: A mixed methods analysis of a hospital electronic medical record enhancement

Objective

This study sought to determine the use and perceived value of a user-centered electronic medical record (EMR) enhancement for stroke care and understand if its value was in alignment with its intended design. The EMR enhancement was introduced into Queensland public hospitals in Australia and included a summary page for enhanced interprofessional collaboration and data collection forms for efficient data extraction.

Methods

A mixed methods design was adopted and data collected from four hospital sites. We conducted 15 semistructured interviews with multidisciplinary end-users across participating sites and analyzed this data using inductive thematic techniques. Usage log data was extracted from the EMR to determine its use.

Results

Relative use of the summary page showed moderate use, varying from 66 ± 22.5 uses for each stroke patient admission per month (Site 1) to 26.7 ± 9.1 (Site 2). Interviews identified key themes of "visibility" and providing a "quick snapshot" of patient data as the main positive attributes. Technology "functionality" was perceived negatively. Use of the data collection forms was minimal, with inconsistency across sites: (Site 3, 0% to Site 2, 47%). Negative themes of "inefficiency," poor "functionality" and the "trust" required in data entry practices were found.

Conclusions

Despite its user-centered design, clinicians did not always use the enhancement in line with its intended design, or grasp its intended value. Our findings highlight the challenges of user-centered design to accurately reflect clinical workflows within different contexts. A greater understanding is required of how to optimize user-centered EMR design for specific hospital contexts.

Building High-Performing Primary Care Systems: After a Decade of Policy Change, Is Canada "Walking the Talk?"

Policy Points Considerable investments have been made to build high-performing primary care systems in Canada. However, little is known about the extent to which change has occurred over the last decade with implementing programs and policies across all 13 provincial and territorial jurisdictions. There is significant variation in the degree of implementation of structural features of high-performing primary care systems across Canada. This study provides evidence on the state of primary care reform in Canada and offers insights into the opportunities based on changes that governments elsewhere have made to advance primary care transformation.

CONTEXT

Despite significant investments to transform primary care, Canada lags behind its peers in providing timely access to regular doctors or places of care, timely access to care, developing interprofessional teams, and communication across health care settings. This study examines changes over the last decade (2012 to 2021) in policies across 13 provincial and territorial jurisdictions that address the structural features of high-performing primary care systems.

METHODS

A multiple comparative case study approach was used to explore changes in primary care delivery across 13 Canadian jurisdictions. Each case consisted of (1) qualitative interviews with academics, provincial health care leaders, and health care professionals and (2) a literature review of policies and innovations. Data for each case were thematically analyzed within and across cases, using 12 structural features of high-performing primary care systems to describe each case and assess changes over time.

FINDINGS

The most significant changes include adopting electronic medical records, investments in quality improvement training and support, and developing interprofessional teams. Progress was more limited in implementing primary care governance mechanisms, system coordination, patient enrollment, and payment models. The rate of change was slowest for patient engagement, leadership development, performance measurement, research capacity, and systematic evaluation of innovation.

CONCLUSIONS

Progress toward building high-performing primary care systems in Canada has been slow and variable, with limited change in the organization and delivery of primary care. Canada's experience can inform innovation internationally by demonstrating how preexisting policy legacies constrain the possibilities for widespread primary care reform, with progress less pronounced in the attributes that impact physician autonomy. To accelerate primary care transformation in Canada and abroad, a national strategy and performance measurement framework is needed based on meaningful engagement of patients and other stakeholders. This must be accompanied by targeted funding investments and building strong data infrastructure for performance measurement to support rigorous research.

What Determines the Acceptance and Use of eHealth by Older Adults in Poland?

An aging population is considered a major challenge for governments and healthcare planners. eHealth is perceived as a tool with the potential to ensure efficient healthcare. Moreover, eHealth services may help older adults to maintain longer life in good health. However, there are still several challenges to the large-scale implementation of these solutions among older adults. Therefore, the aim of this study was to explore determinants of the acceptance and use of eHealth by older adults in Poland. Data was collected by the questionnaire, and the UTAUT model was employed. This research covered older adults aged 60 to 69. The analysis of the results using nested regression analysis showed that performance expectancy has a strong significance on the older adults' acceptance and use of eHealth, followed by effort expectancy and social influence. In contrast, facilitating conditions do not have a significant influence on the acceptance and use of eHealth. These findings may also be beneficial for the government to provide relative policies to support the development and usage of eHealth services as well as for the healthcare devices industry to design more older adult-oriented products.