Electronic Health Record Portals adoption: Empirical model based on UTAUT2

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.

[Digital personalized health information services from physicians: survey results of patients' and physicians' acceptance and expectations]

BACKGROUND

The acquisition of health information is fundamental for patient empowerment. In order to support this, new ways of providing information must be found. In this article, the digital personalized provision of health information by physicians as well as the intended use and requirements of patients and physicians are examined.

METHODS

An online survey of a sample of patients stratified for the German population (N = 1,000) and an online survey of physicians (N = 364) on the subject of digital personalized health information services were conducted. The type of information provision in the medical setting, the intention to use it, and the requirements for digital information services were assessed.

RESULTS

Digital personalized information services are still rare. However, patients would support such a service, while physicians are more skeptical. Patients value usability and information quality. With regard to the form of presentation, texts tend to be rated more important than videos. For physicians, on the other hand, it is important that the service comes from a trustworthy provider, complies with guidelines, and is free of charge.

DISCUSSION

The potential of the digital transformation of information provision has so far only been utilized to a limited extent. While the basis for successful implementation seems to be given among patients, physicians still need to overcome their reservations, the benefits of such services need to be communicated, and systemic incentives must be created.

What drives the adoption of online health communities? An empirical study from patient-centric perspective

BACKGROUND

Online health communities (OHCs) provide platforms for patients to seek advice from physicians and receive professional suggestions online. It can improve the efficiency of patients' diagnosis of simple diseases and alleviate hospital congestion. However, few empirical studies have comprehensively explored the factors influencing patients' intention to use OHCs through objective data. This study aims to fill this gap by identifying key factors that influence patients' acceptance of OHCs and proposing effective ways to promote the applications of OHCs in China.

METHODS

Based on the Unified Theory of Acceptance and Usage of Technology (UTAUT), extended with additional constructs identified with patients' information demands in OHCs, this study developed a research model and proposed nine hypotheses. An online survey involving 783 valid responses was conducted in China to collect data to validate the proposed model. Confirmatory factor analysis and partial least squares (PLS) path model were conducted for instrument validation and hypothesis testing.

RESULTS

Price value, eHealth literacy, and performance expectancy are the most prominent constructs in the study context. Interestingly, relation quality was also found to have a significant positive relationship with behavioral intention.

CONCLUSIONS

Based on these findings, OHC operators need to create a user-friendly platform, improve information quality, set reasonable prices, and establish consummate security systems. Physicians and related organizations can raise awareness and assist patients in developing the skills to appropriately comprehend and utilize information in OHCs. This study contributes to both technology adoption theory and practice.

Digital transformation of healthcare during the COVID-19 pandemic: Patients’ teleconsultation acceptance and trusting beliefs

The COVID-19 pandemic boosted the digital transformation of many services, including healthcare, and access to medical care using teleconsultation has increased rapidly. Thus, a growing number of online platforms have been developed to accommodate patients’ needs. This paper examines the factors that predict the intention to use medical teleconsultation by extending the unified theory of acceptance and use of technology (UTAUT2) with the three dimensions of trusting beliefs and self-efficacy. A survey was administered to patients who had used a teleconsultation platform during the pandemic period. As one of the largest studies to date, a sample of 1233 respondents was collected and analyzed using a partial least squares approach, often mobilized in the information systems (IS) domain. Furthermore, a deep analysis using all recommended metrics was performed. The results highlight the significance of trusting beliefs, and self-efficacy in the adoption of digital healthcare services. These findings contribute to both theory and practice in COVID-19 research.

Emerging technologies adoption in healthcare: A SOHI model

The internet and emerging technologies have increased the utilisation of digital platforms. This study aims to draw on performance expectancy, social influence, and satisfaction to investigate a proposed model which is geared toward social media healthcare information (SOHI) adoption. The proposed model uses a structured online questionnaire, and 300 responses were evaluated using partial least squares and structural equation modelling [PLS-SEM]. From the findings, performance expectancy of social media (PESM) and satisfaction with social media (SATSM) were revealed to be significant predictors of behavioural intention towards social media (BISM). Satisfaction with social media (SATSM) had the greatest impact on BISM, accounting for 63.8 per cent of the variance in users' intentions to utilise SOHI. Similarly, PESM and social influence on social media (SISM) had the most predictive influence on SATSM, accounting for 50.5 per cent of the variance in users' social media satisfaction, which led to SOHI adoption. Unlike others, the social influence on social media (SISM) did not have a significant effect on BISM. BISM and satisfaction with social media (SATSM) were significant predictors of SOHI adoption, accounting for 54.5 per cent of the variance in SOHI adoption. The recommendations in this study would help healthcare professionals change their approach to digital healthcare engagement.

Electronic health record adopters: a typology based on patients' privacy concerns and perceived benefits

OBJECTIVES

Patients' adoption of electronic health records (EHRs) varies substantially. Although some countries, such as Estonia and Denmark, are sufficiently advanced in terms of EHR generalisation, others, such as France, are figuring out how to implement and disseminate EHRs. These governments must respond to patients' disparities to achieve the expected performance for healthcare systems and improve the quality of care delivery. This study investigates patients' perceived benefits and privacy concerns related to EHRs to develop a typology of patients, identify the characteristics of different clusters and propose practical measures for public policy-makers.

STUDY DESIGN

We conducted a cross-sectional study using online questionnaires.

METHODS

An online quantitative survey was carried out in France. The final sample of EHR non-users (N = 1076) was fitted to be representative of the French population by age and gender, region and socioprofessional status. Hierarchical and non-hierarchical cluster analyses were performed. Several robustness check analyses were also performed.

RESULTS

Cluster analyses identified four patient clusters: the worried, who show the highest mean privacy concern and risk levels related to health data disclosure; the ready adopters, who lack privacy concerns and risk and are the most motivated by EHR benefits; the concerned adopters, who express far fewer privacy concerns and perceive EHR benefits more favourably than the worried adopters; and the balanced adopters, who are relatively similar to the ready adopters in their EHR motives and are still concerned about their health data, suggesting a segment that is easier to convince. Comparing clusters regarding the intentions to create EHRs and willingness to disclose health data confirms that ready adopters, followed by balanced adopters, are more likely to create an EHR and disclose health data. The concerned adopters and, finally, the worried exhibit the lowest intentions for EHR creation and data disclosure.

CONCLUSIONS

The results provide meaningful insights into patient profiles and expectations. The findings underscore the need to implement targeting policies for each cluster and design concrete solutions for improving EHR performance.

Assessing patient readiness for a patient portal implementation in the UAE

Purpose

This paper proposes a Web-based patient portal based on the electronic medical record. Such a portal can allow patients to manage their own health care, reduce health-care visits and significantly improve the quality of their health care.

Design/methodology/approach

A patient portal prototype and an accompanying online survey were distributed to assess the adoption readiness among a group of people in the United Arab Emirates (UAE).

Findings

The results from 470 survey participants demonstrated an enhanced awareness of this technology, and support the study hypotheses indicating that both intrinsic and extrinsic factors are important when considering the implementation of a patient portal in the UAE.

Originality/value

This study adds value to the few research studies undertaken in the Middle East discussing online health information technology and its adoption and usage among the population at large. The extended technology acceptance model, which contains two additional constructs, had not been previously validated in terms of a patient portal in the UAE, according to the author’s knowledge, adding more value. The UAE’s health-care system must use the benefits from the available IT infrastructure to provide a user-friendly online portal to encourage patients to manage their health care and health information.

Modifying UTAUT2 for a cross-country comparison of telemedicine adoption

The ongoing COVID19 pandemic has put digital health technologies in the spotlight. To gain a deeper understanding of patients’ usage intentions of virtual doctor appointments, the present research adapts the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) by integrating perceived security and perceived product advantage, two known barriers to successful telemedicine adoption. Applying age-stratified sampling, an online survey was distributed to 800 citizens in Germany and the United States of America. 710 completed and valid questionnaires were subsequently analyzed using SPSS and AMOS (versions 24).

Significant, direct, and positive effects of performance expectancy, hedonic motivation, perceived security, and perceived product advantage on the behavioral intention to use virtual doctor appointments were found. The analysis of the moderating variables, age and gender, showed significant differences in user's performance expectancy and effort expectancy, and perceived product advantage, respectively. With virtual health care models on the rise, these results are important for stakeholders such as policymakers, governments, employers, but also physicians, and insurance companies as they offer clear recommendations to design telemedicine adoption strategies to ensure successful patient engagement.

Barriers and Benefits of Information Communication Technologies Used by Health Care Aides

BACKGROUND

Although information and communication technologies (ICT) are becoming more common among health care providers, there is little evidence on how ICT can support health care aides. Health care aides, also known as personal care workers, are unlicensed service providers who encompass the second largest workforce, next to nurses, that provide care to older adults in Canada.

OBJECTIVE

The purpose of this literature review is to examine the range and extent of barriers and benefits of ICT used by health care workers to manage and coordinate the care-delivery workflow for their clients.

METHODS

We conducted a literature review to examine the range and extent of ICT used by health care aides to manage and coordinate their care delivery, workflow, and activities. We identified 8,958 studies of which 40 were included for descriptive analyses.

RESULTS

We distinguished the following five different purposes for the use and implementation of ICT by health care aides: (1) improve everyday work, (2) access electronic health records for home care, (3) facilitate client assessment and care planning, (4) enhance communication, and (5) provide care remotely. We identified 128 barriers and 130 benefits related to adopting ICT. Most of the barriers referred to incomplete hardware and software features, time-consuming ICT adoption, heavy or increased workloads, perceived lack of usefulness of ICT, cost or budget restrictions, security and privacy concerns, and lack of integration with technologies. The benefits for health care aides' adoption of ICT were improvements in communication, support to workflows and processes, improvements in resource planning and health care aides' services, and improvements in access to information and documentation.

CONCLUSION

Health care aides are an essential part of the health care system. They provide one-on-one care to their clients in everyday tasks. Despite the scarce information related to health care aides, we identified many benefits of ICT adoption.

User trends of electronic payment systems adoption in developing countries: an empirical analysis

Purpose

Electronic payment (e-payment) systems literature analysis reveals that they are growing in developing countries; however, they are limited in the Arab countries and, more importantly, scarce in Iraq in particular. Therefore, this paper aims to investigate the factors influencing the intention of users to use e-payment systems in Iraq. Additionally, this study proposes an e-payment adoption model based on technology usage models to identify user trends toward e-payment systems.

Design/methodology/approach

A quantitative approach is adopted to test the proposed model. The proposed model is based on the Unified Theory of Acceptance and Usage of Technology theory. The proposed model is validated using survey data from 339 e-payment system users. Using Amos software, this study used structural equation modeling (SEM), a statistical technique for analyzing factor relationships.

Findings

The findings of the study indicate that performance expectancy, effort expectancy, social influence, facilitating conditions and price saving orientation influence Intention to accept the e-payment system. Similarly, habit, technology security, trust, innovation resistance, psychological empowerment also affect intention to accept an e-payment system. However, hedonic motivation and perceived risk do not affect e-payment system adoption.

Originality/value

The identified factors play a major role in user intentions toward the adoption of e-payment systems for financial transactions and addressing these factors will make e-payment acceptable in the future. The results of this study contribute to assisting governments or e-payment firms and decision-makers in building strategic decisions or policies that will increase the adoption of e-payment by individuals.

To Wear or Not to Wear: Analysis of Individuals' Tendency to Wear Masks during the COVID-19 Pandemic in China

During the COVID-19 pandemic, the percentage of Chinese people wearing masks was very high, as was the acceptance and initiative toward mask wearing. This national action merits our exploration of the psychological reasons as well as the general social and environmental factors behind this behavior. In this article, we integrated the Unified Theory of Acceptance and Use of Technology 2 (UTAUT 2) as well as Health Belief Model and set up a mask acceptance model. We used a questionnaire survey and received 337 valid questionnaires. The results indicate that social influence, perceived susceptibility to COVID-19, perceived hedonic benefit (appearance enhancement), and a perceived barrier (hindrance to communication) exert significant influences on the willingness to wear masks. Meanwhile, social influence plays an intermediary role between interdependent self-construal and intention to wear a mask. We hope to reveal the micro psychological reasons for the national action and reflect on the cultural characteristics of Chinese people in the special context of the COVID-19 pandemic.

Antecedents of Intention to Adopt Mobile Health (mHealth) Application and Its Impact on Intention to Recommend: An Evidence from Indonesian Customers

INTRODUCTION

Mobile health (mHealth) applications gain popularity due to the increasing number of mobile phone usage and internet penetration, which might help some of Indonesia's medical issues. However, the uptake of mHealth applications is still low in Indonesia. This study is aimed at understanding the factors that drive individuals to adopt mHealth applications and their impact on the intention to recommend.

METHODS

We applied a new model that combines three different theories with some other constructs: an extended unified theory of acceptance and use of technology, diffusion of innovation, and the internet customer trust model. The study used a cross-sectional study design with partial least squares causal modeling approach.

RESULTS

There are 787 respondents in our study, with the majority of them being female, young adults. Our model could explain 53.2% of the variance of intention to adopt while explaining 48.3% of the variance of intention to recommend. Initial trust in mHealth platform (β = 0.373, p = <0.001), facilitating conditions (β = 0.131, p = <0.01), and performance expectancy (β = 0.099, p = <0.05) are the top three most important drivers of intention to adopt mHealth applications. Lastly, importance-performance map analysis (IPMA) showed that the mHealth application's initial trust is the most important construct with a high-performance score. Discussion. Mobile health developers and managers need to improve initial trust in the mHealth platform, facilitating conditions, and performance expectancy when developing the applications. With a medium Q 2 predict, these factors can be applied out of the research context with medium predictive power.

Patients' perceptions of teleconsultation during COVID-19: A cross-national study

In recent months, humanity has had to deal with a worldwide pandemic called COVID-19, which has caused the death of hundreds of thousands of people and paralyzed the global economy. Struggling to cure infected patients while continuing to care for patients with other pathologies, health authorities have faced the lack of medical staff and infrastructure. This study aimed to investigate the acceptance of teleconsultation solutions by patients, which help to avoid the spread of the disease during this pandemic period. The model was built using some constructs of the technology acceptance model UTAUT2, Personal traits, Availability, and Perceived Risks. A new scale on Contamination Avoidance was developed by the authors. The questionnaire was disseminated in several countries in Europe and Asia and a total sample of 386 respondents was collected. The results emphasize the huge impact of Performance Expectancy, the negative influence of Perceived Risk, and the positive influence of Contamination Avoidance on the adoption of teleconsultation solutions. The findings highlight the moderating effects of Age, Gender, and Country.

Understanding the Drivers of Wearable Health Monitoring Technology: An Extension of the Unified Theory of Acceptance and Use of Technology

The market for wearable health monitoring technology is promising globally and in Saudi Arabia particularly. The country has a very high prevalence of chronic diseases that can be managed using wearable health monitoring technology. However, wearable devices are not fully advantageous if people do not accept them. Due to the parsimony of studies on the acceptance of wearable health monitoring technology, understanding the key drivers of using wearable health monitoring technology remains uncertain. This cross-sectional study extends the extended unified theory of acceptance and use of technology (UTAUT2) to explain the variance in the adoption intention of wearable health monitoring technology. A total of 256 responses were analyzed using the partial least squares structural equation modeling technique, in addition to the importance-performance map analysis. The results indicate that performance expectancy (PE), social influence (SI), facilitating conditions (FC), hedonic motivation (HM) and habit (HA) significantly impact users’ behavioral intention (BI) to adopt wearable health monitoring technology. The results also demonstrate that effort expectancy (EE), price value (PV), government health policy (GHP) and trust (TR) are not important. Based on the findings, this research presents a set of recommendations for decisions makers, managers and system developers in the healthcare sector to enhance the use and quality of wearable technology.

Drivers of Mobile Health Acceptance and Use From the Patient Perspective: Survey Study and Quantitative Model Development

Background

Mobile health (mHealth) has potential to play a significant role in realizing a reversal of the current paradigm in health care toward a more patient-centric and more collaborative system to improve the outcomes obtained along with the quality and sustainability of health care systems.

Objective

The aim of this study was to explore and understand individual mHealth acceptance drivers between two groups of users: those with chronic health conditions and those without.

Methods

The extended unified theory of acceptance and usage of technology (UTAUT2) was enhanced with a new health-related framework: behavior intention to recommend and new mediation effects. We applied partial least squares (PLS) causal modeling to test the research model.

Results

We obtained 322 valid responses through an online questionnaire. The drivers of behavior intention with statistical significance were performance expectancy (β=.29, P<.001), habit (β=.39, P<.001), and personal empowerment (β=.18, P=.01). The precursors of use behavior were habit (β= .47, P<.001) and personal empowerment (β=.17, P=.01). Behavior intention to recommend was significantly influenced by behavior intention (β=.58, P<.001) and personal empowerment (β=.26, P<.001). The model explained 66% of the total variance in behavior intention, 54% of the variance in use behavior, and 70% of the variance in behavior intention to recommend.

Conclusions

Our study demonstrates a significant role of personal empowerment, as a second-order construct, in the mHealth acceptance context. The presence of a chronic health condition predicates an impact on acceptance of this technology.

Empirical Investigation of Factors Influencing Consumer Intention to Use an Artificial Intelligence-Powered Mobile Application for Weight Loss and Health Management

Background: Research into interventions based on mobile health (m-Health) applications (apps) has attracted considerable attention among researchers; however, most previous studies have focused on research-led apps and their effectiveness when applied to overweight/obese adults. There remains a paucity of research on the attitudes of typical consumers toward the adoption of m-Health apps for weight management. This study adopted the tenets of the extended unified theory of acceptance and use of technology 2 (UTAUT2) as the theoretical foundation in developing a model that integrates personal innovativeness (PI) and network externality (NE) in seeking to identify the factors with the most pronounced effect on one's intention to use an artificial intelligence-powered weight loss and health management app. Materials and Methods: An online survey was conducted for Taiwanese participants aged ≥21 years from May 23 to June 30, 2018. Hypotheses were tested using structural equation modeling. Results: In the analysis of 458 responses, the proposed research model explained 75.5% of variance in behavioral intention (BI). Habit was the independent variable with the strongest performance in predicting user intention, followed by PI, NE, and performance expectancy (PE). Social influence weakly affects user intention through PE. In multi-group analysis, education was shown to exert a moderating influence on some of the relationships hypothesized in the model. Conclusions: The empirically validated model in this study provides insights into the primary determinants of user intention toward the adoption of m-Health app for weight loss and health management. The theoretical and practical implications are relevant to researchers seeking to extend the applicability of the UTAUT2 model to health apps as well as practitioners seeking to promote the adoption of m-Health apps. In the future, researchers could extend the model to assess the effects of BI on actual use behavior.

An Exploration and Confirmation of the Factors Influencing Adoption of IoT-Based Wearable Fitness Trackers

In recent years, IoT (Internet of Things)-based smart devices have penetrated a wide range of markets, including connected health, smart home, and wearable devices. Among the IoT-based smart devices, wearable fitness trackers are the most widely diffused and adopted IoT based devices. Such devices can monitor or track the physical activity of the person wearing them. Although society has benefitted from the conveniences provided by IoT-based wearable fitness trackers, few studies have explored the factors influencing the adoption of such technology. Furthermore, one of the most prevalent issues nowadays is the large attrition rate of consumers no longer wearing their device. Consequently, this article aims to define an analytic framework that can be used to explore the factors that influence the adoption of IoT-based wearable fitness trackers. In this article, the constructs for evaluating these factors will be explored by reviewing extant studies and theories. Then, these constructs are further evaluated based on experts' consensus using the modified Delphi method. Based on the opinions of experts, the analytic framework for deriving an influence relationship map (IRM) is derived using the decision-making trial and evaluation laboratory (DEMATEL). Finally, based on the IRM, the behaviors adopted by mass customers toward IoT-based wearable fitness trackers are confirmed using the partial least squares (PLS) structural equation model (SEM) approach. The proposed analytic framework that integrates the DEMATEL and PLS-SEM was verified as being a feasible research area by empirical validation that was based on opinions provided by both Taiwanese experts and mass customers. The proposed analytic method can be used in future studies of technology marketing and consumer behaviors.

New Integrated Model Approach to Understand the Factors That Drive Electronic Health Record Portal Adoption: Cross-Sectional National Survey

Background

The future of health care delivery is becoming more patient-focused, and electronic health record (EHR) portals are gaining more attention from worldwide governments that consider this technology as a valuable asset for the future sustainability of the national health care systems. Overall, this makes the adoption of EHR portals an important field to study.

Objective

The aim of this study is to understand the factors that drive individuals to adopt EHR portals.

Methods

We applied a new adoption model that combines 3 different theories, namely, extended unified theory of acceptance and use of technology, health belief model, and the diffusion of innovation; all the 3 theories provided relevant contributions for the understanding of EHR portals. To test the research model, we used the partial least squares causal modeling approach. We executed a national survey based on randomly generated mobile phone numbers. We collected 139 questionnaires.

Results

Performance expectancy (beta=.203; t=2.699), compatibility (beta=.530; t=6.189), and habit (beta=.251; t=2.660) have a statistically significant impact on behavior intention (R²=76.0%). Habit (beta=.378; t=3.821), self-perception (beta=.233; t=2.971), and behavior intention (beta=.263; t=2.379) have a statistically significant impact on use behavior (R²=61.8%). In addition, behavior intention (beta=.747; t=10.737) has a statistically significant impact on intention to recommend (R²=69.0%), results demonstrability (beta=.403; t=2.888) and compatibility (beta=.337; t=2.243) have a statistically significant impact on effort expectancy (R²=48.3%), and compatibility (beta=.594; t=6.141) has a statistically significant impact on performance expectancy (R²=42.7%).

Conclusions

Our research model yields very good results, with relevant R² in the most important dependent variables that help explain the adoption of EHR portals, behavior intention, and use behavior.