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

Unpacking public resistance to health Chatbots: a parallel mediation analysis

Introduction

Despite the numerous potential benefits of health chatbots for personal health management, a substantial proportion of people oppose the use of such software applications. Building on the innovation resistance theory (IRT) and the prototype willingness model (PWM), this study investigated the functional barriers, psychological barriers, and negative prototype perception antecedents of individuals' resistance to health chatbots, as well as the rational and irrational psychological mechanisms underlying their linkages.

Methods

Data from 398 participants were used to construct a partial least squares structural equation model (PLS-SEM).

Results

Resistance intention mediated the relationship between functional barriers, psychological barriers, and resistance behavioral tendency, respectively. Furthermore, The relationship between negative prototype perceptions and resistance behavioral tendency was mediated by resistance intention and resistance willingness. Moreover, negative prototype perceptions were a more effective predictor of resistance behavioral tendency through resistance willingness than functional and psychological barriers.

Discussion

By investigating the role of irrational factors in health chatbot resistance, this study expands the scope of the IRT to explain the psychological mechanisms underlying individuals' resistance to health chatbots. Interventions to address people's resistance to health chatbots are discussed.

Establishing the Saudi pediatric and youth diabetes registry: initial data and challenges

The Saudi National Diabetes Registry focuses mainly on adult patients. In 2020, the National Guard Health Authority (NGHA) launched the Saudi Pediatric and Youth Diabetes Registry (SPYDR), for children and adolescents with diabetes. This report is about the first data and the challenges we faced during SPYDR initiation. Patients were identified from the electronic medical records of the Saudi NGHA hospitals using the International Classification of Disease (ICD-10). A trained coordinator verified the diagnosis and entered patients' details into the registry and a random sample was validated by experienced endocrinologists. The data were analyzed according to patients' demography, diabetes subtypes, duration, control, and complications. The challenges faced by the team were identified and addressed. At the time of manuscript submission, 2,344 individuals were enrolled. Their mean age at diagnosis was 9.08 (±4.27) years and 1,136 (48.46%) were females. Of these, 91.3% have type 1 (T1D), and 6.4% have type 2 diabetes (T2D). The mean HbA1c was 10.45% (±2.36) and duration of diabetes was 5.31 (±3.05) years. The main challenges included the COVID-19 pandemic, data validation, and centers' participation. However, within 12 months of initiation enrolled subjects matched the expected number. Despite the challenges, the first step of SPYDR was achieved. The initial data confirmed that T1D is the most common form of childhood diabetes, and the frequency of T2D is comparable to regional and international data. SPYDR provides the infrastructure for data sharing and collaborative research with the enrollment of patients from other Saudi healthcare institutes.

Factors Influencing the Behavioral Intentions and Use Behaviors of Telemedicine in Patients With Diabetes: Web-Based Survey Study

BACKGROUND

Telemedicine has great potential for diabetes management. The COVID-19 pandemic has boosted the development of telemedicine. However, the factors influencing the behavioral intentions to use and use behaviors of telemedicine in patients with diabetes in China are not clear.

OBJECTIVE

We aimed to understand the determinants of behavioral intention to use telemedicine based on an extended Unified Theory of Acceptance and Use of Technology model and to identify demographic factors associated with telemedicine use in patients with diabetes in China.

METHODS

Patients with diabetes who are aged ≥18 years were surveyed from February 1 to February 7, 2023. We distributed the survey link in 3 WeChat groups including a total of 988 patients with diabetes from the outpatient department or patients discharged from Changsha Central Hospital. Structural equation modeling was used to understand the determinants of behavioral intention. A multivariate logistic regression analysis was used to identify the demographic factors associated with telemedicine use.

RESULTS

In total, 514 questionnaires were collected. Of the respondents, 186 (36.2%) were diagnosed with COVID-19. The measurement model showed acceptable reliability, convergent validity, discriminant validity, and data fit indices. The model explained 63.8% of the variance in behavioral intention. Social influence, performance expectancy, and facilitating conditions positively influenced behavioral intention (β=.463, P<.001; β=.153, P=.02; and β=.257, P=.004, respectively). Perceived susceptibility, perceived severity, and effort expectancy had no significant impact on behavioral intention (all P>.05). The overall use of telemedicine was 20.6% (104/514). After adjusting for the behavioral intention score, the multivariate regression analysis showed that age, education, and family income were associated with telemedicine use. Telemedicine use was higher in the 40 to 59 years and 18 to 39 years age groups than in the ≥60 years age group (odds ratio [OR] 4.35, 95% CI 1.84-10.29, P=.001; OR 9.20, 95% CI 3.40-24.88, P<.001, respectively). Telemedicine use was higher in the senior high school and the university and more groups than in junior high school education and less group (OR 2.45, 95% CI 1.05-5.73, P=.04; OR 2.63, 95% CI 1.11-6.23, P=.03, respectively). Patients with a higher family income used telemedicine more often than the patients who had an annual family income ≤¥10,000 (CNY ¥1=US $0.1398; ¥10,000-¥50,000 group: OR 3.90, 95% CI 1.21-12.51, P=.02; ¥50,000-¥100,000 group: OR 3.91, 95% CI 1.19-12.79, P=.02; >¥100,000 group: OR 4.63, 95% CI 1.41-15.27, P=.01).

CONCLUSIONS

Social influence, performance expectancy, and facilitating conditions positively affected the behavioral intention of patients with diabetes to use telemedicine. Young patients, highly educated patients, and patients with high family income use telemedicine more often. Promoting behavioral intention and paying special attention to the needs of older adult patients, patients with low income, and patients with low levels of education are needed to encourage telemedicine use.

Utilization of patient portals: a cross-sectional study investigating associations with mobile app quality

BACKGROUND

Mobile apps facilitate patients' access to portals and interaction with their healthcare providers. The COVID-19 pandemic accelerated this trend globally, but little evidence exists on patient portal usage in the Middle East, where internet access and digital literacy are limited. Our study aimed to explore how users utilize a patient portal through its related mobile app (MyChart by EPIC).

METHODS

We conducted a cross-sectional survey of MyChart users, recruited from a tertiary care center in Lebanon. We collected MyChart usage patterns, perceived outcomes, and app quality, based on the Mobile Application Rating Scale (user version, uMARS), and sociodemographic factors. We examined associations between app usage, app quality, and sociodemographic factors using Pearson's correlations, Chi-square, ANOVA, and t-tests.

RESULTS

428 users completed the survey; they were primarily female (63%), aged 41.3 ± 15.6 years, with a higher education level (87%) and a relatively high crowding index of 1.4 ± 0.6. Most of the sample was in good and very good health (78%) and had no chronic illnesses (67%), and accessed the portal through MyChart once a month or less (76%). The most frequently used features were accessing health records (98%), scheduling appointments (67%), and messaging physicians (56%). According to uMARS completers (n = 200), the objective quality score was 3.8 ± 0.5, and the subjective quality was 3.6 ± 0.7. No significant association was found between overall app usage and the mobile app quality measured via uMARS. Moreover, app use frequency was negatively associated with education, socioeconomic status, and perceived health status. On the other hand, app use was positively related to having chronic conditions, the number of physician visits and subjective app quality.

CONCLUSION

The patient portal usage was not associated with app quality but with some of the participants' demographic factors. The app offers a user-friendly, good-quality interface to patient health records and physicians, appreciated chiefly by users with relatively low socioeconomic status and education. While this is encouraging, more research is needed to capture the usage patterns and perceptions of male patients and those with even lower education and socioeconomic status, to make patient portals more inclusive.

Adoption of video consultations during the COVID-19 pandemic

BACKGROUND

Video consultations have the potential to play a significant role for the future of healthcare by solving some of the imminently arising healthcare challenges, as pointed by the European Commission in Europe and the National Academy of Medicine in the United States of America. This technology can improve quality, efficiency, and enhance access to healthcare.

OBJECTIVE

The aim of this study is to explore and understand individual video consultations acceptance drivers.

METHODS

An extended technology acceptance model was created based on the diffusion of innovation theory (DOI), unified theory of acceptance and use of technology (UTAUT), health belief model (HBM), and concerns for information privacy framework (CFIP). 346 valid responses were collected through an online questionnaire, and the partial least squares (PLS) modeling approach was used to test the model.

RESULTS

The model explained 77.6 % (R2) of the variance on intention to use, and 71.4 % (R2) of the variance in attitude. The predictors of intention to use are attitude (beta = 0.504, p-value<0.001), performance expectancy (beta = 0.196, p-value = 0.002), and COVID-19 (beta = 0.151, p-value<0.001). The predictors of attitude are performance expectancy (beta = 0.643, p-value>0.001), effort expectancy (beta = 0.138, p-value = 0.001), and COVID-19 (beta = 0.170, p-value<0.001).

CONCLUSIONS

This research model highlights the importance of creating extended acceptance models to capture the specificities of each technology in healthcare. The model created helps to understand the most important drivers of video consultation acceptance, highlighting the importance of the COVID-19 pandemic and perceived health risks.

Development and evaluation of smartphone usage management system for preventing problematic smartphone use

Objective

The increased use of smartphones has led to several problems, including excessive smartphone use and the decreased self-ability to control smartphone use. To prevent these problems, the MindsCare app was developed as a method of self-management and intervention based on an evaluation of smartphone usage. We designed the MindsCare app to manage smartphone usage and prevent problematic smartphone use by providing personalized interventions.

Methods

We recruited 342 Korean participants over the age of 20 and asked them to use MindsCare for 13 weeks. Subsequently, we evaluated the changes in average smartphone usage time and the usability of the app. We designed a usability evaluation questionnaire based on the Technology Acceptance Model and conducted factor and reliability analyses on the participants’ responses. In the eighth week of the study, participants responded to a survey on the usability of the app. We ultimately collected data from 190 participants.

Results

The average score for the usability of the system was 3.61 on a five-point Likert scale, and approximately 58% of the participants responded positively to the evaluation items. In addition, our analysis of MindsCare data revealed a significant reduction in average smartphone use time in the eighth week compared to the baseline (t = 3.47, p = 0.001). Structural equation model analysis revealed that effort expectancy and performance expectancy had a positive relation with behavior intention for the app.

Conclusions

Through this study, we confirmed the MindsCare app's smartphone usage time reduction effect and proved its good usability. As a result, MindsCare may contribute to achieving users’ goals of reducing problematic smartphone use.

The Mediating Influence of the Unified Theory of Acceptance and Use of Technology on the Relationship Between Internal Health Locus of Control and Mobile Health Adoption: Cross-sectional Study

Background

Mobile health (mHealth) as an innovative form of information and communications technology can efficiently deliver high-quality health care by enhancing communication and health management, reducing costs, and increasing access to health services. An individual’s internal health locus of control (HLOC) is found to be associated with the behavioral intent to adopt mHealth. However, little is known about the underlying mechanism of this association.

Objective

The primary objective of this study was to test the mediation influence of the Unified Theory of Acceptance and Use of Technology (UTAUT) on the relationship between internal HLOC and the behavioral intention to use mHealth.

Methods

A total of 374 responses were collected from Malaysian adult users of mHealth, using convenience and snowball sampling methods. Partial least squares structural equation modeling was used to analyze the data. Data were collected for variables, including demographics, internal HLOC, and modified UTAUT constructs (ie, performance expectancy, effort expectancy, and social influence).

Results

The results showed that there was no direct relationship between internal HLOC and the behavioral intention to use mHealth (β=−0.039, P=.32). The indirect relationship between internal HLOC and the intent to adopt mHealth was supported, indicating that the UTAUT constructs performance expectancy (β=0.104, P<.001), effort expectancy (β=0.056, P=.02), and social influence (β=0.057, P=.002) mediated this relationship. The results showed full mediation, with total variance explained at 47.2%.

Conclusions

This study developed an integrative model, where a health-related disposition (internal HLOC), mHealth-related beliefs (performance expectancy and effort expectancy), and normative pressure (social influence) were combined to explain the underlying mechanism of the behavioral intent to adopt mHealth. The results showed that the intention to adopt mHealth is mediated by the influence of UTAUT factors, while HLOC has no direct effect on adoption intention. The findings provide insights into augmenting mHealth adoption among the public by enhancing the perceived benefits of mHealth, helping design more effective and user-friendly mHealth tools, and capitalizing on social normative influence to adopt mHealth. This study utilized the constructs of the UTAUT model to determine the intention to use mHealth. Future research should focus on other health- and technology-related theories to ascertain other possible factors influencing the behavioral intent of mHealth adoption.

Examining How Internet Users Trust and Access Electronic Health Record Patient Portals: Survey Study

Background

Electronic health record (EHR) patient portals are designed to provide medical health records to patients. Using an EHR portal is expected to contribute to positive health outcomes and facilitate patient-provider communication.

Objective

Our objective was to examine how portal users report using their portals and the factors associated with obtaining health information from the internet. We also examined the desired portal features, factors impacting users’ trust in portals, and barriers to using portals.

Methods

An internet-based survey study was conducted using Amazon Mechanical Turk. All the participants were adults in the United States who used patient portals. The survey included questions about how the participants used their portals, what factors acted as barriers to using their portals, and how they used and how much they trusted other web-based health information sources as well as their portals. A logistic regression model was used to examine the factors influencing the participants’ trust in their portals. Additionally, the desired features and design characteristics were identified to support the design of future portals.

Results

A total of 394 participants completed the survey. Most of the participants were less than 35 years old (212/394, 53.8%), with 36.3% (143/394) aged between 35 and 55 years, and 9.9% (39/394) aged above 55 years. Women accounted for 48.5% (191/394) of the survey participants. More than 78% (307/394) of the participants reported using portals at least monthly. The most common portal features used were viewing lab results, making appointments, and paying bills. Participants reported some barriers to portal use including data security and limited access to the internet. The results of a logistic regression model used to predict the trust in their portals suggest that those comfortable using their portals (odds ratio [OR] 7.97, 95% CI 1.11-57.32) thought that their portals were easy to use (OR 7.4, 95% CI 1.12-48.84), and frequent internet users (OR 43.72, 95% CI 1.83-1046.43) were more likely to trust their portals. Participants reporting that the portals were important in managing their health (OR 28.13, 95% CI 5.31-148.85) and that their portals were a valuable part of their health care (OR 6.75, 95% CI 1.51-30.11) were also more likely to trust their portals.

Conclusions

There are several factors that impact the trust of EHR patient portal users in their portals. Designing easily usable portals and considering these factors may be the most effective approach to improving trust in patient portals. The desired features and usability of portals are critical factors that contribute to users’ trust in EHR portals.

Improvement and Evaluation of the TOPCOP Taxonomy of Patient Portals: Taxonomy-Evaluation-Delphi Approach (TED)

Background

Patient portals have been introduced in many countries over the last 10 years, but many health information managers still feel they have too little knowledge of patient portals. A taxonomy can help them to better compare and select portals. This has led us to develop the TOPCOP taxonomy for classifying and comparing patient portals. However, the taxonomy has not been evaluated by users.

Objective

This study aimed to evaluate the taxonomy’s usefulness to support health information managers in comparing, classifying, defining a requirement profile for, and selecting patient portals and to improve the taxonomy where needed.

Methods

We used a modified Delphi approach. We sampled a heterogeneous panel of 13 health information managers from 3 countries using the criterion sampling strategy. We conducted 4 anonymous survey rounds with qualitative and quantitative questions. In round 1, the panelists assessed the appropriateness of each dimension, and we collected new ideas to improve the dimensions. In rounds 2 and 3, the panelists iteratively evaluated the taxonomy that was revised based on round 1. In round 4, the panelists assessed the need for a taxonomy and the appropriateness of patient engagement as a distinguishing concept. Then, they compared 2 real portals with the final taxonomy and evaluated its usefulness for comparing portals, creating an initial requirement profile, and selecting patient portals. To determine group consensus, we applied the RAND/UCLA Appropriateness Method.

Results

The final taxonomy consists of 25 dimensions with 65 characteristics. Five new dimensions were added to the original taxonomy, with 8 characteristics added to already existing dimensions. Group consensus was achieved on the need for such a taxonomy to compare portals, on patient engagement as an appropriate distinguishing concept, and on the comprehensibility of the taxonomy’s form. Further, consensus was achieved on the taxonomy’s usefulness for classifying and comparing portals, assisting users in better understanding portals, creating a requirement profile, and selecting portals. This allowed us to test the usefulness of the final taxonomy with the intended users.

Conclusions

The TOPCOP taxonomy aims to support health information managers in comparing and selecting patient portals. By providing a standardized terminology to describe various aspects of patient portals independent of clinical setting or country, the taxonomy will also be useful for advancing research and evaluation of patient portals.

User Evaluation of the Swedish Patient Accessible Electronic Health Record: System Usability Scale

Background

Transparency is increasingly called for in health care, especially, when it comes to patients’ access to their electronic health records. In Sweden, the e-service Journalen is a national patient accessible electronic health record (PAEHR), accessible online via the national patient portal. User characteristics and perceived benefits of using a PAEHR influence behavioral intention for use and adoption, but poor usability that increases the effort expectancy can have a negative impact. It is, therefore, of interest to explore how users of the PAEHR Journalen perceive its usability and usefulness.

Objective

The aim of this study was to explore how the users of the Swedish PAEHR experience the usability of the system and to identify differences in these experiences based on the level of transparency of the region.

Methods

A survey study was conducted to elicit opinions and experiences of patients using Journalen. The data were collected from June to October 2016. The questionnaire included questions regarding the usability of the system from the System Usability Scale (SUS). The SUS analysis was the focus of this paper. Analysis was performed on different levels: nationally looking at the whole data set and breaking it down by focusing on 2 different regions to explore differences in experienced usability based on the level of transparency.

Results

During the survey period, 423,141 users logged into Journalen, of which 2587 unique users completed the survey (response rate 0.61%). The total mean score for all respondents to the SUS items was 79.81 (SD 14.25), which corresponds to a system with good usability. To further explore whether the level of transparency in a region would affect the user’s experience of the usability of the system, we analyzed the 2 regions with the most respondents: Region Uppsala (the first to launch, with a high level of transparency), and Region Skåne (an early implementer, with a low level of transparency at the time of the survey). Of the participants who responded to at least 1 SUS statement, 520 stated that they had received care in Region Skåne, whereas 331 participants had received care in Region Uppsala. Uppsala’s mean SUS score was 80.71 (SD 13.41), compared with Skåne’s mean of 79.37 (SD 13.78).

Conclusions

The Swedish national PAEHR Journalen has a reasonably good usability (mean SUS score 79.81, SD 14.25); however, further research into more specific usability areas are needed to ensure usefulness and ease of use in the future. A somewhat higher SUS score for the region with high transparency compared with the region with low transparency could indicate a relationship between the perceived usability of a PAEHR and the level of transparency offered, but further research on the relationship between transparency and usability is required.

Development and Validation of a Useful Taxonomy of Patient Portals Based on Characteristics of Patient Engagement

Objective  Taxonomies are classification systems used to reduce complexity and better understand a domain. The present research aims to develop a useful taxonomy for health information managers to classify and compare patient portals based on characteristics appropriate to promote patient engagement. As a result, the taxonomy should contribute to understanding the differences and similarities of the portals. Further, the taxonomy shall support health information managers to more easily define which general type and functionalities of patient portals they need and to select the most suitable solution offered on the market.

Methods  We followed the formal taxonomy-building method proposed by Nickerson et al. Based on a literature review, we created a preliminary taxonomy following the conceptional approach of the model. We then evaluated each taxa's appropriateness by analyzing and classifying 17 patient portals offered by software vendors and 11 patient portals offered by health care providers. After each iteration, we examined the achievement of the determined objective and subjective ending conditions.

Results  After two conceptional approaches to create our taxonomy, and two empirical approaches to evaluate it, the final taxonomy consists of 20 dimensions and 49 characteristics. To make the taxonomy easy to comprehend, we assigned to the dimensions seven aspects related to patient engagement. These aspects are (1) portal design, (2) management, (3) communication, (4) instruction, (5) self-management, (6) self-determination, and (7) data management. The taxonomy is considered finished and useful after all ending conditions that defined beforehand have been fulfilled. We demonstrated that the taxonomy serves to understand the differences and similarities by comparing patient portals. We call our taxonomy “Taxonomy of Patient Portals based on Characteristics of Patient Engagement (TOPCOP).”

Conclusion  We developed the first useful taxonomy for health information managers to classify and compare patient portals. The taxonomy is based on characteristics promoting patient engagement. With 20 dimensions and 49 characteristics, our taxonomy is particularly suitable to discriminate among patient portals and can easily be applied to compare portals. The TOPCOP taxonomy enables health information managers to better understand the differences and similarities of patient portals. Further, the taxonomy may help them to define the type and general functionalities needed. But it also supports them in searching and comparing patient portals offered on the market to select the most suitable solution.

Theories Informing eHealth Implementation: Systematic Review and Typology Classification

Background

Theory-guided approaches to implementation science have informed translation efforts and the acceptance of eHealth (digital health) interventions in clinical care. However, there is scarce evidence on which theories are best suited to addressing the inherent complexity of eHealth implementation.

Objective

The objectives of this systematic review are to identify theories that inform and explain eHealth implementation and to classify these theories using the typology by Sovacool and Hess for theories of sociotechnical change.

Methods

An electronic search was conducted in the PsycINFO, MEDLINE, Embase, CINAHL, Scopus, Sociological Source Ultimate, Web of Science, ABI/INFORM, EBSCO, and ProQuest databases in June 2019. Studies were included if they were published between 2009 and June 2019; were written in English; reported on empirical research, regardless of study or publication type; reported on one or more theories in the context of eHealth implementation; and were published in a peer-reviewed journal. A total of 2 reviewers independently assessed the titles, abstracts, and full texts. Theories identified were classified using a typology for theories of sociotechnical change, which was considered a useful tool for ordering and analyzing the diverse theoretical approaches as a basis for future theory building.

Results

Of the 13,101 potentially relevant titles, 119 studies were included. The review identified 36 theories used to explain implementation approaches in eHealth. The most commonly used approaches were the Technology Acceptance Model (TAM) (n=33) and the Unified Theory of Acceptance and Use of Technology (UTAUT) (n=32). These theories were primarily concerned with individual and interpersonal elements of eHealth acceptance. Less common were theories that reflect the various disorderly social processes and structural dimensions of implementation, such as the normalization process theory (n=17) and the structuration theory (n=6).

Conclusions

Theories currently informing the implementation of eHealth interventions predominantly focus on predicting or explaining end-user acceptance. Theoretical perspectives that capture the dense and intricate relationships and structures required to enact sustainable change are less well represented in the eHealth literature. Given the growing acknowledgment of the inherent complexity of eHealth implementation, future research should develop and test models that recognize and reflect the multidimensional, dynamic, and relational nature of this process.

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.

A Technology Acceptance Model for Deploying Masks to Combat the COVID-19 Pandemic in Taiwan (My Health Bank): Web-Based Cross-sectional Survey Study

BACKGROUND

The successful completion of medical practices often relies on information collection and analysis. Government agencies and medical institutions have encouraged people to use medical information technology (MIT) to manage their conditions and promote personal health. In 2014, Taiwan established the first electronic personal health record (PHR) platform, My Health Bank (MHB), which allows people to access and manage their PHRs at any time. In the face of the COVID-19 pandemic in 2020, Taiwan has used MIT to effectively prevent the spread of COVID-19 and undertaken various prevention measures before the onset of the outbreak. Using MHB to purchase masks in an efficient and orderly way and thoroughly implementing personal protection efforts is highly important to contain disease spread.

OBJECTIVE

This study aims to understand people's intention to use the electronic PHR platform MHB and to investigate the factors affecting their intention to use this platform.

METHODS

From March 31 to April 9, 2014, in a promotion via email and Facebook, participants were asked to fill out a structured questionnaire after watching an introductory video about MHB on YouTube. The questionnaire included seven dimensions: perceived usefulness, perceived ease of use, health literacy, privacy and security, computer self-efficacy, attitude toward use, and behavioral intention to use. Each question was measured on a 5-point Likert scale ranging from "strongly disagree" (1 point) to "strongly agree" (5 points). Descriptive statistics and structural equation analysis were performed using SPSS 21 and AMOS 21 software.

RESULTS

A total of 350 valid questionnaire responses were collected (female: 219/350, 62.6%; age: 21-30 years: 238/350, 68.0%; university-level education: 228/350, 65.1%; occupation as student: 195/350, 56.6%; average monthly income

CONCLUSIONS

From the perspective of the populace, this study explored the factors affecting the use of MHB and constructed an interpretation model with a strong goodness of fit. The results of our analysis are consistent with the technology acceptance model. Through the diverse value-added services of MHB, Taiwan's experience in pandemic prevention with smart technology can facilitate future responses to unknown, emerging infectious diseases.

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Key Words

• COVID-19
• electronic health record
• electronic medical record
• intention
• literacy
• model
• my health bank
• personal health record
• privacy
• protection
• security
• structural equation model
• survey
• technology acceptance model
• usage

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MESH Headings

• Adult
• COVID-19/epidemiology
• COVID-19/prevention & control
• COVID-19/transmission
• Cross-Sectional Studies
• Disease Transmission, Infectious/prevention & control
• Female
• Humans
• Internet
• Male
• Masks
• Pandemics
• SARS-CoV-2
• Surveys and Questionnaires
• Taiwan/epidemiology
• Technology
• Young Adult

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Affiliation(s)

Wen-Hsun Tsai Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan Medical Administration Office, Beitou Branch, Tri-Service General Hospital, Taipei, Taiwan
Yi-Syuan Wu Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan
Chia-Shiang Cheng Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan
Ming-Hao Kuo Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan
Yu-Tien Chang School of Public Health, National Defense Medical Center, Taipei, Taiwan
Fu-Kang Hu Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan Medical Informatics Office, Tri-Service General Hospital, Taipei, Taiwan
Chien-An Sun Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan
Chi-Wen Chang School of Nursing, College of Medicine, Chang-Gung University, Taoyuan, Taiwan Division of Pediatric Endocrinology & Genetics, Department of Pediatrics, Chang-Gung Memorial Hospital, Taoyuan, Taiwan
Ta-Chien Chan Research Center for Humanities and Social Sciences, Academia Sinica, Taipei, Taiwan
Chao-Wen Chen Trauma and Critical Care Service Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
Chia-Cheng Lee Medical Informatics Office, Tri-Service General Hospital, Taipei, Taiwan Division of Colorectal Surgery, Department of Surgery, Tri-Service General Hospital, Taipei, Taiwan
Chi-Ming Chu Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan School of Public Health, National Defense Medical Center, Taipei, Taiwan Big Data Research Center, College of Medicine, Fu-Jen Catholic University, New Taipei City, Taiwan Department of Public Health, China Medical University, Taichung, Taiwan Department of Public Health, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan Department of Healthcare Administration and Medical Informatics, College of Health Sciences, Kaohsiung Medical University, Kaohsiung, Taiwan Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan

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Behavioral Intentions to Use Patient Portals to Disclose HIV and Other Sexually Transmitted Infection Testing Histories with Sexual Partners Among U.S. Sexual Minority Men

Disclosure of HIV and other sexually transmitted infection (HIV/STI) testing history to sexual partners is low among gay, bisexual, and other U.S. sexual minority men (SMM). Patient portals (PP) could increase HIV/STI testing history disclosure. This study estimated the predictive validity of the Enhancing Dyadic Communication (EDC) latent construct for perceived behavioral intentions to use PP for HIV/STI test disclosures. A randomized subset of SMM completed the Patient Portal Sexual Health Instrument as part of the 2018 American Men's Internet Survey. Multivariable logistic regression models estimated associations between EDC and intentions to use PP for test disclosures. Among a sample of 1,509 SMM aged 15 to 77 years, EDC was associated with intentions to use PP to disclose test history with main partners (aOR 2.17; 95% CI 1.90 to 2.47) and non-main partners (aOR 2.39; 95%CI 2.07 to 2.76). Assessing EDC could be useful in clinical settings for interventions encouraging patients to communicate with partners about testing.

Using the Patient Portal Sexual Health Instrument in Surveys and Patient Questionnaires Among Sexual Minority Men in the United States: Cross-sectional Psychometric Validation Study

Background

Patient portal modules, including electronic personal health records, health education, and prescription refill ordering, may be leveraged to address the sexually transmitted infection (STI) burden, including HIV, among gay, bisexual, and other sexual minority men (SMM). Theoretical frameworks in the implementation sciences highlight examining constructs of innovation attributes and performance expectations as key determinants of behavioral intentions and the use of new web-based health technologies. However, behavioral intentions to use patient portals for HIV and other STI prevention and care among SMM is understudied.

Objective

The aim of this study is to develop a brief instrument for measuring attitudes focused on using patient portals for STI prevention and care among a nationwide sample of SMM.

Methods

A total of 12 items of the American Men’s Internet Survey-Patient Portal Sexual Health Instrument (AMIS-PPSHI) were adapted from a previous study. Psychometric analyses of the AMIS-PPSHI items were conducted among a randomized subset of 2018 AMIS participants reporting web-based access to their health records (N=1375). Parallel analysis and inspection of eigenvalues in a principal component analysis (PCA) informed factor retention in exploratory factor analysis (EFA). After EFA, Cronbach α was used to examine the internal consistency of the scale and its subscales. Confirmatory factor analysis (CFA) was used to assess the goodness of fit of the final factor structure. We calculated the total AMIS-PPSHI scale scores for comparisons within group categories, including age, STI diagnosis history, recency of testing, serious mental illness, and anticipated health care stigma.

Results

The AMIS-PPSHI scale resulting from EFA consisted of 12 items and had good internal consistency (α=.84). The EFA suggested 3 subscales: sexual health engagement and awareness (α=.87), enhancing dyadic communication (α=.87), and managing sexual health care (α=.79). CFA demonstrated good fit in the 3-factor PPSHI structure: root mean square error of approximation=0.061, comparative fit index=0.964, Tucker-Lewis index=0.953, and standardized root mean square residual=0.041. The most notable differences were lower scores on the enhanced dyadic communication subscale among people living with HIV.

Conclusions

PPSHI is a brief instrument with strong psychometric properties that may be adapted for use in large surveys and patient questionnaires in other settings. Scores demonstrate that patient portals are favorable web-based solutions to deliver health services focused on STI prevention and care among SMM in the United States. More attention is needed to address the privacy implications of interpersonal use of patient portals outside of traditional health settings among persons with HIV.

Teenagers’ behavioural intention towards wearable technologies and intention to recommend others: an empirical study in Bangladesh

Purpose

The purpose of this study is to investigate the factors, which drive teenagers’ behavioural intention to adopt wearable technologies and their behavioural intention to recommend others.

Design/methodology/approach

This study proposes a new adoption model combining two different models including the extended unified theory of acceptance and use of technology and the theory of planned behaviour, which provided relevant contributions for understanding the adoption of wearable technologies. A structural equation modelling approach using analysis of a moment structures 23 software was used to analyse the data collected from 318 respondents.

Findings

Findings of this study reveals that performance expectancy (β = 0.28; t = 2.049), facilitating conditions (β = 0.28; t = 1.989), social influence (β = 0.23; t = 3.150) and attitude (β = 0.18; t = 3.246) have a statistically significant impact on behavioural intention. Additionally, behavioural intention (β = 0.15; t = 2.543) and attitude (β = 0.15; t = 3.261) have a statistically significant impact on intention to recommend others. However, effort expectancy, price value, hedonic motivation and habit did not have a significant influence on behavioural intention.

Practical implications

In this study, the understanding of the determinants contributing to teenagers’ behavioural intention to use wearable technologies and driving their intention to recommend others to adopt these devices will provide insights to practitioners and decision makers to customize the features of wearable devices to promote sustainable use of these technologies.

Originality/value

This study is among the first to investigate wearable technologies from behavioural perspectives especially on teenagers in Bangladesh. Hence, the findings of this study will help to comprehensively explain teenagers’ behavioural intention to adopt wearable technologies and their intention to recommend others.

Factors affecting the acceptance of integrated electronic personal health records in Saudi Arabia: The impact of e-health literacy

Background:

National implementation of electronic personal health record (ePHR) systems is of vital importance to governments worldwide because this type of technology promises to promote and enhance healthcare. Although there is widespread agreement as to the advantages of ePHRs, the level of awareness and acceptance of this technology among healthcare consumers has been low.

Objective:

The aim of this study was to identify the factors that can influence the acceptance and use of an integrated ePHR system in Saudi Arabia.

Method:

The unified theory of acceptance and use of technology model was extended in this study to include e-health literacy (e-HL) and tested using structural equation modelling. Data were collected via a questionnaire survey, resulting in 794 valid responses.

Results:

The proposed model explained 56% of the variance in behavioural intention (BI) to use the integrated ePHR system. Findings also highlighted the significance of performance expectancy, effort expectancy, social influence (SI) and e-HL as determinants of Saudi healthcare consumers’ intentions to accept and use the integrated ePHR system. Additionally, assessment of the research model moderators revealed that only gender had a moderating influence on the relationship between SI and BI. Finally, findings showed a low level of awareness among Saudi citizens about the national implementation of an integrated ePHR system, suggesting the need to promote a greater and more widespread awareness of the system and to demonstrate its usefulness.

Conclusion:

Findings from this study can assist governments, policymakers and developers of health information technologies and systems by identifying important factors that may influence the diffusion and use of integrated ePHRs.

Digital technology to address HIV and other sexually transmitted infection disparities: Intentions to disclose online personal health records to sex partners among students at a historically Black college

Patient portals are creating new opportunities for youth to disclose high-fidelity sexually transmitted infection (STI) laboratory test result histories to sex partners. Among an online survey sample, we describe latent constructs and other variables associated with perceived behavioral intentions to disclose STI test history using patient portals. Participants were co-ed students aged 18 to 25 years (N = 354) attending a southern United States Historically Black College and University in 2015. Three reliable latent constructs were identified by conducting psychometric analyses on 27 survey items. Latent constructs represent, a) STI test disclosure valuation beliefs, b) communication practices, and c) performance expectancy beliefs for disclosing with patient portals. Multivariable logistic regression was used to estimate the relationship of latent constructs to perceived behavioral intentions to disclose STI test history using patient portals. Approximately 14% (48/354) reported patient portal use prior to study and 59% (208/354) endorsed behavioral intentions to use patient portals to disclose STI test history. The latent construct reflecting performance expectancies of patient portals to improve communication and accuracy of disclosed test information was associated with behavioral intentions to disclose STI test histories using patient portals [adjusted odds ratio (AOR) = 1.15; 95% CI = 1.08 to 1.22; p<0.001]. Latent constructs representing communication valuation beliefs and practices were not associated with intentions. Self-reporting prior STI diagnosis was also associated with intentions to disclose using patient portals (AOR = 2.84; 95% CI = 1.15 to 6.96; p = 0.02). Point of care messages focused on improvements to validating test results, communication, and empowerment, may be an effective strategy to support the adoption of patient portals for STI prevention among populations of college-aged Black youth.

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.

Effectiveness of Lilly Connected Care Program (LCCP) App-Based Diabetes Education for Patients With Type 2 Diabetes Treated With Insulin: Retrospective Real-World Study

Background

Diabetes poses heavy economic and social burdens worldwide. Mobile apps show great potential for diabetes self-management education. However, there is limited evidence for the effectiveness of providing general diabetes education through mobile apps.

Objective

The aim of this study was to clarify the effectiveness of Lilly Connected Care Program (LCCP) app-based diabetes education for glycemic control.

Methods

This retrospective cohort study included patients with diabetes recruited to the LCCP platform from September 1, 2018, to May 31, 2019. Each patient was followed for 12 weeks. According to the number of diabetes education courses they had completed, the patients were divided into the following three groups: group A (0-4 courses), group B (5-29 courses), and group C (≥30 courses). The main outcomes were the change in blood glucose at the 12th week compared with baseline and the differences in blood glucose at the 12th week among the three groups. The associations of the number of diabetes education courses completed with the average blood glucose and frequency of self-monitoring of blood glucose (SMBG) at the 12th week were assessed by multivariate linear regression analyses controlling for other confounding covariates. Univariate and multivariate linear regression analyses were used to assess factors influencing patients’ engagement in the diabetes education courses.

Results

A total of 5011 participants were enrolled. Their mean fasting blood glucose (FBG) and postprandial blood glucose (PBG) were significantly lower at the 12th week than at baseline (FBG, 7.46 [standard deviation (SD) 1.95] vs 7.79 [SD 2.18] mmol/L, P<.001; PBG, 8.94 [SD 2.74] vs 9.53 [SD 2.81] mmol/L, P<.001). The groups that completed more diabetes education courses had lower FBG (group B, β=−0.14, 95% CI −0.26 to −0.03; group C, β=−0.29, 95% CI −0.41 to −0.16; P for trend <.001) and PBG (group B, β=−0.29, 95% CI −0.46 to −0.11; group C, β=−0.47, 95% CI −0.66 to −0.28; P for trend <.001) and a higher frequency of SMBG at the 12th week (group B, β=1.17, 95% CI 0.81-1.53; group C, β=4.21, 95% CI 3.81-4.62; P for trend <.001) when compared with the findings in group A. Age and education were related to patients’ engagement in the diabetes education courses. Middle-aged patients (35-59 years old) and elderly patients (≥60 years old) completed more diabetes education courses (middle-aged group, β=2.22, P=.01; elderly group, β=2.42, P=.02) than young patients (18-34 years old).

Conclusions

LCCP app-based diabetes education is effective for glycemic control and SMBG behavior improvement in patients with type 2 diabetes receiving insulin therapy. Young patients’ engagement in the education courses was relatively low. We need to conduct in-depth interviews with users to further improve the curriculum.

Users' acceptance of electronic patient portals in Lebanon

Background

Acceptance of Electronic patient portal (EPP) is instrumental for its success. Studies on users’ acceptance in the Middle East region are scarce. This study aims to use the TAM as a framework to quantitatively describe potential users, diabetic and chronic high blood pressure patients and their providers, intention to use and factors influencing the intention to use EPP at AUBMC-FMC We concurrently test the internal construct validity and the reliability of the TAM.

Methods

A cross-sectional survey design and the vignette approach were used. For validation, we needed a minimum of 180 patients; all 35 attending physicians and 11 registered nurses were targeted. We used descriptive statistics to calculate the intention to use EPP and its determinants based on the TAM constructs. Exploratory factor analysis (EFA) and structural equation modeling (SEM) were employed to estimate significant path coefficients for patients only as the sample size of providers was too small.

Results

We had 199 patients, half intended to use EPP; 73% of providers (N = 17) intended to use EPP. Perceived ease of use and privacy concerns were significantly higher among providers than patients (Mean (M) = 0.77 vs M = 0.42 (CI: − 0.623; − 0.081)) and (M = 3.67 vs M = 2.13, CI: − 2.16; − 0.91) respectively; other constructs were not significantly different. Reliability of TAM revealed a Cronbach Alpha of α=.91. EFA showed that three components explained 73.48% of the variance: Behavioral Intention of Use (14.9%), Perceived Ease of Use (50.74%), Perceived Usefulness (7.84%). SEM found that perceived ease of use increased perceived usefulness (standardized regression weight = 0.49); perceived usefulness (0.51) had more predictive value than perceived ease of use (0.27) to explain the behavioral intention of use of the EPP.

Conclusions

We found that providers valued the usefulness of EPP and were mostly intending to use it. This finding has yet to be tested in future studies testing actual use as intention and actual use may not be concordant. The intention to use among patients was lower than those reported in developed countries. We identified two factors that we need to address to increase use, namely perceived ease and usefulness, and proposed practical implications to address them; future research directions were also discussed.

Psychosocial Factors Affecting Artificial Intelligence Adoption in Health Care in China: Cross-Sectional Study

Background

Poor quality primary health care is a major issue in China, particularly in blindness prevention. Artificial intelligence (AI) could provide early screening and accurate auxiliary diagnosis to improve primary care services and reduce unnecessary referrals, but the application of AI in medical settings is still an emerging field.

Objective

This study aimed to investigate the general public’s acceptance of ophthalmic AI devices, with reference to those already used in China, and the interrelated influencing factors that shape people’s intention to use these devices.

Methods

We proposed a model of ophthalmic AI acceptance based on technology acceptance theories and variables from other health care–related studies. The model was verified via a 32-item questionnaire with 7-point Likert scales completed by 474 respondents (nationally random sampled). Structural equation modeling was used to evaluate item and construct reliability and validity via a confirmatory factor analysis, and the model’s path effects, significance, goodness of fit, and mediation and moderation effects were analyzed.

Results

Standardized factor loadings of items were between 0.583 and 0.876. Composite reliability of 9 constructs ranged from 0.673 to 0.841. The discriminant validity of all constructs met the Fornell and Larcker criteria. Model fit indicators such as standardized root mean square residual (0.057), comparative fit index (0.915), and root mean squared error of approximation (0.049) demonstrated good fit. Intention to use (R²=0.515) is significantly affected by subjective norms (beta=.408; P<.001), perceived usefulness (beta=.336; P=.03), and resistance bias (beta=–.237; P=.02). Subjective norms and perceived behavior control had an indirect impact on intention to use through perceived usefulness and perceived ease of use. Eye health consciousness had an indirect positive effect on intention to use through perceived usefulness. Trust had a significant moderation effect (beta=–.095; P=.049) on the effect path of perceived usefulness to intention to use.

Conclusions

The item, construct, and model indicators indicate reliable interpretation power and help explain the levels of public acceptance of ophthalmic AI devices in China. The influence of subjective norms can be linked to Confucian culture, collectivism, authoritarianism, and conformity mentality in China. Overall, the use of AI in diagnostics and clinical laboratory analysis is underdeveloped, and the Chinese public are generally mistrustful of medical staff and the Chinese medical system. Stakeholders such as doctors and AI suppliers should therefore avoid making misleading or over-exaggerated claims in the promotion of AI health care products.

Human Factors and Sociotechnical Issues

OBJECTIVE

To summarize significant research contributions on human factors (HF) and organizational issues in medical informatics published in 2018.

METHODS

An extensive search using PubMed/Medline and Web of Science^® was conducted to identify the scientific contributions published in 2018 that address human factors and organizational issues in medical informatics. The selection process comprised three steps: (i) 15 candidate best papers were first selected by the two section editors, (ii) external reviewers from internationally renowned research teams reviewed each candidate best paper, and (iii) the final selection of four best papers was conducted by the editorial board of the Yearbook.

RESULTS

The four selected best papers are excellent contributions to the HF literature: they show the added value of HF studies by providing nice illustrated and rigorous interventions.

CONCLUSION

HF interventions are known to have great potential to contribute to efficient HIT design, but the interventions still face challenges in successfully demonstrating their value to the main stakeholders of the healthcare domain. There is a need to strengthen the demand for high-quality HF studies by increasing awareness among powerful stakeholders of the value of high-quality HF studies.

Factors Influencing Patients' Intentions to Use Diabetes Management Apps Based on an Extended Unified Theory of Acceptance and Use of Technology Model: Web-Based Survey

BACKGROUND

Diabetes poses heavy social and economic burdens worldwide. Diabetes management apps show great potential for diabetes self-management. However, the adoption of diabetes management apps by diabetes patients is poor. The factors influencing patients' intention to use these apps are unclear. Understanding the patients' behavioral intention is necessary to support the development and promotion of diabetes app use.

OBJECTIVE

This study aimed to identify the determinants of patients' intention to use diabetes management apps based on an integrated theoretical model.

METHODS

The hypotheses of our research model were developed based on an extended Unified Theory of Acceptance and Use of Technology (UTAUT). From April 20 to May 20, 2019, adult patients with diabetes across China, who were familiar with diabetes management apps, were surveyed using the Web-based survey tool Sojump. Structural equation modeling was used to analyze the data.

RESULTS

A total of 746 participants who met the inclusion criteria completed the survey. The fitness indices suggested that the collected data fit well with the research model. The model explained 62.6% of the variance in performance expectancy and 57.1% of the variance in behavioral intention. Performance expectancy and social influence had the strongest total effects on behavioral intention (β=0.482; P=.001). Performance expectancy (β=0.482; P=.001), social influence (β=0.223; P=.003), facilitating conditions (β=0.17; P=.006), perceived disease threat (β=0.073; P=.005), and perceived privacy risk (β=-0.073; P=.012) had direct effects on behavioral intention. Additionally, social influence, effort expectancy, and facilitating conditions had indirect effects on behavioral intention that were mediated by performance expectancy. Social influence had the highest indirect effects among the three constructs (β=0.259; P=.001).

CONCLUSIONS

Performance expectancy and social influence are the most important determinants of the intention to use diabetes management apps. Health care technology companies should improve the usefulness of apps and carry out research to provide clinical evidence for the apps' effectiveness, which will benefit the promotion of these apps. Facilitating conditions and perceived privacy risk also have an impact on behavioral intention. Therefore, it is necessary to improve facilitating conditions and provide solid privacy protection. Our study supports the use of UTAUT in explaining patients' intention to use diabetes management apps. Context-related determinants should also be taken into consideration.

Investigating Factors Impelling the Adoption of e-Health: A Perspective of African Expats in China

The purpose of the study was to analyze the factors affecting the acceptance and adoption of e-Health applications among African expats in China from the patient’s perspective. This research used extended technology acceptance model (TAM) with the addition of privacy and trust. The survey method with the structured questionnaire was used to collect data from more than 300 African expats in three Tier 1 cities of China. Hypotheses were tested using partial least squares (PLS) method, a structural equation modeling (SEM) based statistical technique. The results show that perceived usefulness, perceived ease of use (PEU), and privacy have significant effects on intention to use (INT) e-Health technologies. Moreover, PEU endorses positive impact on perceived usefulness. The results also revealed that gender was partially associated with the acceptance and use of e-Health technologies. However, surprisingly, trust had an insignificant effect on INT of e-Health. The results of the current research provide the foundation for the development of policies and strategies for the enhancement of e-Health services to African expats in China. Moreover, the acceptance model of current study can be modified easily because of its generic approach for the investigation of adoption of e-Health services among other developing countries’ expats in China.

The Use of an Electronic Health Record Patient Portal to Access Diagnostic Test Results by Emergency Patients at an Academic Medical Center: Retrospective Study

BACKGROUND

Electronic health record (EHR) patient portals provide a means by which patients can access their health information, including diagnostic test results. Little is known about portal usage by emergency department (ED) patients.

OBJECTIVE

The study aimed to assess patient portal utilization by ED patients at an academic medical center using account activation rates along with the rates of access of diagnostic test results (laboratory results and radiology reports), analyzing the impact of age, gender, and self-reported patient race.

METHODS

This institutional review board-approved retrospective study was performed at a 60,000-visits-per-year university-based ED. We utilized EHR data reporting tools to examine EHR portal activation and utilization for all patients who had at least one ED encounter with one or more diagnostic tests performed between October 1, 2016, and October 1, 2017. The total dataset for laboratory testing included 208,635 laboratory tests on 25,361 unique patients, of which 9482 (37.39%) had active portal accounts. The total dataset for radiologic imaging included 23,504 radiology studies on 14,455 unique patients, of which 5439 (37.63%) had an active portal account.

RESULTS

Overall, 8.90% (18,573/208,635) of laboratory tests and 8.97% (2019/22,504) of radiology reports ordered in the ED were viewed in the patient portal. The highest rates of viewing of laboratory and radiology results were seen for those who were female, were aged 0 to 11 years (parent or guardian viewing by proxy) and 18 to 60 years, and self-reported their race as Caucasian or Asian. The lowest rates were for those who were teenagers, aged older than 81 years, African American/black, and Hispanic/Latino. Infectious disease, urinalysis, and pregnancy testing constituted the highest number of laboratory tests viewed. Magnetic resonance imaging reports were viewed at higher rates than computed tomography or x-ray studies (P<.001). Approximately half of all the diagnostic test results accessed by patients were reviewed within 72 hours of availability in the patient portal (laboratory results: 9904/18,573, 53.32% and radiology reports: 971/2019, 48.1%). On the other extreme, 19.9% (3701/18,573) of laboratory results and 31.6% (639/2019) of radiology reports were viewed more than 2 weeks after availability in the portal.

CONCLUSIONS

The data highlight the relatively low use of a patient portal by ED patients and existing disparities between patient groups. There can be wide lag time (months) between result/report availability and access by patients. Opportunities for improvement exist for both activation and more robust utilization of patient portals by ED patients.