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  JMIR Theme Issue 2020: COVID-19...

  Oct 29, 2020

  Determinants of Patients’ Intention to Use the Online Inquiry Services Provided by Internet Hospitals: Empirical Evidence From China

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  Authors List:

  • Dehe Li  
  • Yinhuan Hu  
  • Holger Pfaff  
  • Liuming Wang  
  • Lu Deng  
  • Chuntao Lu  
  • Shixiao Xia  
  • Siyu Cheng  
  • Ximin Zhu  
  • Xiaoyue Wu  

  Abstract:

  Background: Internet hospitals show great potential for adequately fulfilling people’s demands for high-quality outpatient services, and with the normalization of the epidemic prevention and control of COVID-19, internet hospitals play an increasingly important role in delivering health services to the public. However, the factors that influence patients’ intention to use the online inquiry services provided by internet hospitals remain unclear. Understanding the patients’ behavioral intention is necessary to support the development of internet hospitals in China and promote patients’ intention to use online inquiry services provided by internet hospitals during the prevention and control of the COVID-19 epidemic. Objective: The purpose of this study is to identify the determinants of patients’ intention to use the online inquiry services provided by internet hospitals based on the theory of planned behavior (TPB). Methods: The hypotheses of our research model were developed based on the TPB. A questionnaire was developed through patient interviews, verified using a presurvey, and used for data collection for this study. The cluster sampling technique was used to include respondents with chronic diseases. Structural equation modeling was used to test the research hypotheses. Results: A total of 638 valid responses were received from patients with chronic diseases. The goodness-of-fit indexes corroborated that the research model was a good fit for the collected data. The model explained 45.9% of the variance in attitude toward the behavior and 60.5% of the variance in behavioral intention. Perceived behavioral control and perceived severity of disease had the strongest total effects on behavioral intention (β=.624, P=.004 and β=.544, P=.003, respectively). Moreover, perceived convenience, perceived information risk, emotional preference, and health consciousness had indirect effects on behavioral intention, and these effects were mediated by attitude toward the behavior. Among the four constructs, perceived convenience had the highest indirect effect on behavioral intention (β=.207; P=.001). Conclusions: Perceived behavioral control and perceived severity of disease are the most important determinants of patients’ intention to use the online inquiry services provided by internet hospitals. Therefore, internet hospitals should further optimize the design of online service delivery and ensure a reasonable assembly of high-quality experts, which will benefit the promotion of patients’ adoption intention toward online inquiry services for health purposes. Perceived convenience, emotional preference, and perceived risks also have effects on behavioral intention. Therefore, the relevant quality control standards and regulations for internet hospitals should be further developed and improved, and the measures to protect personal information should be strengthened to ensure the patient safety. Our study supports the use of the TPB in explaining patients’ intention to use online inquiry services provided by internet hospitals.

  • J Med Internet Res 2020;22(10):e22716

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  eHealth Literacy / Digital Literacy

  Oct 29, 2020

  Undergraduate Medical Competencies in Digital Health and Curricular Module Development: Mixed Methods Study

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  Authors List:

  • Akira-Sebastian Poncette  
  • Daniel Leon Glauert  
  • Lina Mosch  
  • Katarina Braune  
  • Felix Balzer  
  • David Back  

  Abstract:

  Background: Owing to an increase in digital technologies in health care, recently leveraged by the COVID-19 pandemic, physicians are required to use these technologies appropriately and to be familiar with their implications on patient care, the health system, and society. Therefore, medical students should be confronted with digital health during their medical education. However, corresponding teaching formats and concepts are still largely lacking in the medical curricula. Objective: This study aims to introduce digital health as a curricular module at a German medical school and to identify undergraduate medical competencies in digital health and their suitable teaching methods. Methods: We developed a 3-week curricular module on digital health for third-year medical students at a large German medical school, taking place for the first time in January 2020. Semistructured interviews with 5 digital health experts were recorded, transcribed, and analyzed using an abductive approach. We obtained feedback from the participating students and lecturers of the module through a 17-item survey questionnaire. Results: The module received overall positive feedback from both students and lecturers who expressed the need for further digital health education and stated that the field is very important for clinical care and is underrepresented in the current medical curriculum. We extracted a detailed overview of digital health competencies, skills, and knowledge to teach the students from the expert interviews. They also contained suggestions for teaching methods and statements supporting the urgency of the implementation of digital health education in the mandatory curriculum. Conclusions: An elective class seems to be a suitable format for the timely introduction of digital health education. However, a longitudinal implementation in the mandatory curriculum should be the goal. Beyond training future physicians in digital skills and teaching them digital health’s ethical, legal, and social implications, the experience-based development of a critical digital health mindset with openness to innovation and the ability to assess ever-changing health technologies through a broad transdisciplinary approach to translate research into clinical routine seem more important. Therefore, the teaching of digital health should be as practice-based as possible and involve the educational cooperation of different institutions and academic disciplines.

  • J Med Internet Res 2020;22(10):e22161

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  Review

  Oct 29, 2020

  Primary Prevention of Cardiovascular Disease and Type 2 Diabetes Mellitus Using Mobile Health Technology: Systematic Review of the Literature

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  Authors List:

  • Vera Helen Buss  
  • Stuart Leesong  
  • Margo Barr  
  • Marlien Varnfield  
  • Mark Harris  

  Abstract:

  Background: Digital technology is an opportunity for public health interventions to reach a large part of the population. Objective: This systematic literature review aimed to assess the effectiveness of mobile health–based interventions in reducing the risk of cardiovascular disease and type 2 diabetes mellitus. Methods: We conducted the systematic search in 7 electronic databases using a predefined search strategy. We included articles published between inception of the databases and March 2019 if they reported on the effectiveness of an intervention for prevention of cardiovascular disease or type 2 diabetes via mobile technology. One researcher performed the search, study selection, data extraction, and methodological quality assessment. The steps were validated by the other members of the research team Results: The search yielded 941 articles for cardiovascular disease, of which 3 met the inclusion criteria, and 732 for type 2 diabetes, of which 6 met the inclusion criteria. The methodological quality of the studies was low, with the main issue being nonblinding of participants. Of the selected studies, 4 used SMS text messaging, 1 used WhatsApp, and the remaining ones used specific smartphone apps. Weight loss and reduction in BMI were the most reported successful outcomes (reported in 4 studies). Conclusions: Evidence on the effectiveness of mobile health-based interventions in reducing the risk for cardiovascular disease and type 2 diabetes is low due to the quality of the studies and the small effects that were measured. This highlights the need for further high-quality research to investigate the potential of mobile health interventions. Trial Registration: International Prospective Register of Systematic Reviews (PROSPERO) CRD42019135405; https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=135405

  • J Med Internet Res 2020;22(10):e21159

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  New Methods

  Oct 29, 2020

  Influenza Screening via Deep Learning Using a Combination of Epidemiological and Patient-Generated Health Data: Development and Validation Study

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  Authors List:

  • Hyunwoo Choo  
  • Myeongchan Kim  
  • Jiyun Choi  
  • Jaewon Shin  
  • Soo-Yong Shin  

  Abstract:

  Background: Screening for influenza in primary care is challenging due to the low sensitivity of rapid antigen tests and the lack of proper screening tests. Objective: The aim of this study was to develop a machine learning–based screening tool using patient-generated health data (PGHD) obtained from a mobile health (mHealth) app. Methods: We trained a deep learning model based on a gated recurrent unit to screen influenza using PGHD, including each patient’s fever pattern and drug administration records. We used meteorological data and app-based surveillance of the weekly number of patients with influenza. We defined a single episode as the set of consecutive days, including the day the user was diagnosed with influenza or another disease. Any record a user entered 24 hours after his or her last record was considered to be the start of a new episode. Each episode contained data on the user’s age, gender, weight, and at least one body temperature record. The total number of episodes was 6657. Of these, there were 3326 episodes within which influenza was diagnosed. We divided these episodes into 80% training sets (2664/3330) and 20% test sets (666/3330). A 5-fold cross-validation was used on the training set. Results: We achieved reliable performance with an accuracy of 82%, a sensitivity of 84%, and a specificity of 80% in the test set. After the effect of each input variable was evaluated, app-based surveillance was observed to be the most influential variable. The correlation between the duration of input data and performance was not statistically significant (P=.09). Conclusions: These findings suggest that PGHD from an mHealth app could be a complementary tool for influenza screening. In addition, PGHD, along with traditional clinical data, could be used to improve health conditions. Trial Registration:

  • J Med Internet Res 2020;22(10):e21369

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  Viewpoint

  Oct 29, 2020

  Maximizing the Potential of Patient-Reported Assessments by Using the Open-Source Concerto Platform With Computerized Adaptive Testing and Machine Learning

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  Authors List:

  • Conrad Harrison  
  • Bao Sheng Loe  
  • Przemysław Lis  
  • Chris Sidey-Gibbons  

  Abstract:

  Patient-reported assessments are transforming many facets of health care, but there is scope to modernize their delivery. Contemporary assessment techniques like computerized adaptive testing (CAT) and machine learning can be applied to patient-reported assessments to reduce burden on both patients and health care professionals; improve test accuracy; and provide individualized, actionable feedback. The Concerto platform is a highly adaptable, secure, and easy-to-use console that can harness the power of CAT and machine learning for developing and administering advanced patient-reported assessments. This paper introduces readers to contemporary assessment techniques and the Concerto platform. It reviews advances in the field of patient-reported assessment that have been driven by the Concerto platform and explains how to create an advanced, adaptive assessment, for free, with minimal prior experience with CAT or programming.

  • J Med Internet Res 2020;22(10):e20950

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  Theoretical Frameworks and Concepts

  Oct 29, 2020

  Digital Micro Interventions for Behavioral and Mental Health Gains: Core Components and Conceptualization of Digital Micro Intervention Care

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  Authors List:

  • Amit Baumel  
  • Theresa Fleming  
  • Stephen M Schueller  

  Abstract:

  Although many people access publicly available digital behavioral and mental health interventions, most do not invest as much effort in these interventions as hoped or intended by intervention developers, and ongoing engagement is often low. Thus, the impact of such interventions is minimized by a misalignment between intervention design and user behavior. Digital micro interventions are highly focused interventions delivered in the context of a person’s daily life with little burden on the individual. We propose that these interventions have the potential to disruptively expand the reach of beneficial therapeutics by lowering the bar for entry to an intervention and the effort needed for purposeful engagement. This paper provides a conceptualization of digital micro interventions, their component parts, and principles guiding their use as building blocks of a larger therapeutic process (ie, digital micro intervention care). The model represented provides a structure that could improve the design, delivery, and research on digital micro interventions and ultimately improve behavioral and mental health care and care delivery.

  • J Med Internet Res 2020;22(10):e20631

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  Consumer & Patient Education and...

  Oct 29, 2020

  Information Access and Use by Patients With Cancer and Their Friends and Family: Development of a Grounded Theory

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  Authors List:

  • Maclean Thiessen  
  • Shane Sinclair  
  • Patricia A Tang  
  • Shelley Raffin Bouchal  

  Abstract:

  Background: Information has been identified as a commonly unmet supportive care need for those living with cancer (ie, patients and their friends and family). The information needed to help individuals plan their lives around the consequences of cancer, such as the receipt of health care, is an example of an important informational need. A suitable theory to guide the development of interventions designed to meet this informational need has not been identified by the authors. Objective: The aim of this study is to generate a grounded theory capable of guiding the development of interventions designed to assist those living with cancer in meeting their informational needs. Methods: Classic grounded theory was used to analyze data collected through digitally recorded one-on-one audio interviews with 31 patients with cancer and 29 friends and family members. These interviews focused on how the participants had accessed and used information to plan their lives and what barriers they faced in obtaining and using this information. Results: The theory that emerged consisted of 4 variables: personal projects, cancer as a source of disruption to personal projects, information as the process of accessing and interpreting cancer-related data (CRD) to inform action, and CRD quality as defined by accessibility, credibility, applicability, and framing. CRD quality as a moderator of personal project disruption by cancer is the core concept of this theory. Conclusions: Informational resources providing accessible, credible, applicable, and positively framed CRD are likely key to meeting the information needs of those affected by cancer. Web-based informational resources delivering high-quality CRD focused on assisting individuals living with cancer in maintaining and planning their personal projects are predicted to improve quality of life. Research is needed to develop and integrate resources informed by this theoretical framework into clinical practice.

  • J Med Internet Res 2020;22(10):e20510

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  Patient-Reported Outcome Measures...

  Oct 29, 2020

  Web-Based Patient-Reported Outcome Measures for Personalized Treatment and Care (PROMPT-Care): Multicenter Pragmatic Nonrandomized Trial

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  Authors List:

  • Afaf Girgis  
  • Ivana Durcinoska  
  • Anthony Arnold  
  • Joseph Descallar  
  • Nasreen Kaadan  
  • Eng-Siew Koh  
  • Andrew Miller  
  • Weng Ng  
  • Martin Carolan  
  • Stephen A Della-Fiorentina  
  • Sandra Avery  
  • Geoff P Delaney  

  Abstract:

  Background: Despite the acceptability and efficacy of e–patient-reported outcome (ePRO) systems, implementation in routine clinical care remains challenging. Objective: This pragmatic trial implemented the PROMPT-Care (Patient Reported Outcome Measures for Personalized Treatment and Care) web-based system into existing clinical workflows and evaluated its effectiveness among a diverse population of patients with cancer. Methods: Adult patients with solid tumors receiving active treatment or follow-up care in four cancer centers were enrolled. The PROMPT-Care intervention supported patient management through (1) monthly off-site electronic PRO physical symptom and psychosocial well-being assessments, (2) automated electronic clinical alerts notifying the care team of unresolved clinical issues following two consecutive assessments, and (3) tailored online patient self-management resources. Propensity score matching was used to match controls with intervention patients in a 4:1 ratio for patient age, sex, and treatment status. The primary outcome was a reduction in emergency department presentations. Secondary outcomes were time spent on chemotherapy and the number of allied health service referrals. Results: From April 2016 to October 2018, 328 patients from four public hospitals received the intervention. Matched controls (n=1312) comprised the general population of patients with cancer, seen at the participating hospitals during the study period. Emergency department visits were significantly reduced by 33% (P=.02) among patients receiving the intervention compared with patients in the matched controls. No significant associations were found in allied health referrals or time to end of chemotherapy. At baseline, the most common patient reported outcomes (above-threshold) were fatigue (39%), tiredness (38.4%), worry (32.9%), general wellbeing (32.9%), and sleep (24.1%), aligning with the most frequently accessed self-management domain pages of physical well-being (36%) and emotional well-being (23%). The majority of clinical feedback reports were reviewed by nursing staff (729/893, 82%), largely in response to the automated clinical alerts (n=877). Conclusions: Algorithm-supported web-based systems utilizing patient reported outcomes in clinical practice reduced emergency department presentations among a diverse population of patients with cancer. This study also highlighted the importance of (1) automated triggers for reviewing above-threshold results in patient reports, rather than passive manual review of patient records; (2) the instrumental role nurses play in managing alerts; and (3) providing patients with resources to support guided self-management, where appropriate. Together, these factors will inform the integration of web-based PRO systems into future models of routine cancer care. Trial Registration: Australian New Zealand Clinical Trials Registry ACTRN12616000615482; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=370633

  • J Med Internet Res 2020;22(10):e19685

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  Clinical Information and Decision Making

  Oct 29, 2020

  Integrating the Practical Robust Implementation and Sustainability Model With Best Practices in Clinical Decision Support Design: Implementation Science...

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  Authors List:

  • Katy E Trinkley  
  • Michael G Kahn  
  • Tellen D Bennett  
  • Russell E Glasgow  
  • Heather Haugen  
  • David P Kao  
  • Miranda E Kroehl  
  • Chen-Tan Lin  
  • Daniel C Malone  
  • Daniel D Matlock  

  Abstract:

  Background: Clinical decision support (CDS) design best practices are intended to provide a narrative representation of factors that influence the success of CDS tools. However, they provide incomplete direction on evidence-based implementation principles. Objective: This study aims to describe an integrated approach toward applying an existing implementation science (IS) framework with CDS design best practices to improve the effectiveness, sustainability, and reproducibility of CDS implementations. Methods: We selected the Practical Robust Implementation and Sustainability Model (PRISM) IS framework. We identified areas where PRISM and CDS design best practices complemented each other and defined methods to address each. Lessons learned from applying these methods were then used to further refine the integrated approach. Results: Our integrated approach to applying PRISM with CDS design best practices consists of 5 key phases that iteratively interact and inform each other: multilevel stakeholder engagement, designing the CDS, design and usability testing, thoughtful deployment, and performance evaluation and maintenance. The approach is led by a dedicated implementation team that includes clinical informatics and analyst builder expertise. Conclusions: Integrating PRISM with CDS design best practices extends user-centered design and accounts for the multilevel, interacting, and dynamic factors that influence CDS implementation in health care. Integrating PRISM with CDS design best practices synthesizes the many known contextual factors that can influence the success of CDS tools, thereby enhancing the reproducibility and sustainability of CDS implementations. Others can adapt this approach to their situation to maximize and sustain CDS implementation success.

  • J Med Internet Res 2020;22(10):e19676

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  Email Communication, Web-Based...

  Oct 29, 2020

  Associations Between Patient Health Outcomes and Secure Message Content Exchanged Between Patients and Clinicians: Retrospective Cohort Study

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  Authors List:

  • Dawn M Heisey-Grove  
  • Laura E McClelland  
  • Cheryl Rathert  
  • Alexander Tartaglia  
  • Kevin Jackson  
  • Jonathan P DeShazo  

  Abstract:

  Background: The number of electronic messages securely exchanged between clinic staff and patients has risen dramatically over the last decade. A variety of studies explored whether the volume of messages sent by patients was associated with outcomes. None of these studies, however, examined whether message content itself was associated with outcomes. Because secure messaging is a significant form of communication between patients and clinic staff, it is critical to evaluate the context of the communication to best understand its impact on patient health outcomes. Objective: To examine associations between patients’ and clinicians’ message content and changes in patients’ health outcomes. Methods: We applied a taxonomy developed specifically for secure messages to 14,394 patient- and clinic staff–generated messages derived from patient-initiated message threads. Our study population included 1602 patients, 50.94% (n=816) of whom initiated message threads. We conducted linear regression analyses to determine whether message codes were associated with changes in glycemic (A1C) levels in patients with diabetes and changes in systolic (SBP) and diastolic (DBP) blood pressure in patients with hypertension. Results: Patients who initiated threads had larger declines in A1Cs (P=.01) compared to patients who did not initiate threads. Clinic nonresponse was associated with decreased SBP (β=–.30; 95% CI –0.56 to –0.04), as were staffs’ action responses (β=–30; 95% CI –0.58 to –0.02). Increased DBP, SBP, and A1C levels were associated with patient-generated appreciation and praise messages and staff encouragement with effect sizes ranging from 0.51 (A1C) to 5.80 (SBP). We found improvements in SBP associated with patients’ complaints (β=–4.03; 95% CI –7.94 to –0.12). Deferred information sharing by clinic staff was associated with increased SBP (β=1.29; 95% CI 0.4 to 2.19). Conclusions: This is the first research to find associations between message content and patients’ health outcomes. Our findings indicate mixed associations between patient message content and patient outcomes. Further research is needed to understand the implications of this work; in the meantime, health care providers should be aware that their message content may influence patient health outcomes.

  • J Med Internet Res 2020;22(10):e19477

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  JMIR Theme Issue 2020: COVID-19...

  Oct 28, 2020

  Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and...

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  Authors List:

  • Jose Luis Izquierdo  
  • Julio Ancochea  
  • Savana COVID-19 Research Group
  • Joan B Soriano  

  Abstract:

  Background: Many factors involved in the onset and clinical course of the ongoing COVID-19 pandemic are still unknown. Although big data analytics and artificial intelligence are widely used in the realms of health and medicine, researchers are only beginning to use these tools to explore the clinical characteristics and predictive factors of patients with COVID-19. Objective: Our primary objectives are to describe the clinical characteristics and determine the factors that predict intensive care unit (ICU) admission of patients with COVID-19. Determining these factors using a well-defined population can increase our understanding of the real-world epidemiology of the disease. Methods: We used a combination of classic epidemiological methods, natural language processing (NLP), and machine learning (for predictive modeling) to analyze the electronic health records (EHRs) of patients with COVID-19. We explored the unstructured free text in the EHRs within the Servicio de Salud de Castilla-La Mancha (SESCAM) Health Care Network (Castilla-La Mancha, Spain) from the entire population with available EHRs (1,364,924 patients) from January 1 to March 29, 2020. We extracted related clinical information regarding diagnosis, progression, and outcome for all COVID-19 cases. Results: A total of 10,504 patients with a clinical or polymerase chain reaction–confirmed diagnosis of COVID-19 were identified; 5519 (52.5%) were male, with a mean age of 58.2 years (SD 19.7). Upon admission, the most common symptoms were cough, fever, and dyspnea; however, all three symptoms occurred in fewer than half of the cases. Overall, 6.1% (83/1353) of hospitalized patients required ICU admission. Using a machine-learning, data-driven algorithm, we identified that a combination of age, fever, and tachypnea was the most parsimonious predictor of ICU admission; patients younger than 56 years, without tachypnea, and temperature <39 degrees Celsius (or >39 ºC without respiratory crackles) were not admitted to the ICU. In contrast, patients with COVID-19 aged 40 to 79 years were likely to be admitted to the ICU if they had tachypnea and delayed their visit to the emergency department after being seen in primary care. Conclusions: Our results show that a combination of easily obtainable clinical variables (age, fever, and tachypnea with or without respiratory crackles) predicts whether patients with COVID-19 will require ICU admission.

  • J Med Internet Res 2020;22(10):e21801

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  Review

  Oct 28, 2020

  Disaster eHealth: Scoping Review

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  Authors List:

  • Samaneh Madanian  
  • Tony Norris  
  • Dave Parry  

  Abstract:

  Background: Although both disaster management and disaster medicine have been used for decades, their efficiency and effectiveness have been far from perfect. One reason could be the lack of systematic utilization of modern technologies, such as eHealth, in their operations. To address this issue, researchers’ efforts have led to the emergence of the disaster eHealth (DEH) field. DEH’s main objective is to systematically integrate eHealth technologies for health care purposes within the disaster management cycle (DMC). Objective: This study aims to identify, map, and define the scope of DEH as a new area of research at the intersection of disaster management, emergency medicine, and eHealth. Methods: An extensive scoping review using published materials was carried out in the areas of disaster management, disaster medicine, and eHealth to identify the scope of DEH. This review procedure was iterative and conducted in multiple scientific databases in 2 rounds, one using controlled indexed terms and the other using similar uncontrolled terms. In both rounds, the publications ranged from 1990 to 2016, and all the appropriate research studies discovered were considered, regardless of their research design, methodology, and quality. Information extracted from both rounds was thematically analyzed to define the DEH scope, and the results were evaluated by the field experts through a Delphi method. Results: In both rounds of the research, searching for eHealth applications within DMC yielded 404 relevant studies that showed eHealth applications in different disaster types and disaster phases. These applications varied with respect to the eHealth technology types, functions, services, and stakeholders. The results led to the identification of the scope of DEH, including eHealth technologies and their applications, services, and future developments that are applicable to disasters as well as to related stakeholders. Reference to the elements of the DEH scope indicates what, when, and how current eHealth technologies can be used in the DMC. Conclusions: Comprehensive data gathering from multiple databases offered a grounded method to define the DEH scope. This scope comprises concepts related to DEH and the boundaries that define it. The scope identifies the eHealth technologies relevant to DEH and the functions and services that can be provided by these technologies. In addition, the scope tells us which groups can use the provided services and functions and in which disaster types or phases. DEH approaches could potentially improve the response to health care demands before, during, and after disasters. DEH takes advantage of eHealth technologies to facilitate DMC tasks and activities, enhance their efficiency and effectiveness, and enhance health care delivery and provide more quality health care services to the wider population regardless of their geographical location or even disaster types and phases.

  • J Med Internet Res 2020;22(10):e18310

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