Subjects -> HEALTH AND SAFETY (Total: 1566 journals)
    - CIVIL DEFENSE (22 journals)
    - DRUG ABUSE AND ALCOHOLISM (86 journals)
    - HEALTH AND SAFETY (744 journals)
    - HEALTH FACILITIES AND ADMINISTRATION (390 journals)
    - OCCUPATIONAL HEALTH AND SAFETY (109 journals)
    - PHYSICAL FITNESS AND HYGIENE (133 journals)
    - WOMEN'S HEALTH (82 journals)

HEALTH FACILITIES AND ADMINISTRATION (390 journals)                  1 2 | Last

Showing 1 - 200 of 401 Journals sorted alphabetically
Academy of Health Care Management Journal     Full-text available via subscription   (Followers: 13)
ACI Open     Open Access  
Acta Bioquimica Clinica Latinoamericana     Open Access   (Followers: 1)
Administration and Policy in Mental Health and Mental Health Services Research     Partially Free   (Followers: 22)
Adnan Menderes Üniversitesi Sağlık Bilimleri Fakültesi Dergisi     Open Access   (Followers: 1)
Advanced Healthcare Materials     Hybrid Journal   (Followers: 17)
Advances in Dual Diagnosis     Hybrid Journal   (Followers: 48)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 26)
Advances in Medical Education and Practice     Open Access   (Followers: 34)
Advances in Mental Health and Intellectual Disabilities     Hybrid Journal   (Followers: 89)
Advances in Nursing Science     Hybrid Journal   (Followers: 43)
Advances in Simulation     Open Access   (Followers: 7)
African Journal of Primary Health Care & Family Medicine     Open Access   (Followers: 6)
AIDS and Behavior     Hybrid Journal   (Followers: 18)
American Journal of Hospice and Palliative Medicine     Hybrid Journal   (Followers: 48)
American Journal of Managed Care     Full-text available via subscription   (Followers: 13)
Analytical Methods     Full-text available via subscription   (Followers: 14)
Anthropologie et santé     Open Access   (Followers: 5)
Applied Clinical Informatics     Hybrid Journal   (Followers: 5)
Applied Health Economics and Health Policy     Full-text available via subscription   (Followers: 24)
Applied Research in Quality of Life     Hybrid Journal   (Followers: 13)
Archives of Public Health     Open Access   (Followers: 13)
Asian Journal of Health     Open Access   (Followers: 4)
Australasian Journal of Paramedicine     Open Access   (Followers: 7)
Australian and New Zealand Journal of Public Health     Hybrid Journal   (Followers: 17)
Australian Health Review     Hybrid Journal   (Followers: 7)
Australian Journal of Primary Health     Hybrid Journal  
Australian Journal of Rural Health     Hybrid Journal   (Followers: 18)
Autism     Hybrid Journal   (Followers: 349)
Avicenna     Open Access   (Followers: 3)
Balint Journal     Hybrid Journal   (Followers: 2)
Bereavement Care     Hybrid Journal   (Followers: 13)
BJR     Hybrid Journal   (Followers: 21)
BMC Medical Informatics and Decision Making     Open Access   (Followers: 25)
BMC Oral Health     Open Access   (Followers: 7)
BMJ Leader     Hybrid Journal  
BMJ Quality & Safety     Hybrid Journal   (Followers: 69)
BMJ Supportive & Palliative Care     Hybrid Journal   (Followers: 50)
British Journal of Healthcare Assistants     Full-text available via subscription   (Followers: 33)
British Journal of Healthcare Management     Full-text available via subscription   (Followers: 19)
British Journal of Hospital Medicine     Full-text available via subscription   (Followers: 18)
British Journal of Nursing     Full-text available via subscription   (Followers: 294)
British Journal of School Nursing     Full-text available via subscription   (Followers: 14)
Bruce R Hopkins' Nonprofit Counsel     Hybrid Journal   (Followers: 2)
Building Better Healthcare     Full-text available via subscription   (Followers: 1)
Canadian Nurse     Full-text available via subscription   (Followers: 8)
Cardiac Electrophysiology Clinics     Full-text available via subscription   (Followers: 1)
Children and Schools     Hybrid Journal   (Followers: 8)
Chinese Medical Record English Edition     Hybrid Journal  
CIN : Computers Informatics Nursing     Hybrid Journal   (Followers: 11)
Clinical Audit     Open Access   (Followers: 4)
Clinics and Practice     Open Access  
Cognition, Technology & Work     Hybrid Journal   (Followers: 14)
Communication & Medicine     Hybrid Journal   (Followers: 5)
Community Based Medical Journal     Open Access  
Conflict and Health     Open Access   (Followers: 8)
Contemporary Nurse : A Journal for the Australian Nursing Profession     Hybrid Journal   (Followers: 7)
Critical Public Health     Hybrid Journal   (Followers: 26)
Culture, Health & Sexuality: An International Journal for Research, Intervention and Care     Hybrid Journal   (Followers: 17)
Current Opinion in Supportive and Palliative Care     Hybrid Journal   (Followers: 28)
Das Gesundheitswesen     Hybrid Journal   (Followers: 10)
Death Studies     Hybrid Journal   (Followers: 22)
Dental Nursing     Full-text available via subscription   (Followers: 3)
Disaster Health     Hybrid Journal   (Followers: 1)
DoctorConsult - The Journal. Wissen für Klinik und Praxis     Full-text available via subscription  
Droit, Déontologie & Soin     Full-text available via subscription   (Followers: 3)
E-Health Telecommunication Systems and Networks     Open Access   (Followers: 2)
East and Central African Journal of Surgery     Open Access  
Éducation thérapeutique du patient     Full-text available via subscription   (Followers: 1)
eGEMs     Open Access  
Emergency Radiology     Hybrid Journal   (Followers: 10)
Enfermería Clínica     Full-text available via subscription   (Followers: 3)
Epidemiologic Methods     Hybrid Journal   (Followers: 4)
Ergonomics     Hybrid Journal   (Followers: 24)
Escola Anna Nery     Open Access   (Followers: 1)
Ethnicity & Health     Hybrid Journal   (Followers: 14)
European Journal of Public Health     Hybrid Journal   (Followers: 27)
European Journal of Work and Organizational Psychology     Hybrid Journal   (Followers: 35)
European Research in Telemedicine / La Recherche Européenne en Télémédecine     Full-text available via subscription   (Followers: 2)
Evaluation & the Health Professions     Hybrid Journal   (Followers: 10)
Evidence-Based Nursing     Hybrid Journal   (Followers: 74)
Evolution, Medicine, and Public Health     Open Access   (Followers: 12)
Expert Opinion on Therapeutic Patents     Hybrid Journal   (Followers: 12)
Families, Systems, & Health     Full-text available via subscription   (Followers: 9)
Family Practice Management     Full-text available via subscription   (Followers: 5)
Focus on Health Professional Education : A Multi-disciplinary Journal     Full-text available via subscription   (Followers: 7)
Frontiers in Public Health Services and Systems Research     Open Access   (Followers: 5)
Future Hospital Journal     Full-text available via subscription   (Followers: 2)
Gastrointestinal Nursing     Full-text available via subscription   (Followers: 5)
Geron     Full-text available via subscription  
Global & Regional Health Technology Assessment     Open Access   (Followers: 1)
Global Health Action     Open Access   (Followers: 12)
Global Health Management Journal (GHMJ)     Open Access   (Followers: 1)
Global Health Research and Policy     Open Access   (Followers: 4)
Global Journal of Hospital Administration     Open Access   (Followers: 1)
Global Public Health: An International Journal for Research, Policy and Practice     Hybrid Journal   (Followers: 21)
Globalization and Health     Open Access   (Followers: 9)
Handbook of Practice Management     Hybrid Journal   (Followers: 2)
Health     Open Access   (Followers: 5)
Health & Social Care In the Community     Hybrid Journal   (Followers: 54)
Health : An Interdisciplinary Journal for the Social Study of Health, Illness and Medicine     Hybrid Journal   (Followers: 16)
Health and Interprofessional Practice     Open Access   (Followers: 6)
Health and Technology     Hybrid Journal   (Followers: 4)
Health Care Analysis     Hybrid Journal   (Followers: 17)
Health Care Management Review     Hybrid Journal   (Followers: 16)
Health Economics     Hybrid Journal   (Followers: 59)
Health Expectations     Open Access   (Followers: 16)
Health Facilities Management     Free   (Followers: 10)
Health Informatics Journal     Hybrid Journal   (Followers: 28)
Health Information : Jurnal Penelitian     Open Access   (Followers: 6)
Health Information Science and Systems     Open Access   (Followers: 4)
Health Policy and Management     Open Access   (Followers: 7)
Health Policy and Planning     Hybrid Journal   (Followers: 27)
Health Professions Education     Open Access   (Followers: 3)
Health Promotion International     Hybrid Journal   (Followers: 28)
Health Promotion Practice     Hybrid Journal   (Followers: 18)
Health Psychology     Full-text available via subscription   (Followers: 62)
Health Psychology Review     Hybrid Journal   (Followers: 46)
Health Reform Observer : Observatoire des Réformes de Santé     Open Access   (Followers: 2)
Health Research Policy and Systems     Open Access   (Followers: 16)
Health Science Journal of Indonesia     Open Access   (Followers: 2)
Health Services Research and Managerial Epidemiology     Open Access   (Followers: 3)
Health, Risk & Society     Hybrid Journal   (Followers: 14)
Healthcare : The Journal of Delivery Science and Innovation     Full-text available via subscription   (Followers: 1)
Healthcare Financial Management     Full-text available via subscription   (Followers: 4)
Healthcare in Low-resource Settings     Open Access   (Followers: 1)
Healthcare Management Forum     Hybrid Journal   (Followers: 8)
Healthcare Policy / Politiques de Santé     Full-text available via subscription   (Followers: 5)
Healthcare Quarterly     Full-text available via subscription   (Followers: 10)
Healthcare Risk Management     Full-text available via subscription   (Followers: 5)
HealthcarePapers     Full-text available via subscription   (Followers: 2)
Hispanic Health Care International     Full-text available via subscription  
História, Ciências, Saúde - Manguinhos     Open Access   (Followers: 2)
Hong Kong Journal of Social Work, The     Hybrid Journal   (Followers: 3)
Hospital     Open Access   (Followers: 3)
Hospital a Domicilio     Open Access  
Hospital Infection Control & Prevention     Full-text available via subscription   (Followers: 15)
Hospital Medicine Clinics     Full-text available via subscription   (Followers: 2)
Hospital Peer Review     Full-text available via subscription   (Followers: 1)
Hospital Pharmacy     Partially Free   (Followers: 18)
Hospital Practice     Hybrid Journal   (Followers: 2)
Hospital Practices and Research     Open Access  
Housing, Care and Support     Hybrid Journal   (Followers: 9)
Human Factors : The Journal of the Human Factors and Ergonomics Society     Full-text available via subscription   (Followers: 39)
Human Resources for Health     Open Access   (Followers: 12)
ICU Director     Hybrid Journal  
Ids Practice Papers     Hybrid Journal  
IEEE Pulse     Hybrid Journal   (Followers: 5)
IISE Transactions on Healthcare Systems Engineering     Hybrid Journal   (Followers: 2)
Independent Nurse     Full-text available via subscription   (Followers: 3)
Index de Enfermeria     Open Access   (Followers: 7)
Indian Journal of Public Health     Open Access   (Followers: 1)
Informatics for Health and Social Care     Hybrid Journal   (Followers: 10)
Innovation and Entrepreneurship in Health     Open Access   (Followers: 1)
INQUIRY : The Journal of Health Care Organization, Provision, and Financing     Open Access   (Followers: 1)
Interface - Comunicação, Saúde, Educação     Open Access   (Followers: 1)
International Archives of Health Sciences     Open Access  
International Journal for Equity in Health     Open Access   (Followers: 9)
International Journal for Quality in Health Care     Hybrid Journal   (Followers: 41)
International Journal of Care Coordination     Hybrid Journal   (Followers: 7)
International Journal of Computers in Healthcare     Hybrid Journal   (Followers: 3)
International Journal of Electronic Healthcare     Hybrid Journal   (Followers: 2)
International Journal of Environmental Research and Public Health     Open Access   (Followers: 27)
International Journal of Health Administration and Education Congress (Sanitas Magisterium)     Open Access  
International Journal of Health Care Quality Assurance     Hybrid Journal   (Followers: 15)
International Journal of Health Economics and Management     Hybrid Journal   (Followers: 13)
International Journal of Health Governance     Hybrid Journal   (Followers: 27)
International Journal of Health Planning and Management     Hybrid Journal   (Followers: 6)
International Journal of Health Sciences Education     Open Access   (Followers: 2)
International Journal of Health Services Research and Policy     Open Access   (Followers: 1)
International Journal of Health System and Disaster Management     Open Access   (Followers: 3)
International Journal of Healthcare     Open Access   (Followers: 1)
International Journal of Healthcare Technology and Management     Hybrid Journal   (Followers: 7)
International Journal of Hospital Research     Open Access  
International Journal of Human Factors and Ergonomics     Hybrid Journal   (Followers: 20)
International Journal of Human Rights in Healthcare     Hybrid Journal   (Followers: 5)
International Journal of Medicine and Public Health     Open Access   (Followers: 6)
International Journal of Migration, Health and Social Care     Hybrid Journal   (Followers: 12)
International Journal of Occupational and Environmental Medicine, The     Open Access   (Followers: 15)
International Journal of Palliative Nursing     Full-text available via subscription   (Followers: 32)
International Journal of Positive Behavioural Support     Full-text available via subscription   (Followers: 38)
International Journal of Prisoner Health     Hybrid Journal   (Followers: 14)
International Journal of Privacy and Health Information Management     Full-text available via subscription   (Followers: 3)
International Journal of Public and Private Healthcare Management and Economics     Full-text available via subscription   (Followers: 4)
International Journal of Qualitative Studies on Health and Well-Being     Open Access   (Followers: 22)
International Journal of Reliable and Quality E-Healthcare     Full-text available via subscription   (Followers: 1)
International Journal of Research in Nursing     Open Access   (Followers: 12)
International Journal of Technology Assessment in Health Care     Hybrid Journal   (Followers: 16)
International Journal of Telemedicine and Clinical Practices     Hybrid Journal   (Followers: 5)
International Journal of Telework and Telecommuting Technologies     Full-text available via subscription  
International Journal of Therapy and Rehabilitation     Full-text available via subscription   (Followers: 42)
International Journal of User-Driven Healthcare     Full-text available via subscription   (Followers: 1)
International Journal on Disability and Human Development     Hybrid Journal   (Followers: 23)
Irish Journal of Paramedicine     Open Access   (Followers: 3)
JAAPA     Hybrid Journal   (Followers: 3)
Jaffna Medical Journal     Open Access  
Joint Commission Journal on Quality and Patient Safety     Hybrid Journal   (Followers: 41)
Journal for Healthcare Quality     Hybrid Journal   (Followers: 28)
Journal of Advanced Nursing     Hybrid Journal   (Followers: 250)
Journal of Advances in Medical Education & Professionalism     Open Access   (Followers: 10)

        1 2 | Last

Similar Journals
Journal Cover
Health Informatics Journal
Journal Prestige (SJR): 0.612
Citation Impact (citeScore): 2
Number of Followers: 28  
 
Hybrid Journal Hybrid journal   * Containing 1 Open Access Open Access article(s) in this issue *
ISSN (Print) 1460-4582 - ISSN (Online) 1741-2811
Published by Sage Publications Homepage  [1135 journals]
  • Physician experiences of screen-level features in a prominent electronic
           health record: Design recommendations from a qualitative study
    • Authors: Saif Khairat, Cameron Coleman, Randall Teal, Salma Rezk, Victoria Rand, Thomas Bice, Shannon S Carson
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      The goal of this qualitative study was to assess physicians’ perceptions around features of key screens within a prominent commercial EHR, and to solicit end-user recommendations for improved retrieval of high-priority clinical information. We conducted a qualitative, descriptive study of 25 physicians in a medical ICU setting. at a tertiary academic medical center. An in-depth, semi-structured interview guide was developed to elicit physician perceptions on information retrieval as well as favorable and unfavorable features of specific EHR screens. Transcripts were independently coded in a qualitative software management tool by at least two trained coders using a common code book. We successfully obtained vendor permission to map physicians perception’s on full Epic© screenshots. Among the 25 physician participants (13 female; 5 attending physicians, 9 fellows, 11 residents), the majority of participants reported experiencing challenges finding clinical information in the EHR. We present the most favorable and unfavorable screen-level features for four central EHR screens: Flowsheet, Notes/Chart Review, Results Review, and Vital Signs. We also compiled participants’ recommendations for a comprehensive EHR dashboard screen to better support clinical workflow and information retrieval in the medical ICU through User-Centered Design. ICU physicians demonstrated a mix of positive and negative attitudes toward specific screen-level features in a major vendor-based EHR system. Physician perceptions of information overload emerged as a theme across multiple EHR screens. Our findings underscore the importance of qualitative research and end-user feedback in EHR software design and interface optimization at both the vendor and institutional level.
      Citation: Health Informatics Journal
      PubDate: 2021-03-11T07:12:35Z
      DOI: 10.1177/1460458221997914
      Issue No: Vol. 27, No. 1 (2021)
       
  • Home telemonitoring for chronic disease management: Perceptions of users
           and factors influencing adoption
    • Authors: Jane Li, Marlien Varnfield, Rajiv Jayasena, Branko Celler
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Home telemonitoring has been used as a solution to support the care of individuals living with chronic disease. While effectiveness of telemonitoring have been widely studied, more research is needed to understand the perceptions among patients and clinicians in incorporating telemonitoring into their daily routine and practices. This paper presents an investigation of patients’ and clinicians’ experiences in a care augmenting telemonitoring service, their perceived impact delivered through the service, and clinicians’ perceptions on how the service was introduced in their organizations. This work was embedded in a large multi-site trial of home telemonitoring using a mixed method approach for evaluation. Interviews with clinicians involved in the study were conducted at multiple time points during the trial. Questionnaires were administered to clinicians and patients at the end of the trial. Results showed that both patients and clinicians recognized the benefits of patient empowerment through telemonitoring, and patient-clinician interactions. Results identified the needs of a dedicated telemonitoring clinical care coordinator role, guidelines that translate telemonitoring services into clinical pathways and engagement of different healthcare providers, especially general practitioners, to support the integration of telemonitoring into chronic disease management programs and long-term organizational strategic plans.
      Citation: Health Informatics Journal
      PubDate: 2021-03-09T06:43:56Z
      DOI: 10.1177/1460458221997893
      Issue No: Vol. 27, No. 1 (2021)
       
  • Effect of physician prescribed information on hospital readmission and
           death after discharge among patients with health failure: A randomized
           controlled trial
    • Authors: Faranak Kazemi Majd, Vahideh Zarea Gavgani, Ali Golmohammadi, Ali Jafari-Khounigh
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      In order to understand if a physician prescribed medical information changes, the number of hospital readmission, and death among the heart failure patients. A 12-month randomized controlled trial was conducted (December 2013–2014). Totally, 120 patients were randomly allocated into two groups of intervention (n = 60) and control (n = 60). Accordingly, the control group was given the routine oral information by the nurse or physician, and the intervention group received the Information Prescription (IP) prescribed by the physician as well as the routine oral information. The data was collected via telephone interviews with the follow-up intervals of 6 and 12 months, and also for 1 year after the discharge. The patients with the median age of (IQR) 69.5 years old (19.8) death upon adjusting a Cox survival model, [RR = 0.67, 95%CI: 0.46–0.97]. Few patients died during 1 year in the intervention group compared to the controls (7 vs 15) [RR = 0.47, 95%CI: 0.20–1.06]. During a period of 6-month follow-up there was not statistically significant on death and readmission between two groups. Physician prescribed information was clinically and statistically effective on the reduction of death and hospital readmission rates among the HF patients in long term follow-up.
      Citation: Health Informatics Journal
      PubDate: 2021-03-04T06:27:22Z
      DOI: 10.1177/1460458221996409
      Issue No: Vol. 27, No. 1 (2021)
       
  • Corrigendum
    • Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.

      Citation: Health Informatics Journal
      PubDate: 2021-03-04T05:35:17Z
      DOI: 10.1177/1460458217726871
      Issue No: Vol. 27, No. 1 (2021)
       
  • A qualitative study of clinician perceptions regarding the potential role
           for digital health interventions for the management of COPD
    • Authors: Patrick Slevin, Threase Kessie, John Cullen, Marcus W. Butler, Seamas C. Donnelly, Brian Caulfield
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Effective self-management of chronic obstructive pulmonary disease (COPD) can lead to increased patient control and reduced health care costs. However, both patients and healthcare professionals encounter significant challenges. Digital health interventions, such as smart oximeters and COPD self-management applications, promise to enhance the management of COPD, yet, there is little evidence to support their use and user-experience issues are still common. Understanding the needs of healthcare professionals is central for increasing adoption and engagement with digital health interventions but little is known about their perceptions of digital health interventions in COPD. This paper explored the perceptions of healthcare professionals regarding the potential role for DHI in the management of COPD. Snowball sampling was used to recruit the participants (n = 32). Each participant underwent a semi-structured interview. Using NVivo 12 software, thematic analysis was completed. Healthcare professionals perceive digital health interventions providing several potential benefits to the management of COPD including the capture of patient status indicators during the interappointment period, providing new patient data to support the consultation process and perceived digital health interventions as a potential means to improve patient engagement. The findings offer new insights regarding potential future use-cases for digital health interventions in COPD, which can help ease user-experience issues as they align with the needs of healthcare professionals.
      Citation: Health Informatics Journal
      PubDate: 2021-03-03T05:36:12Z
      DOI: 10.1177/1460458221994888
      Issue No: Vol. 27, No. 1 (2021)
       
  • Conversion to an electronic missing medication request system at an
           academic medical center
    • Authors: Michael J Peters, Chris K Finch, Lauchland Roberts, Angela Covington, Joseph Krushinski
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Missing medications can negatively contribute to the financial and operational workflows of pharmacy departments and add medication safety challenges. The missing medication request (MMR) system at the study institution converted to entirely electronic in June 2018 from a hybrid electronic system. This study evaluated 4-week periods pre- and post-conversion. The objective of this study was to evaluate the impact of conversion to an electronic MMR system on the quantity of requests received at an academic medical center. The average daily number of MMR’s decreased from the pre-conversion group to the post-conversion group (1.77 (±0.16) vs 1.48 (±0.17), p 
      Citation: Health Informatics Journal
      PubDate: 2021-02-24T12:18:24Z
      DOI: 10.1177/1460458221994862
      Issue No: Vol. 27, No. 1 (2021)
       
  • Potentially modifiable risk factors for 30-day unplanned hospital
           readmission preventive intervention—A data mining and statistical
           analysis
    • Authors: Peng Zhao, Illhoi Yoo
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Unplanned hospital readmissions have a high prevalence and substantial healthcare costs. Preventive intervention during hospitalization holds the potential for reducing readmission risk. However, it is challenging to develop individualized interventions during hospitalization because the causes of readmissions have not been clearly known and because patients are heterogeneous. This work aimed to identify potentially modifiable risk factors of readmission to help clinicians better plan and prioritize interventions for different patient subgroups during hospitalization. We performed the analysis of associations between the changes of potentially modifiable risk factors and the change of readmission status with association rule mining and statistical methods. Twenty-nine risk factors were identified from the association rules, and twenty-five of them were potentially modifiable. The association rules with potentially modifiable risk factors can be recommended to different patient subgroups to support the development of customized readmission preventive interventions.
      Citation: Health Informatics Journal
      PubDate: 2021-02-24T12:15:29Z
      DOI: 10.1177/1460458221995231
      Issue No: Vol. 27, No. 1 (2021)
       
  • Exploring the acceptability of a digital mental health platform
           incorporating a virtual coach: The good, the bad, and the opportunities
    • Authors: Anthony Venning, Madeleine CE Herd, Tassia K Oswald, Sabran Razmi, Fiona Glover, Tim Hawke, Victoria Quartermain, Paula Redpath
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Digital Mental Health Platforms offer feasible options to increase access to mental health support. This study aimed to examine the acceptability of a Low Intensity Cognitive Behaviour Therapy Digital Mental Health Platform, containing a Virtual Coach, with University Students (n = 16) and Mental Health Professionals (n = 5). Semi-structured interviews, exploratory focus groups, and inductive thematic analysis were conducted. Four overarching themes were identified, with potential users and professionals highlighting positive aspects, elements to be improved, and ambivalent feelings towards the platform overall. However, participants predominately expressed negative experiences indicating that the Virtual Coach was unrelatable and hard to engage with. While Virtual Coaches and similar Digital Mental Health Platforms have the potential to overcome barriers for those attempting to access mental health services, their effectiveness may be limited if the people who need them are not drawn to and then consistently engaged with them. Based on the feedback attained for this specific Digital Mental Health Platform, recommendations are provided for future developers aiming to create similar platforms, to assist in their uptake and ensure ongoing user engagement.
      Citation: Health Informatics Journal
      PubDate: 2021-02-19T05:54:39Z
      DOI: 10.1177/1460458221994873
      Issue No: Vol. 27, No. 1 (2021)
       
  • Applying machine learning on home videos for remote autism diagnosis:
           Further study and analysis
    • Authors: Mohamed A. Nabil, Ansam Akram, Karma M Fathalla
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Autism Spectrum Disorder (Autism) is a developmental disorder that impedes the social and communication capabilities of a person through out his life. Early detection of autism is critical in contributing to better prognosis. In this study, the use of home videos to provide accessible diagnosis is investigated. A machine learning approach is adopted to detect autism from home videos. Feature selection and state-of-the-art classification methods are applied to provide a sound diagnosis based on home video ratings obtained from non-clinicians feedback. Our models results indicate that home videos can effectively detect autistic group with True Positive Rate reaching 94.05% using Support Vector Machines and backwards feature selection. In this study, human-interpretable models are presented to elucidate the reasoning behind the classification process and its subsequent decision. In addition, the prime features that need to be monitored for early autism detection are revealed.
      Citation: Health Informatics Journal
      PubDate: 2021-02-15T04:51:29Z
      DOI: 10.1177/1460458221991882
      Issue No: Vol. 27, No. 1 (2021)
       
  • Feature selection with ensemble learning for prostate cancer diagnosis
           from microarray gene expression
    • Authors: Abdu Gumaei, Rachid Sammouda, Mabrook Al-Rakhami, Hussain AlSalman, Ali El-Zaart
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Cancer diagnosis using machine learning algorithms is one of the main topics of research in computer-based medical science. Prostate cancer is considered one of the reasons that are leading to deaths worldwide. Data analysis of gene expression from microarray using machine learning and soft computing algorithms is a useful tool for detecting prostate cancer in medical diagnosis. Even though traditional machine learning methods have been successfully applied for detecting prostate cancer, the large number of attributes with a small sample size of microarray data is still a challenge that limits their ability for effective medical diagnosis. Selecting a subset of relevant features from all features and choosing an appropriate machine learning method can exploit the information of microarray data to improve the accuracy rate of detection. In this paper, we propose to use a correlation feature selection (CFS) method with random committee (RC) ensemble learning to detect prostate cancer from microarray data of gene expression. A set of experiments are conducted on a public benchmark dataset using 10-fold cross-validation technique to evaluate the proposed approach. The experimental results revealed that the proposed approach attains 95.098% accuracy, which is higher than related work methods on the same dataset.
      Citation: Health Informatics Journal
      PubDate: 2021-02-11T11:59:30Z
      DOI: 10.1177/1460458221989402
      Issue No: Vol. 27, No. 1 (2021)
       
  • Web-based expert system with quick response code for beta-thalassemia
           management
    • Authors: Haneen R. Banjar, Galila F. Zaher, Hanadi S. Almutiry, Asma S. A Alshamarni, Ghaidaa I. Almouhana, Hatem M. Alahwal, Salem Bahashwan, Ahmed S. Barefah, Salwa A. Alnajjar, Hajar M. Alharbi
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      β-thalassemia is an inherited blood disorder in which the body cannot produce hemoglobin normally. Since patients with this condition receive blood transfusions regularly, iron builds up primarily in organs such as the heart, liver and endocrine glands. Accumulation of iron in the organs necessitates chelation therapy. These patients must visit the hospital frequently to assess and follow up on their health condition. Physician intervention is required after each regular assessment to adjust the treatment. Lifelong healthcare support using a web-based expert system with a quick response code is designed for β-thalassemia management in order to deliver benefits to patients, physicians, and other healthcare providers. The aim of this study is to implement a web-based expert system for β-thalassemia management in order to provide treatment recommendations and support the lifelong healthcare of patients. The system provides patient-related details, such as medical history, medicines, and appointments, in real-time. It has been also tested in real-life cases and shown to enhance β-thalassemia management.
      Citation: Health Informatics Journal
      PubDate: 2021-02-11T11:53:28Z
      DOI: 10.1177/1460458221989397
      Issue No: Vol. 27, No. 1 (2021)
       
  • Incorporating patient concerns into design requirements for IoMT-based
           systems: The fall detection case study
    • Authors: Mara Nikolaidou, Christos Kotronis, Ioannis Routis, Elena Politi, George Dimitrakopoulos, Dimosthenis Anagnostopoulos, Hamza Djelouat, Abbes Amira, Faycal Bensaali
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Internet of Medical Things (IoMT) systems are envisioned to provide high-quality healthcare services to patients in the comfort of their home, utilizing cutting-edge Internet of Things (IoT) technologies and medical sensors. Patient comfort and willingness to participate in such efforts is a prominent factor for their adoption. As IoT technology has provided solutions for all technical issues, patient concerns are those that seem to restrict their wider adoption. To enhance patient awareness of the system properties and enhance their willingness to adopt IoMT solutions, this paper presents a novel methodology to integrate patient concerns in the design requirements of such systems. It comprises a number of straightforward steps that an IoMT designer can follow, starting from identifying patient concerns, incorporating them in system design requirements as criticalities, proceeding to system implementation and testing, and finally, verifying that it fulfills the concerns of the patients. To showcase the effectiveness of the proposed methodology, the paper applies it in the design and implementation of a fall detection system for elderly patients remotely monitored in their homes.
      Citation: Health Informatics Journal
      PubDate: 2021-02-11T11:47:28Z
      DOI: 10.1177/1460458220982640
      Issue No: Vol. 27, No. 1 (2021)
       
  • Teaching university students co-creation and living lab methodologies
           through experiential learning activities and preparing them for RRI
    • Authors: Evdokimos I Konstantinidis, Despoina Petsani, Panagiotis D Bamidis
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      During the last decade, the living lab and co-creation concepts have started being blended with the Responsible Research and Innovation approach, aiming to evaluate potential societal anticipations toward fostering an inclusive RRI behavior. Teaching co-creation concept and living lab methodologies to university students has started been considered as valuable for future researchers along with the demand of companies and public sectors which turn toward user-center techniques for inspiration to develop innovative and services. To this end, the scientific publications presenting work on teaching co-creation and living lab methodologies are not so many while there are no published research studies on experiential learning activities for teaching co-creation and living lab approaches to university students. This study presents a course based on living labs and co-creation methodologies through experiential learning activities, consisted of four different lectures and an open event. The study involves stakeholders from the academia, the citizens, and the public sector. The results show that lectures with the participation of end-users were the most enjoyable. Furthermore, students thought that they learned the most when they first met the end-users. This lecture was perceived as a successful way to gain methodical knowledge for user-centered design and software development.
      Citation: Health Informatics Journal
      PubDate: 2021-02-04T06:52:40Z
      DOI: 10.1177/1460458221991204
      Issue No: Vol. 27, No. 1 (2021)
       
  • Building a specialized lexicon for breast cancer clinical trial subject
           eligibility analysis
    • Authors: Euisung Jung, Hemant Jain, Atish P Sinha, Carmelo Gaudioso
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      A natural language processing (NLP) application requires sophisticated lexical resources to support its processing goals. Different solutions, such as dictionary lookup and MetaMap, have been proposed in the healthcare informatics literature to identify disease terms with more than one word (multi-gram disease named entities). Although a lot of work has been done in the identification of protein- and gene-named entities in the biomedical field, not much research has been done on the recognition and resolution of terminologies in the clinical trial subject eligibility analysis. In this study, we develop a specialized lexicon for improving NLP and text mining analysis in the breast cancer domain, and evaluate it by comparing it with the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT). We use a hybrid methodology, which combines the knowledge of domain experts, terms from multiple online dictionaries, and the mining of text from sample clinical trials. Use of our methodology introduces 4243 unique lexicon items, which increase bigram entity match by 38.6% and trigram entity match by 41%. Our lexicon, which adds a significant number of new terms, is very useful for matching patients to clinical trials automatically based on eligibility matching. Beyond clinical trial matching, the specialized lexicon developed in this study could serve as a foundation for future healthcare text mining applications.
      Citation: Health Informatics Journal
      PubDate: 2021-02-04T06:49:20Z
      DOI: 10.1177/1460458221989392
      Issue No: Vol. 27, No. 1 (2021)
       
  • Physician perceptions of documentation methods in electronic health
           records
    • Authors: Nicole E McAmis, Andrew S Dunn, Richard S Feinn, Aaron W Bernard, Margaret J Trost
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      This study sought to determine physician, specialty and practice factors influencing choice of method for electronic health record (EHR) documentation: direct typing (DT), electronic transcription (ET), human transcription (HT), and scribes. A survey assessing physician documentation practices was developed and distributed online. The primary outcome was the proportion of physicians using each method. Secondary outcomes were provider-rated accuracy, efficiency, and ease of navigation on a 1-5 Likert scale. Means were compared using linear mixed models with Bonferroni adjustment. The 818 respondents were mostly outpatient (46%) adult (79%) physicians, practiced for a mean 15.8 years, and used DT for EHR documentation (72%). Emergency physicians were more likely to use scribes (p 
      Citation: Health Informatics Journal
      PubDate: 2021-02-04T06:45:38Z
      DOI: 10.1177/1460458221989399
      Issue No: Vol. 27, No. 1 (2021)
       
  • Assessment of an evidence-based laryngeal cancer fact sheet: A mixed
           methods study
    • Authors: Joe Jabbour, Heather L Shepherd, Thomas Beddow, Puma Sundaresan, Chris Milross, Carsten E Palme, Jonathan R Clark, Haryana M Dhillon
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      To evaluate perceptions of a laryngeal cancer fact sheet amongst people with direct experience of the disease and its treatment. A mixed methods study (questionnaire and interview) evaluating the information resource was conducted across two institutions. In total 20 participants responded to the questionnaire. Overall participants reported the information resource was detailed and understandable. Insufficient information was provided on: impact on family in eight participants (40%); impact on work in six (33%); and, second opinions and long-term side effects in five (25%). The majority (67%) wanted a large amount of information with the preferred source being one-on-one meetings with their doctor. The thematic analysis identified three main themes: preferences for information, self-management; and, information sources. People with direct experience of laryngeal cancer and its treatments reported the information resource was comprehensive and clear. There were some gaps in the information provided, particularly related to survivorship issues.
      Citation: Health Informatics Journal
      PubDate: 2021-02-01T05:21:05Z
      DOI: 10.1177/1460458221989403
      Issue No: Vol. 27, No. 1 (2021)
       
  • Screening of apathetic elderly adults using kinematic information in gait
           and sit-to-stand/stand-to-sit movements measured with Doppler radar
    • Authors: Kenshi Saho, Kouki Sugano, Kazuki Uemura, Michito Matsumoto
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      This paper presents a Doppler radar apathy-screening technique applied to elderly people based on their basic daily activities of walking and movements of sit-to-stand and stand-to-sit (STS). Our Doppler radar system remotely measured the kinematic parameters of the movements of 78 community-dwelling elderly adults (27 apathetic participants and 51 non-apathetic ones). Subsequently, logistic regression models using the measured kinematic parameters of gait and sit-to-stand/stand-to-sit movements were constructed for screening. The experimental results verified that, although the model using gait parameters could screen an apathetic group with a sensitivity of 85.2% and a specificity of 58.8%, the model using the STS parameters achieved better screening accuracies with a sensitivity of 88.9% and a specificity of 76.5%. These results reveal that the kinematic information of STS movements is significantly more effective at detecting apathy than is the gait information, which is otherwise regarded to be effective in conventional epidemiological studies.
      Citation: Health Informatics Journal
      PubDate: 2021-01-29T08:49:53Z
      DOI: 10.1177/1460458221990051
      Issue No: Vol. 27, No. 1 (2021)
       
  • Prediction of cancer incidence rates for the European continent using
           machine learning models
    • Authors: Boran Sekeroglu, Kubra Tuncal
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Cancer is one of the most important and common public health problems on Earth that can occur in many different types. Treatments and precautions are aimed at minimizing the deaths caused by cancer; however, incidence rates continue to rise. Thus, it is important to analyze and estimate incidence rates to support the determination of more effective precautions. In this research, 2018 Cancer Datasheet of World Health Organization (WHO), is used and all countries on the European Continent are considered to analyze and predict the incidence rates until 2020, for Lung cancer, Breast cancer, Colorectal cancer, Prostate cancer and All types of cancer, which have highest incidence and mortality rates. Each cancer type is trained by six machine learning models namely, Linear Regression, Support Vector Regression, Decision Tree, Long-Short Term Memory neural network, Backpropagation neural network, and Radial Basis Function neural network according to gender types separately. Linear regression and support vector regression outperformed the other models with the [math] scores 0.99 and 0.98, respectively, in initial experiments, and then used for prediction of incidence rates of the considered cancer types. The ML models estimated that the maximum rise of incidence rates would be in colorectal cancer for females by 6%.
      Citation: Health Informatics Journal
      PubDate: 2021-01-28T11:54:20Z
      DOI: 10.1177/1460458220983878
      Issue No: Vol. 27, No. 1 (2021)
       
  • The challenge of predicting blood glucose concentration changes in
           patients with type I diabetes
    • Authors: Neil C Borle, Edmond A Ryan, Russell Greiner
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Patients with Type I Diabetes (T1D) must take insulin injections to prevent the serious long term effects of hyperglycemia. They must also be careful not to inject too much insulin because this could induce (potentially fatal) hypoglycemia. Patients therefore follow a “regimen” that determines how much insulin to inject at each time, based on various measurements. We can produce an effective regimen if we can accurately predict a patient’s future blood glucose (BG) values from his/her current features. This study explores the challenges of predicting future BG by applying a number of machine learning algorithms, as well as various data preprocessing variations (corresponding to 312 [learner, preprocessed-dataset] combinations), to a new T1D dataset that contains 29,601 entries from 47 different patients. Our most accurate predictor, a weighted ensemble of two Gaussian Process Regression models, achieved a (cross-validation) [math] loss of 2.7 mmol/L (48.65 mg/dl). This result was unexpectedly poor given that one can obtain an [math] of 2.9 mmol/L (52.43 mg/dl) using the naive approach of simply predicting the patient’s average BG. These results suggest that the diabetes diary data that is typically collected may be insufficient to produce accurate BG prediction models; additional data may be necessary to build accurate BG prediction models over hours.
      Citation: Health Informatics Journal
      PubDate: 2021-01-28T07:50:35Z
      DOI: 10.1177/1460458220977584
      Issue No: Vol. 27, No. 1 (2021)
       
  • Living lab on sharing and circular economy: The case of Turin
    • Authors: Federico Cuomo, Nadia Lambiase, Antonio Castagna
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Cities with their innovative capacity are key places to address critical climate, environmental and health challenges. Urban experimentations, such as Living Labs, can represent a starting point to reintroduce resources into the production cycle and reduce environmental impacts, embracing the paradigm of the circular economy (CE). According to recent studies, Living Labs at a city scale could generate significant environmental benefits, improvements in quality of life and positive impacts on citizens’ health.1 This paper aims at presenting the case of the Torino Living Lab on Sharing and Circular Economy (LLSC) to point out possible future scenarios of urban sustainable policies. The case study is analysed in five sections: (1) the description of the new permanent laboratory proposed by the City of Turin; (2) the past experiences of Living Labs in Turin; (3) the birth of LLSC and the involvement strategy; (4) the introduction of the eight admitted experimentations. In the light of the results collected, the last paragraph (5) came up with the Strengths, Weaknesses, Opportunities, Treaths (SWOT) analysis in the LLSC. Eventually, it deals with the research question by offering a common ground for global and local policies focused on sustainability and CE.
      Citation: Health Informatics Journal
      PubDate: 2021-01-28T07:47:49Z
      DOI: 10.1177/1460458220987278
      Issue No: Vol. 27, No. 1 (2021)
       
  • Computational intelligence identifies alkaline phosphatase (ALP),
           alpha-fetoprotein (AFP), and hemoglobin levels as most predictive survival
           factors for hepatocellular carcinoma
    • Authors: Davide Chicco, Luca Oneto
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Liver cancer kills approximately 800 thousand people annually worldwide, and its most common subtype is hepatocellular carcinoma (HCC), which usually affects people with cirrhosis. Predicting survival of patients with HCC remains an important challenge, especially because technologies needed for this scope are not available in all hospitals. In this context, machine learning applied to medical records can be a fast, low-cost tool to predict survival and detect the most predictive features from health records. In this study, we analyzed medical data of 165 patients with HCC: we employed computational intelligence to predict their survival, and to detect the most relevant clinical factors able to discriminate survived from deceased cases. Afterwards, we compared our data mining results with those obtained through statistical tests and scientific literature findings. Our analysis revealed that blood levels of alkaline-phosphatase (ALP), alpha-fetoprotein (AFP), and hemoglobin are the most effective prognostic factors in this dataset. We found literature supporting association of these three factors with hepatoma, even though only AFP has been used in a prognostic index. Our results suggest that ALP and hemoglobin can be candidates for future HCC prognostic indexes, and that physicians could focus on ALP, AFP, and hemoglobin when studying HCC records.
      Citation: Health Informatics Journal
      PubDate: 2021-01-28T07:47:31Z
      DOI: 10.1177/1460458220984205
      Issue No: Vol. 27, No. 1 (2021)
       
  • Medication reconciliation process: Assessing value, adoption, and the
           potential of information technology from pharmacists’ perspective
    • Authors: Abdullah Al Anazi
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      The Medication Reconciliation (MedRec) process aims to improve patient safety through safe prescription and medication administration. A validated survey was carried out to address aspects related to MedRec process, its obstacles, the role of information technology, and the required functionalities for optimizing the MedRec process. A total of 81% of the survey’s respondents acknowledged the roles of EHR (62% of respondents), PHR (41%), and electronic medication registration list (33%) as necessary technology tools for MedRec. Most respondents emphasized the need to compile multiple medications’ entries of information technology systems into one application (96.4%), allowing the entries from community pharmacies (90.6%). Further, incorporating information technology into the MedRec process presents a challenge in terms of legal responsibility (92 %) and the ability to integrate medications with other hospitals and community medications (78.6%). Findings affirm the need for a well-designed MedRec process aided with information technology solutions. The external data and user preferences should be considered when redesigning the MedRec process. The study also suggests initiating a policy that mandates sharing data necessary for creating a compiled medication list for each patient. MedRec is an indispensable tool for building a fruitful medication management system in a healthcare organization.
      Citation: Health Informatics Journal
      PubDate: 2021-01-20T09:23:15Z
      DOI: 10.1177/1460458220987276
      Issue No: Vol. 27, No. 1 (2021)
       
  • Estimation of COVID-19 epidemic curves using genetic programming algorithm
    • Authors: Nikola Anđelić, Sandi Baressi Šegota, Ivan Lorencin, Vedran Mrzljak, Zlatan Car
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      This paper investigates the possibility of the implementation of Genetic Programming (GP) algorithm on a publicly available COVID-19 data set, in order to obtain mathematical models which could be used for estimation of confirmed, deceased, and recovered cases and the estimation of epidemiology curve for specific countries, with a high number of cases, such as China, Italy, Spain, and USA and as well as on the global scale. The conducted investigation shows that the best mathematical models produced for estimating confirmed and deceased cases achieved R2 scores of 0.999, while the models developed for estimation of recovered cases achieved the R2 score of 0.998. The equations generated for confirmed, deceased, and recovered cases were combined in order to estimate the epidemiology curve of specific countries and on the global scale. The estimated epidemiology curve for each country obtained from these equations is almost identical to the real data contained within the data set.
      Citation: Health Informatics Journal
      PubDate: 2021-01-16T11:35:30Z
      DOI: 10.1177/1460458220976728
      Issue No: Vol. 27, No. 1 (2021)
       
  • Structuring electronic dental records through deep learning for a clinical
           decision support system
    • Authors: Qingxiao Chen, Xuesi Zhou, Ji Wu, Yongsheng Zhou
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Extracting information from unstructured clinical text is a fundamental and challenging task in medical informatics. Our study aims to construct a natural language processing (NLP) workflow to extract information from Chinese electronic dental records (EDRs) for clinical decision support systems (CDSSs). We extracted attributes, attribute values, and tooth positions based on an existing ontology from EDRs. A workflow integrating deep learning with keywords was constructed, in which vectors representing texts were unsupervised learned. Specifically, we implemented Sentence2vec to learn sentence vectors and Word2vec to learn word vectors. For attribute recognition, we calculated similarity values among sentence vectors and extracted attributes based on our selection strategy. For attribute value recognition, we expanded the keyword database by calculating similarity values among word vectors to select keywords. Performance of our workflow with the hybrid method was evaluated and compared with keyword-based method and deep learning method. In both attribute and value recognition, the hybrid method outperforms the other two methods in achieving high precision (0.94, 0.94), recall (0.74, 0.82), and F score (0.83, 0.88). Our NLP workflow can efficiently structure narrative text from EDRs, providing accurate input information and a solid foundation for further data-based CDSSs.
      Citation: Health Informatics Journal
      PubDate: 2021-01-15T06:35:57Z
      DOI: 10.1177/1460458220980036
      Issue No: Vol. 27, No. 1 (2021)
       
  • Patients’ moral attitudes toward electronic health records: Survey study
           with vignettes and statements
    • Authors: Tania Moerenhout, Ignaas Devisch, Laetitia Cooreman, Jodie Bernaerdt, An De Sutter, Veerle Provoost
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Patient access to electronic health records gives rise to ethical questions related to the patient-doctor-computer relationship. Our study aims to examine patients’ moral attitudes toward a shared EHR, with a focus on autonomy, information access, and responsibility. A de novo self-administered questionnaire containing three vignettes and 15 statements was distributed among patients in four different settings. A total of 1688 valid questionnaires were collected. Patients’ mean age was 51 years, 61% was female, 50% had a higher degree (college or university), and almost 50% suffered from a chronic illness. Respondents were hesitant to hide sensitive information electronically from their care providers. They also strongly believed hiding information could negatively affect the quality of care provided. Participants preferred to be informed about negative test results in a face-to-face conversation, or would have every patient decide individually how they want to receive results. Patients generally had little experience using patient portal systems and expressed a need for more information on EHRs in this survey. They tended to be hesitant to take up control over their medical data in the EHR and deemed patients share a responsibility for the accuracy of information in their record.
      Citation: Health Informatics Journal
      PubDate: 2021-01-15T06:35:57Z
      DOI: 10.1177/1460458220980039
      Issue No: Vol. 27, No. 1 (2021)
       
  • The impact of algorithmic decision-making processes on young
           people’s well-being
    • Authors: Elvira Perez Vallejos, Liz Dowthwaite, Helen Creswich, Virginia Portillo, Ansgar Koene, Marina Jirotka, Amy McCarthy, Derek McAuley
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      This study aims to capture the online experiences of young people when interacting with algorithm mediated systems and their impact on their well-being. We draw on qualitative (focus groups) and quantitative (survey) data from a total of 260 young people to bring their opinions to the forefront while eliciting discussions. The results of the study revealed the young people’s positive as well as negative experiences of using online platforms. Benefits such as convenience, entertainment and personalised search results were identified. However, the data also reveals participants’ concerns for their privacy, safety and trust when online, which can have a significant impact on their well-being. We conclude by recommending that online platforms acknowledge and enact on their responsibility to protect the privacy of their young users, recognising the significant developmental milestones that this group experience during these early years, and the impact that algorithm mediated systems may have on them. We argue that governments need to incorporate policies that require technologists and others to embed the safeguarding of users’ well-being within the core of the design of Internet products and services to improve the user experiences and psychological well-being of all, but especially those of children and young people.
      Citation: Health Informatics Journal
      PubDate: 2021-01-15T06:35:55Z
      DOI: 10.1177/1460458220972750
      Issue No: Vol. 27, No. 1 (2021)
       
  • Validity and reliability testing of the Indonesian version of the eHealth
           Literacy Scale during the COVID-19 pandemic
    • Authors: Maria Cellina Wijaya, Yudhistira Pradnyan Kloping
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Nowadays, it is common for people to look for health care information on the internet. The eHealth Literacy Scale (eHEALS) is commonly used to measure eHealth literacy. As of the publication of this study, the Indonesian version for eHEALS has not been published even though eHealth literacy is necessary, especially in the current COVID-19 pandemic. We aimed to evaluate the validity and reliability of the Indonesian version of eHEALS (I-eHEALS). A total of 100 respondents in East Java were involved in this cross-sectional study. Pearson-product moment correlation method and construct validity were used to validate the results. The reliability was determined based on the Cronbach’s alpha internal consistency measurement and intraclass correlation coefficient (ICC). The Pearson correlation analysis results are significantly higher (r > 0.254, p 
      Citation: Health Informatics Journal
      PubDate: 2021-01-15T06:35:55Z
      DOI: 10.1177/1460458220975466
      Issue No: Vol. 27, No. 1 (2021)
       
  • Web-based education of the elderly improves drug utilization literacy: A
           randomized controlled trial
    • Authors: Maria Qvarfordt, Victoria Throfast, Göran Petersson, Tora Hammar, Lina Hellström
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      The aim of this study was to explore the effects of web-based education in the field of drug utilization on elderly individuals’ knowledge of, concerns about and self-assessed understanding of drug utilization. The 260 included participants were randomized to a control group or an intervention group. To assess drug utilization literacy, we used a questionnaire containing 20 multiple-choice questions on drug utilization and ten statements about drug utilization (to which participants graded their response using a Likert scale: two about common concerns and eight about their self-assessed understanding of drug utilization). The Beliefs about Medicines Questionnaire-General was also used. The intervention group scored higher on the knowledge questions (p 
      Citation: Health Informatics Journal
      PubDate: 2021-01-15T06:35:54Z
      DOI: 10.1177/1460458220977585
      Issue No: Vol. 27, No. 1 (2021)
       
  • Generation of reusable learning objects from digital medical collections:
           An analysis based on the MASMDOA framework
    • Authors: Félix Buendía, Joaquín Gayoso-Cabada, José-Luis Sierra
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Learning Objects represent a widespread approach to structuring instructional materials in a large variety of educational contexts. The main aim of this work consists of analyzing the process of generating reusable learning objects followed by Clavy, a tool that can be used to retrieve data from multiple medical knowledge sources and reconfigure such sources in diverse multimedia-based structures and organizations. From these organizations, Clavy is able to generate learning objects that can be adapted to various instructional healthcare scenarios with several types of user profiles and distinct learning requirements. Moreover, Clavy provides the capability of exporting these learning objects through standard educational specifications, which improves their reusability features. The analysis proposed is conducted following criteria defined by the MASMDOA framework for comparing and selecting learning object generation methodologies. The analysis insights highlight the importance of having a tool to transfer knowledge from the available digital medical collections to learning objects that can be easily accessed by medical students and healthcare practitioners through the most popular e-learning platforms.
      Citation: Health Informatics Journal
      PubDate: 2021-01-15T06:35:54Z
      DOI: 10.1177/1460458220977586
      Issue No: Vol. 27, No. 1 (2021)
       
  • The effects of a physical activity intervention based on a fatness and
           fitness smartphone app for University students
    • Authors: Adrià Muntaner-Mas, Victor A Sanchez-Azanza, Francisco B Ortega, Josep Vidal-Conti, Pere Antoni Borràs, Jaume Cantallops, Pere Palou
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Since the 2012 Lancet Series on physical activity, progress regarding this topic has been negligible at global level. Thus, improving physical activity levels in specific populations through new methodologies is positioned as a priority. The aim of this study was to determine the effects of a physical activity intervention on body fatness composition, and measured and self-reported physical fitness components based on the use of a smartphone app. The investigation included 100 Spanish university students, cluster-randomized into the smartphone app intervention group or a control group (n = 35 and n = 31 respectively, after applying exclusion criteria). The physical activity intervention comprised a 9-week programme designed to promote a healthy physical activity pattern using a smartphone app. Specifically, an mHealth approach was taken containing five BCTs. The results showed that the intervention group improved their physical fitness (F = 8.1, p = .006) and reported better general scores in self-reported physical fitness (F = 7.4, p = .008) over time, in comparison to the control group. However, the intervention group did not show any changes to their fatness. Further research is needed to disentangle which BCTs are more effective to achieve physical health improvements when using physical activity apps.
      Citation: Health Informatics Journal
      PubDate: 2021-01-15T06:35:52Z
      DOI: 10.1177/1460458220987275
      Issue No: Vol. 27, No. 1 (2021)
       
  • Design and evaluation of mobile scenario based learning in the
           self-management of chronic pain
    • Authors: Ioannis Koulas, Antonis Billis, Nikoletta Kousouri, Vasilis Vasilopoulos, Evangelos Lykotsetas, Dimitris Kola, Eleni Dafli, Dimitris Spachos, Panagiotis Bamidis
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Chronic pain is a lifelong issue, being one of the main causes of disability, affecting a great number of people worldwide, many of which often avoid seeking medical advice from pain experts and/or demonstrate poor adherence to their therapeutic plan. One of the most important steps in achieving a manageable course of disease, is the ability of self-management. We aimed at applying a method of systematic patient education and self-management through the use of Virtual Patients (VPs), a well-established method for educating medical doctors and students but never before targeting patients. Two VPs scenarios were designed, tested and evaluated by patients with rheumatic disorders, achieving a SUS score of 88/100 “Best Imaginable”, alongside with positive reviews from the participants. The positive feedback from the patients supports the potential of VP educational paradigm to educate these patients and equip them with disease coping skills and strategies.
      Citation: Health Informatics Journal
      PubDate: 2021-01-15T06:35:51Z
      DOI: 10.1177/1460458220977575
      Issue No: Vol. 27, No. 1 (2021)
       
  • Identifying strategies to overcome roadblocks to utilising near real-time
           healthcare and administrative data to create a Scotland-wide learning
           health system
    • Authors: Mome Mukherjee, Kathrin Cresswell, Aziz Sheikh
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Creating a learning health system could help reduce variations in quality of care. Success is dependent on timely access to health data. To explore the barriers and facilitators to timely access to patients’ data, we conducted in-depth semi-structured interviews with 37 purposively sampled participants from government, the NHS and academia across Scotland. Interviews were analysed using the framework approach. Participants were of the view that Scotland could play a leading role in the exploitation of routine data to drive forward service improvements, but highlighted major impediments: (i) persistence of paper-based records and a variety of information systems; (ii) the need for a proportionate approach to managing information governance; and (iii) the need for support structures to facilitate accrual, processing, linking, analysis and timely use and reuse of data for patient benefit. There is a pressing need to digitise and integrate existing health information infrastructures, guided by a nationwide proportionate information governance approach and the need to enhance technological and human capabilities to support these efforts.
      Citation: Health Informatics Journal
      PubDate: 2021-01-15T06:35:51Z
      DOI: 10.1177/1460458220977579
      Issue No: Vol. 27, No. 1 (2021)
       
  • Design of 1-year mortality forecast at hospital admission: A machine
           learning approach
    • Authors: Vicent Blanes-Selva, Vicente Ruiz-García, Salvador Tortajada, José-Miguel Benedí, Bernardo Valdivieso, Juan M García-Gómez
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Palliative care is referred to a set of programs for patients that suffer life-limiting illnesses. These programs aim to maximize the quality of life (QoL) for the last stage of life. They are currently based on clinical evaluation of the risk of 1-year mortality. The main aim of this work is to develop and validate machine-learning-based models to predict the exitus of a patient within the next year using data gathered at hospital admission. Five machine-learning techniques were applied using a retrospective dataset. The evaluation was performed with five metrics computed by a resampling strategy: Accuracy, the area under the ROC curve, Specificity, Sensitivity, and the Balanced Error Rate. All models reported an AUC ROC from 0.857 to 0.91. Specifically, Gradient Boosting Classifier was the best model, producing an AUC ROC of 0.91, a sensitivity of 0.858, a specificity of 0.808, and a BER of 0.1687. Information from standard procedures at hospital admission combined with machine learning techniques produced models with competitive discriminative power. Our models reach the best results reported in the state of the art. These results demonstrate that they can be used as an accurate data-driven palliative care criteria inclusion.
      Citation: Health Informatics Journal
      PubDate: 2021-01-13T10:15:55Z
      DOI: 10.1177/1460458220987580
      Issue No: Vol. 27, No. 1 (2021)
       
  • Acoustic and prosodic information for home monitoring of bipolar disorder
    • Authors: Mireia Farrús, Joan Codina-Filbà, Joan Escudero
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Epidemiological studies suggest that bipolar disorder has a prevalence of about 1% in European countries, becoming one of the most disabling illnesses in working age adults, and often long-term and persistent with complex management and treatment. Therefore, the capacity of home monitoring for patients with this disorder is crucial for their quality of life. The current paper introduces the use of speech-based information as an easy-to-record, ubiquitous and non-intrusive health sensor suitable for home monitoring, and its application in the framework on the NYMPHA-MD project. Some preliminary results also show the potential of acoustic and prosodic features to detect and classify bipolar disorder, by predicting the values of the Hamilton Depression Rating Scale (HDRS) and the Young Mania Rating Scale (YMRS) from speech.
      Citation: Health Informatics Journal
      PubDate: 2021-01-13T10:13:30Z
      DOI: 10.1177/1460458220972755
      Issue No: Vol. 27, No. 1 (2021)
       
  • Proposing a mobile apps acceptance model for users in the health area: A
           systematic literature review and meta-analysis
    • Authors: Sami S Binyamin, Bassam A Zafar
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Due to rapid advancements in the field of information and communication technologies, mobile health (mHealth) has become a significant topic in the delivery of healthcare. Despite the perceived advantages and the large number of mHealth initiatives, the success of mHealth ultimately relies on whether these initiatives are used; their benefits will be diminished should people not use them. Previous literature has found that the adoption of mHealth by users is not yet widespread, and little research has been conducted on this problem. Therefore, this study identifies the antecedents of the intention to use mHealth and proposes a general model that might prove beneficial in explaining the acceptance of mHealth. The authors performed a quantitative meta-analysis of 49 journal papers published over the past 10 years and systematically reviewed the evidence regarding the most commonly identified factors that may affect the acceptance of mHealth. The findings indicate that the proposed model includes the seven most commonly used relationships in the selected articles. More specifically, the model assumes that perceived usefulness positively affects perceived ease of use and user behavioral intention to use mHealth is commonly influenced by five factors: perceived usefulness, perceived ease of use, attitude toward behavior, subjective norms, and facilitating conditions. The results of this work provide important insights into the predictors of mHealth acceptance for future researchers and practitioners.
      Citation: Health Informatics Journal
      PubDate: 2021-01-13T10:11:10Z
      DOI: 10.1177/1460458220976737
      Issue No: Vol. 27, No. 1 (2021)
       
  • The paradox of project success despite lack of the “My Pathway”
           telehealth platform usage
    • Authors: Sune Dueholm Müller, Ditte Lykke Wehner, Henrike Konzag, Martin Vesterby, Mette Terp Høybye
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      The article investigates the paradoxical success of a Danish telehealth project introducing the “My Pathway” platform to reduce the length of patient stays while maintaining patient satisfaction. These goals were achieved in the project, which was considered successful despite the lack of actual platform usage. Based on a qualitative, longitudinal case study we investigate this paradox by showing how barriers and facilitators have influenced telehealth adoption and use in the post-implementation process, affecting the overall success of the project. The study makes two contributions. First, it describes dynamics of adoption barriers, that is, that barriers are interrelated and influence adoption to varying degrees over time. Adoption barriers resulted in the telehealth platform not being used and it consequently only influenced the actual project success and goal achievement indirectly. Second, it highlights information management as a critical facilitator in telehealth adoption and use. Information management facilitated achievement of project goals despite the lack of actual use of “My Pathway,” which explains the paradoxical project success. Based on these interpretations, we point to information management as a critical facilitator of the success of telehealth initiatives and provide recommendations for research and practice.
      Citation: Health Informatics Journal
      PubDate: 2021-01-13T10:08:10Z
      DOI: 10.1177/1460458220976734
      Issue No: Vol. 27, No. 1 (2021)
       
  • Recommending healthy meal plans by optimising nature-inspired
           many-objective diet problem
    • Authors: Cumali Türkmenoğlu, A Şima Etaner Uyar, Berna Kiraz
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      Healthy eating is an important issue affecting a large part of the world population, so human diets are becoming increasingly popular, especially with the devastating consequences of Coronavirus Disease (Covid-19). A realistic and sustainable diet plan can help us to have a healthy eating habit since it considers most of the expectations from a diet without any restriction. In this study, the classical diet problem has been extended in terms of modelling, data sets and solution approach. Inspired by animals’ hunting strategies, it was re-modelled as a many-objective optimisation problem. In order to have realistic and applicable diet plans, cooked dishes are used. A well-known many-objective evolutionary algorithm is used to solve the diet problem. Results show that our approach can optimise specialised daily menus for different user types, depending on their preferences, age, gender and body index. Our approach can be easily adapted for users with health issues by adding new constraints and objectives. Our approach can be used individually or by dietitians as a decision support mechanism.
      Citation: Health Informatics Journal
      PubDate: 2021-01-13T10:05:09Z
      DOI: 10.1177/1460458220976719
      Issue No: Vol. 27, No. 1 (2021)
       
  • Drivers of expectations: Why are Norwegian general practitioners skeptical
           of a prospective electronic health record'
    • Authors: Morten Hertzum, Gunnar Ellingsen, Line Melby
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      While expectations are well-known drivers of electronic health record (EHR) adoption, the drivers of expectations are more elusive. On the basis of interviews with general practitioners (GPs), we investigate how the early implementation process drives their expectations of an EHR that is being implemented in Norway. The GPs’ expectations of the prospective EHR are driven by (a) satisfying experiences with their current system, (b) the transfer of others’ experiences with the prospective EHR, (c) a sense of alignment, or lack thereof, with those in charge of the implementation process, (d) uncertainty about the inclusion of GP needs, and (e) competing technological futures. To manage expectations, starting early is important. Mismanaged expectations produce a need for convincing people to reverse their expectations. This appears to be the situation in Norway, where the GPs are currently skeptical of the prospective EHR.
      Citation: Health Informatics Journal
      PubDate: 2021-01-13T10:03:09Z
      DOI: 10.1177/1460458220987298
      Issue No: Vol. 27, No. 1 (2021)
       
  • Sensor-based platforms for remote management of chronic diseases in
           developing regions: A qualitative approach examining the perspectives of
           healthcare professionals
    • Authors: Adelina Basholli, Thomas Lagkas, Peter A Bath, George Eleftherakis
      Abstract: Health Informatics Journal, Volume 27, Issue 1, January-March 2021.
      The continuous monitoring of chronic diseases serves as one of the cornerstones in the efforts to improve the quality of life of patients and maintain the healthcare services provided to them. This study aims to provide an in-depth understanding of the perspectives of healthcare professionals on using sensor-based networks (SBN) used for remote and continuous monitoring of patients with chronic illness in Kosovo, a developing country. A qualitative research method was used to interview 26 healthcare professionals. The study results demonstrate the positive attitudes of participants to using SBN, and considers their concerns on the impact of these platforms on the patient’s life, the number of visits in the medical centre, data privacy concerning interactions between patients and their medical personnel and the costs of the platform. Further to that, the study makes an important contribution to knowledge by identifying the challenges and drawbacks of these platforms and provides recommendations for system designers.
      Citation: Health Informatics Journal
      PubDate: 2021-01-13T09:55:12Z
      DOI: 10.1177/1460458220979350
      Issue No: Vol. 27, No. 1 (2021)
       
  • RETRACTION NOTICE: Atrial fibrillation classification using deep learning
           algorithm in Internet of Things–based smart healthcare system
    • Abstract: Health Informatics Journal, Ahead of Print.

      Citation: Health Informatics Journal
      PubDate: 2020-11-04T07:25:11Z
      DOI: 10.1177/1460458220968756
       
  • Erratum to “Using photos for public health communication: A
           computational analysis of the Centers for Disease Control and Prevention
           Instagram photos and public responses”
    • Abstract: Health Informatics Journal, Ahead of Print.

      Citation: Health Informatics Journal
      PubDate: 2020-09-24T07:23:55Z
      DOI: 10.1177/1460458220959512
       
  • RETRACTION NOTICE: FoodKnight: A mobile educational game and analyses of
           obesity awareness in children
    • Abstract: Health Informatics Journal, Ahead of Print.

      Citation: Health Informatics Journal
      PubDate: 2020-09-18T04:33:36Z
      DOI: 10.1177/1460458220957178
       
  • Expression of concern
    • Abstract: Health Informatics Journal, Ahead of Print.

      Citation: Health Informatics Journal
      PubDate: 2020-08-08T09:53:28Z
      DOI: 10.1177/1460458220948624
       
  • Retraction Notice: Speech enhancement method using deep learning approach
           for hearing-impaired listeners
    • Abstract: Health Informatics Journal, Ahead of Print.

      Citation: Health Informatics Journal
      PubDate: 2020-07-28T10:02:12Z
      DOI: 10.1177/1460458220943995
       
  • Speech enhancement method using deep learning approach for
           hearing-impaired listeners

         This is an Open Access Article Open Access Article

    • Authors: PF Khaleelur Rahiman, VS Jayanthi, AN Jayanthi
      Abstract: Health Informatics Journal, Ahead of Print.
      A deep learning-based speech enhancement method is proposed to aid hearing-impaired listeners by improving speech intelligibility. The algorithm decomposes the noisy speech signal into frames (as features). Subsequently, a deep convolutional neural network is fed with decomposed noisy speech signal frames to produce frequency channel estimation. However, a higher signal-to-noise ratio information is contained in produced frequency channel estimation. Using this estimate, speech-dominated cochlear implant channels are taken to produce electrical stimulation. This process is the same as that of the conventional n-of-m cochlear implant coding strategies. To determine the speech-in-noise performance of 12 cochlear implant users, the fan and music sound applied are considered as background noises. Performance of the proposed algorithm is evaluated by considering these background noises. Low processing delay and reliable architecture are the best characteristics of the deep learning-based speech enhancement algorithm; hence, this can be suitably applied for all applications of hearing devices. Experimental results demonstrate that deep convolutional neural network approach appeared more promising than conventional approaches.
      Citation: Health Informatics Journal
      PubDate: 2020-01-23T09:25:23Z
      DOI: 10.1177/1460458219893850
       
 
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