Published on in Vol 20, No 5 (2018): May

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/7299, first published .
Electronic Health Use in the European Union and the Effect of Multimorbidity: Cross-Sectional Survey

Electronic Health Use in the European Union and the Effect of Multimorbidity: Cross-Sectional Survey

Electronic Health Use in the European Union and the Effect of Multimorbidity: Cross-Sectional Survey

Journals

  1. Hallberg D, Salimi N. Qualitative and Quantitative Analysis of Definitions of e-Health and m-Health. Healthcare Informatics Research 2020;26(2):119 View
  2. Caldeira C, Gui X, Reynolds T, Bietz M, Chen Y. Managing healthcare conflicts when living with multiple chronic conditions. International Journal of Human-Computer Studies 2021;145:102494 View
  3. Castillo-Olea C, Garcia-Zapirain Soto B, Zuñiga C. Evaluation of Prevalence of the Sarcopenia Level Using Machine Learning Techniques: Case Study in Tijuana Baja California, Mexico. International Journal of Environmental Research and Public Health 2020;17(6):1917 View
  4. Melchiorre M, Papa R, Quattrini S, Lamura G, Barbabella F. Integrated Care Programs for People with Multimorbidity in European Countries: eHealth Adoption in Health Systems. BioMed Research International 2020;2020:1 View
  5. Senft N, Everson J. eHealth Engagement as a Response to Negative Healthcare Experiences: Cross-Sectional Survey Analysis. Journal of Medical Internet Research 2018;20(12):e11034 View
  6. Baltaxe E, Czypionka T, Kraus M, Reiss M, Askildsen J, Grenkovic R, Lindén T, Pitter J, Rutten-van Molken M, Solans O, Stokes J, Struckmann V, Roca J, Cano I. Digital Health Transformation of Integrated Care in Europe: Overarching Analysis of 17 Integrated Care Programs. Journal of Medical Internet Research 2019;21(9):e14956 View
  7. Kong Q, Riedewald D, Askari M. Factors Affecting Portal Usage Among Chronically Ill Patients During the COVID-19 Pandemic in the Netherlands: Cross-sectional Study. JMIR Human Factors 2021;8(3):e26003 View
  8. Hartono I, Della T, Kawi Y, Yuniarty . Determinants factor affecting user continuance usage and intention to recommend of mobile telemedicine. IOP Conference Series: Earth and Environmental Science 2021;794(1):012079 View
  9. Xie Z, Zhang Y, Wei R, Li Y, Mei Z. Prognostic Nomograms for Elderly Patients with Small Cell Lung Cancer Brain Metastasis: A Surveillance, Epidemiology, and End Results Population-Based Study with Temporal External Validation. World Neurosurgery 2024;189:e632 View