This paper is in the following e-collection/theme issue:

mHealth in a Clinical Setting (624) Mobile Health (mhealth) (2982) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1428) mHealth for Wellness, Behavior Change and Prevention (2922) mHealth for Treatment Adherence (404)

Published on in Vol 4, No 4 (2016): Oct-Dec

Patient-Facing Mobile Apps to Treat High-Need, High-Cost Populations: A Scoping Review

Patient-Facing Mobile Apps to Treat High-Need, High-Cost Populations: A Scoping Review

Patient-Facing Mobile Apps to Treat High-Need, High-Cost Populations: A Scoping Review

Authors of this article:

Karandeep Singh1 Author Orcid Image ;   Kaitlin Drouin2 Author Orcid Image ;   Lisa P Newmark3 Author Orcid Image ;   Malina Filkins4 Author Orcid Image ;   Elizabeth Silvers3 Author Orcid Image ;   Paul A Bain5 Author Orcid Image ;   Donna M Zulman6, 7 Author Orcid Image ;   Jae-Ho Lee8 Author Orcid Image ;   Ronen Rozenblum5, 9 Author Orcid Image ;   Erika Pabo5, 9 Author Orcid Image ;   Adam Landman5, 10 Author Orcid Image ;   Elissa V Klinger9 Author Orcid Image ;   David W Bates5, 9, 11 Author Orcid Image
Article Authors Cited by (44) Tweetations (16) Metrics

Journals

  1. Park Y, Lee Y, Kim J, Kim J, Kim H, Kim Y, Kim W, Lee J. Managing Patient-Generated Health Data Through Mobile Personal Health Records: Analysis of Usage Data. JMIR mHealth and uHealth 2018;6(4):e89 View
  2. Klimova B. Mobile Phone Apps in the Management and Assessment of Mild Cognitive Impairment and/or Mild-to-Moderate Dementia: An Opinion Article on Recent Findings. Frontiers in Human Neuroscience 2017;11 View
  3. Chattopadhyay D, Ma T, Sharifi H, Martyn-Nemeth P. Computer-Controlled Virtual Humans in Patient-Facing Systems: Systematic Review and Meta-Analysis. Journal of Medical Internet Research 2020;22(7):e18839 View
  4. Tarricone R, Cucciniello M, Armeni P, Petracca F, Desouza K, Hall L, Keefe D. Mobile Health Divide Between Clinicians and Patients in Cancer Care: Results From a Cross-Sectional International Survey. JMIR mHealth and uHealth 2019;7(9):e13584 View
  5. Davies K, Cheraghi-Sohi S, Ong B, Perryman K, Sanders C. Co-designing an Adaption of a Mobile App to Enhance Communication, Safety, and Well-being Among People Living at Home With Early-Stage Dementia: Protocol for an Exploratory Multiple Case Study. JMIR Research Protocols 2021;10(12):e19543 View
  6. Meinert E, Rahman E, Potter A, Lawrence W, Van Velthoven M. Acceptability and Usability of the Mobile Digital Health App NoObesity for Families and Health Care Professionals: Protocol for a Feasibility Study. JMIR Research Protocols 2020;9(7):e18068 View
  7. Kim H, Park E, Lee S, Kim M, Park E, Hong S. Self-management of Older Korean Adults Living with Chronic Diseases: The mHealth Training Protocol and Feasibility Study (Preprint). JMIR Research Protocols 2018 View
  8. Breton M, Patek S, Lv D, Schertz E, Robic J, Pinnata J, Kollar L, Barnett C, Wakeman C, Oliveri M, Fabris C, Chernavvsky D, Kovatchev B, Anderson S. Continuous Glucose Monitoring and Insulin Informed Advisory System with Automated Titration and Dosing of Insulin Reduces Glucose Variability in Type 1 Diabetes Mellitus. Diabetes Technology & Therapeutics 2018;20(8):531 View
  9. Park Y, Lee E, Na W, Park S, Lee Y, Lee J. Is Blockchain Technology Suitable for Managing Personal Health Records? Mixed-Methods Study to Test Feasibility. Journal of Medical Internet Research 2019;21(2):e12533 View
  10. Bhattacharyya O, Mossman K, Gustafsson L, Schneider E. Using Human-Centered Design to Build a Digital Health Advisor for Patients With Complex Needs: Persona and Prototype Development. Journal of Medical Internet Research 2019;21(5):e10318 View
  11. Kim H, Park E, Lee S, Kim M, Park E, Hong S. Self-Management of Chronic Diseases Among Older Korean Adults: An mHealth Training, Protocol, and Feasibility Study. JMIR mHealth and uHealth 2018;6(6):e147 View
  12. Rodriguez J, Singh K. The Spanish Availability and Readability of Diabetes Apps. Journal of Diabetes Science and Technology 2018;12(3):719 View
  13. DiFilippo K, Huang W, Chapman-Novakofski K. Mobile Apps for the Dietary Approaches to Stop Hypertension (DASH): App Quality Evaluation. Journal of Nutrition Education and Behavior 2018;50(6):620 View
  14. Levine D, Co Z, Newmark L, Groisser A, Holmgren A, Haas J, Bates D. Design and testing of a mobile health application rating tool. npj Digital Medicine 2020;3(1) View
  15. Singh K, Diamantidis C, Ramani S, Bhavsar N, Mara P, Warner J, Rodriguez J, Wang T, Wright-Nunes J. Patients’ and Nephrologists’ Evaluation of Patient-Facing Smartphone Apps for CKD. Clinical Journal of the American Society of Nephrology 2019;14(4):523 View
  16. Ifejika N, Bhadane M, Cai C, Noser E, Grotta J, Savitz S. Use of a Smartphone-Based Mobile App for Weight Management in Obese Minority Stroke Survivors: Pilot Randomized Controlled Trial With Open Blinded End Point. JMIR mHealth and uHealth 2020;8(4):e17816 View
  17. Lagan S, Aquino P, Emerson M, Fortuna K, Walker R, Torous J. Actionable health app evaluation: translating expert frameworks into objective metrics. npj Digital Medicine 2020;3(1) View
  18. Wang P, Luo D, Lu F, Elias J, Landman A, Michaud K, Lee Y. A Novel Mobile App and Population Management System to Manage Rheumatoid Arthritis Flares: Protocol for a Randomized Controlled Trial. JMIR Research Protocols 2018;7(4):e84 View
  19. Singh K. Mobile Health in Dialysis: The Best Engagement Medium Is the One that’s with Patients. Clinical Journal of the American Society of Nephrology 2021;16(1):12 View
  20. Karim J, Talhouk A. Person-Generated Health Data in Women’s Health: Protocol for a Scoping Review. JMIR Research Protocols 2021;10(5):e26110 View
  21. Katayama Y, Kiyohara K, Hirose T, Matsuyama T, Ishida K, Nakao S, Tachino J, Ojima M, Noda T, Kiguchi T, Hayashida S, Kitamura T, Mizobata Y, Shimazu T. A Mobile App for Self-Triage for Pediatric Emergency Patients in Japan: 4 Year Descriptive Epidemiological Study. JMIR Pediatrics and Parenting 2021;4(2):e27581 View
  22. Zhang T, Dong L, Jing H, Gao S. Smartphone Applications in the Management of Parkinson's Disease in a Family Setting: An Opinion Article. Frontiers in Neurology 2021;12 View
  23. Upadhyay V, Landman A, Hassett M. Landscape Analysis of Oncology Mobile Health Applications. JCO Clinical Cancer Informatics 2021;(5):579 View
  24. Beck A, Kelly P, Deane F, Baker A, Hides L, Manning V, Shakeshaft A, Neale J, Kelly J, Gray R, Argent A, McGlaughlin R, Chao R, Martini M. Developing a mHealth Routine Outcome Monitoring and Feedback App (“SMART Track”) to Support Self-Management of Addictive Behaviours. Frontiers in Psychiatry 2021;12 View
  25. San Giovanni C, Dawley E, Pope C, Steffen M, Roberts J. The Doctor Will “Friend” You Now: A Qualitative Study on Adolescents’ Preferences for Weight Management App Features. Southern Medical Journal 2021;114(7):373 View
  26. Kim D, Lee Y, Oh J, Seo D, Lee K, Kim Y, Kim W, Lee J. Effects of Patient-Generated Health Data: Comparison of Two Versions of Long-Term Mobile Personal Health Record Usage Logs. Healthcare 2021;10(1):53 View
  27. Zhou Y. Mobile Health Applications to Tackle Obesity and Assist Weight-Management Goals among Adults. Highlights in Science, Engineering and Technology 2022;2:63 View
  28. Colmegna P, Bisio A, McFadden R, Wakeman C, Oliveri M, Nass R, Breton M. Evaluation of a Web-Based Simulation Tool for Self-Management Support in Type 1 Diabetes: A Pilot Study. IEEE Journal of Biomedical and Health Informatics 2023;27(1):515 View
  29. Hong S, Lee S, Song K, Kim M, Kim Y, Kim H, Kim H. A nurse-led mHealth intervention to alleviate depressive symptoms in older adults living alone in the community: A quasi-experimental study. International Journal of Nursing Studies 2023;138:104431 View
  30. Kelly P, Beck A, Deane F, Larance B, Baker A, Hides L, Manning V, Shakeshaft A, Neale J, Kelly J, Oldmeadow C, Searles A, Palazzi K, Lawson K, Treloar C, Gray R, Argent A, McGlaughlin R. Feasibility of a Mobile Health App for Routine Outcome Monitoring and Feedback in SMART Recovery Mutual Support Groups: Stage 1 Mixed Methods Pilot Study. Journal of Medical Internet Research 2021;23(10):e25217 View
  31. Lattie E, Stiles-Shields C, Graham A. An overview of and recommendations for more accessible digital mental health services. Nature Reviews Psychology 2022;1(2):87 View
  32. Oliveira L, Lucato A, Fernandes D, Vieira L, Santos B, Silveira R. Use of technology for self-care in surgical wound infection surveillance: integrative review. Revista Brasileira de Enfermagem 2022;75(3) View
  33. Wilt M. Differentiation of Family System Inventory (DoFSI): Development and content validation of a new qualitative family intervention and evaluation tool. Australian and New Zealand Journal of Family Therapy 2023;44(2):179 View
  34. Hempel S, Bolshakova M, Hochman M, Jimenez E, Thompson G, Motala A, Ganz D, Gabrielian S, Edwards S, Zenner J, Dennis B, Chang E. Caring for high-need patients. BMC Health Services Research 2023;23(1) View
  35. Milne-Ives M, Rahman E, Bradwell H, Baines R, Boey T, Potter A, Lawrence W, Helena van Velthoven M, Meinert E, Ayatollahi H. Barriers and facilitators to parents’ engagement with and perceived impact of a childhood obesity app: A mixed-methods study. PLOS Digital Health 2024;3(3):e0000481 View
  36. Kim K, Kim S, Park Y, Lee E, Jung S, Kang J, An D, Min K, Shim S, Yu H, Han H. A blockchain-based healthcare data marketplace: prototype and demonstration. JAMIA Open 2024;7(2) View
  37. Park Y, Lee M, Kim S. Quality of Care in Hospitals and the Use of Mobile-Based Personal Health Record Applications: An Exploratory Study Using National Hospital Evaluation Data. Healthcare 2024;12(11):1064 View
  38. Augusto Duenhas Accorsi T, Tocci Moreira F, Aires Eduardo A, Albaladejo Morbeck R, Francine Köhler K, De Amicis Lima K, Henrique Sartorato Pedrotti C. Outcome After Self-Triage App Referral in Urgent Direct-to-Consumer Telemedicine Encounter. Telemedicine and e-Health 2024;30(8):2142 View
  39. Arthurs N, Browne S, Boardman R, O'Donnell S, Doyle G, Kechadi T, Shahid A, Tully L, O’Malley G. Usability of the BigO system in pediatric obesity treatment: A mixed-methods evaluation of clinical end-users. Computational and Structural Biotechnology Journal 2024;24:507 View
  40. Maaß L, Hrynyschyn R, Lange M, Löwe A, Burdenski K, Butten K, Vorberg S, Hachem M, Gorga A, Grieco V, Restivo V, Vella G, Varnfield M, Holl F. Challenges and Alternatives to Evaluation Methods and Regulation Approaches for Medical Apps as Mobile Medical Devices: International and Multidisciplinary Focus Group Discussion. Journal of Medical Internet Research 2024;26:e54814 View
  41. Marelli A, Rozenblum R, Bolster-Foucault C, Via-Dufresne Ley A, Maynard N, Amaria K, Galuppi B, Strohm S, Nguyen L, Dawe-McCord C, Putterman C, Kovacs A, Gorter J. Development of MyREADY Transition BBD Mobile App, a Health Intervention Technology Platform, to Improve Care Transition for Youth With Brain-Based Disabilities: User-Centered Design Approach. JMIR Pediatrics and Parenting 2024;7:e51606 View

Books/Policy Documents

  1. Singh K, Landman A. Key Advances in Clinical Informatics. View
  2. Tremblay M, Cucciniello M, Tarricone R, Porumbescu G, Desouza K. Designing for Digital Transformation. Co-Creating Services with Citizens and Industry. View
  3. MacMartin-Moglia K, Mahler M. Precision Medicine and Artificial Intelligence. View