1. Powley, L, Mcilroy, G, Simons, G, et al. Are online symptoms checkers useful for patients with inflammatory arthritis? BMC Musculoskelet Disord. 2016;17(1):362 DOI: 10.1186/s12891-016-1189-2
Google Scholar | Crossref | Medline2. Berry, AC, Cash, BD, Wang, B, et al. Online symptom checker diagnostic and triage accuracy for HIV and hepatitis C. Epidemiol Infect. 2019;147(104):e104.
Google Scholar | Crossref | Medline3. Perlman, A, Zilberg, AV, Bak, P, et al. Characteristics and symptoms of app users seeking COVID-19–related digital health information and remote services: Retrospective cohort study. J Med Internet Res. 2019;22(10):e23197.
Google Scholar | Crossref4. Marco-Ruiz, L, Bønes, E, de la Asunción, E, et al. Combining multivariate statistics and the think-aloud protocol to assess human-computer interaction barriers in symptom checkers. J Biomed Inform. 2017;74:104–122. DOI: 10.1016/j.jbi.2017.09.002
Google Scholar | Crossref | Medline5. Tenhunen, H, Hirvonen, P, Linna, M, et al. Intelligent patient flow management system at a primary healthcare center-The effect on service use and costs in decision support systems and education: Help and support in healthcare. Stud Health Technol Inform. 2018;255:142–146.
Google Scholar | Medline6. Munsch, N, Martin, A, Gruarin, S, et al. Diagnostic accuracy of web-based COVID-19 symptom checkers: comparison study. J Med Internet Res. 2020;22(10):e21299.
Google Scholar | Crossref | Medline7. Semigran, HL, Linder, JA, Gidengil, C, et al. Evaluation of symptom checkers for self-diagnosis and triage: Audit study. BMJ. 2018;351:h3480.
Google Scholar8. Ceney, A, Tolond, S, Glowinski, A, et al. Accuracy of online symptom checkers and the potential impact on service utilisation. PLoS One. 2021;16(7):e0254088. DOI: 10.1371/journal.pone.0254088
Google Scholar | Crossref | Medline9. Chambers, D, Cantrell, AJ, Johnson, M, et al. Digital and online symptom checkers and health assessment/triage services for urgent health problems: Systematic review. BMJ Open. 2019;9(8):e027743.
Google Scholar | Crossref | Medline10. Meyer, AND, Giardina, TD, Spitzmueller, C, et al. Patient perspectives on the usefulness of an artificial intelligence—Assisted symptom checker: Cross-Sectional Surv Study. 2020;22(1):e14679.
Google Scholar11. Mansab, F, Bhatti, S, Goyal, D. Performance of national COVID-19 symptom checkers’: A comparative case simulation study. BMJ Heal Care Inform. 2021;28(1):1–7.
Google Scholar12. Cresswell, K, Sheikh, A. Organizational issues in the implementation and adoption of health information technology innovations: An interpretative review. Int J Med Inform. 2013;82(5):e73–e86. DOI: 10.1016/j.ijmedinf.2012.10.007
Google Scholar | Crossref | Medline13. Laukka, E, Huhtakangas, M, Heponiemi, T, et al. Identifying the roles of healthcare leaders in HIT implementation: A scoping review of the quantitative and qualitative evidence. Int J Environ Res Public Health. 2020;17(8):2865.
Google Scholar | Crossref14. Kujala, S, Hörhammer, I, Heponiemi, T, et al. The role of frontline leaders in building health professional support for a new patient portal: Survey study. J Med Internet Res. 2019;21(3):e11413.
Google Scholar | Crossref | Medline15. Hikmet, N, Banerjee, S, Burns, MB. State of content: Healthcare executive’s role in information technology adoption. J Serv Sci Manag. 2012;5(02):124–131.
Google Scholar16. Greenhalgh, T, Stramer, K, Bratan, T, et al. Introduction of shared electronic records: Multi-site case study using diffusion of innovation theory. BMJ. 2008;337:a1786.
Google Scholar | Crossref | Medline17. Dugstad, J, Eide, T, Nilsen, ER, et al. Towards successful digital transformation through co-creation: A longitudinal study of a four-year implementation of digital monitoring technology in residential care for persons with dementia. BMC Health Services Research. 2019;19(1):366–417.
Google Scholar | Crossref | Medline18. Varsi, C, Ekstedt, M, Gammon, D, et al. Middle managers’ experiences and role in implementing an interactive tailored patient assessment eHealth intervention in clinical practice. CIN—Comput Inform Nurs.2015;33(6):249–257.
Google Scholar | Crossref | Medline19. Miller, SS, Gilbert, S, Virani, V, et al. Patients’ utilization and perception of an artificial intelligence-based symptom assessment and advice technology in a British primary care waiting room: Exploratory pilot study. JMIR Hum Factors. 2020;7(3):e19713.
Google Scholar | Crossref | Medline20. Deokar, AV, Sarnikar, S. Understanding process change management in electronic health record implementations. Inf Syst E-Business Manag. 2016;14:733–766.
Google Scholar | Crossref21. Boddy, D, King, G, Clark, JS, et al. The influence of context and process when implementing e-health. BMC Med Inform Decis Mak. 2009;9(1):9.
Google Scholar | Crossref | Medline22. Ministry of Social Affairs and Health . Social welfare and healthcare in Finland. 2019. Available from: https://stm.fi/en/social-and-health-services.
Google Scholar23. Ministry of Social Affairs and Health . Digital coronavirus information service now open in the public. 2020. Available from: https://stm.fi/en/-/sahkoinen-oirearviointi-koronavirusepailysta-kayttoon-koko-maahan.
Google Scholar24. Ward, MM, Vartak, S, Schwichtenberg, T, et al. Nurses’ perceptions of how clinical information system implementation affects workflow and patient care. CIN—Comput Inform Nurs 2011;29(9):502–511.
Google Scholar | Crossref | Medline25. Wakefield, DS, Halbesleben, JRB, Ward, MM, et al. Development of a measure of clinical information systems expectations and experiences. Med Care. 2007;45(9):884–890.
Google Scholar | Crossref | Medline26. Kirkendall, ES, Goldenhar, LM, Simon, JL, et al. Transitioning from a computerized provider order entry and paper documentation system to an electronic health record: Expectations and experiences of hospital staff. Int J Med Inform. 2013;82(11):1037–1045. DOI: 10.1016/j.ijmedinf.2013.08.005
Google Scholar | Crossref | Medline27. Kujala, S, Rajalahti, E, Heponiemi, T, et al. Health professionals’ expanding eHealth competences for supporting patients’ self-management. Stud Health Technol Inform. 2018;247:181–185.
Google Scholar | Medline28. Ingebrigtsen, T, Georgiou, A, Clay-Williams, R, et al. The impact of clinical leadership on health information technology adoption: Systematic review. Int J Med Inform. 2014;83(6):393–405. DOI: 10.1016/j.ijmedinf.2014.02.005
Google Scholar | Crossref | Medline29. Paré, G, Sicotte, C, Poba-Nzaou, P, et al. Clinicians’ perceptions of organizational readiness for change in the context of clinical information system projects: Insights from two cross-sectional surveys. Implement Sci. 2011;6(1):15–14.
Google Scholar | Crossref | Medline | ISI30. Tabachnick, BG, Fidell, LS. Using Multivariate Statistics. Boston, MA: Pearson Allyn and Bacon; 2007, 980.
Google Scholar31. R Core Team . R: A Language and Environment for Statistical Computing. Vienna, Austria: R Found Stat Comput Vienna. 2018.
Google Scholar32. Kyngäs, H . Inductive Content Analysis. In: Kyngäs, H, Mikkonen, K, Kääriäinen, M. (eds) The Application of Content Analysis in Nursing Science Research. New York, NY: Springer International Publishing, 2020.
Google Scholar | Crossref33. Chambers, D, Cantrell, A, Johnson, M, et al. Digital and online symptom checkers and assessment services for urgent care to inform a new digital platform: A systematic review. HS&DR 2019;7:29. DOI: 10.3310/hsdr07290
Google Scholar | Crossref34. Kujala, S, Hörhammer, I, Hänninen-Ervasti, R, et al. Health professionals’ experiences of the benefits and challenges of online symptom checkers. Stud Health Technol Inform. 2020;270:966–970.
Google Scholar | Medline35. Miller, DPJ, Latulipe, C, Melius, KA, et al. Primary care providers’ views of patient portals: Interview study of perceived benefits and consequences. J Med Internet Res. 2016;18:e8.
Google Scholar | Crossref | Medline36. Morse, KE, Ostberg, NP, Jones, VG, et al. Use characteristics and triage acuity of a digital symptom checker in a large integrated health system: Population-based descriptive study. J Med Internet Res. 2020;22(11):e20549.
Google Scholar | Crossref | Medline37. Mackert, M, Mabry-flynn, A, Champlin, S, et al. Health literacy and health information technology adoption: The potential for a new digital divide. J Med Interner Res. 2016;18(10):e264.
Google Scholar | Crossref | Medline38. Bodie, GD, Dutta, MJ. Understanding health literacy for strategic health marketing: eHealth literacy, health disparities, and the digital divide. Health Mark Q. 2008;25(1–2):175–203.
Google Scholar | Crossref | Medline39. Kyngäs, H, Kääriäinen, M, Elo, S. The trustworthiness of content analysis. In: Kyngäs, H, Mikkonen, K, Kääriäinen, M. (eds) The Application of Concent Analysis in Nursing Science Research. Cham: Springer, 2020. 41–48.
Google Scholar | Crossref