SERIES: eHealth in primary care. Part 1: Concepts, conditions and challenges

References

• Rimmer A. Doctors call for cap on GP workload. BMJ. 2018;361:k2810.
   PubMedGoogle Scholar
• Fisher RF, Croxson CH, Ashdown HF, et al. GP views on strategies to cope with increasing workload: a qualitative interview study. Br J Gen Pract. 2017;67:e148.
   PubMed Web of Science ®Google Scholar
• Practitioners RCoG. Over 500 surgeries at risk of closure as GP workforce crisis deepens. 2014 [cited 2019 Aug 8]. Available from: https://www.bjfm.co.uk/over-500-surgeries-at-risk-of-closure-as-gp-workforce-crisis-deepens
   Google Scholar
• Reeves D, Pye S, Ashcroft D, et al. The challenge of ageing populations and frail people: can primary care adapt? Br Med J. 2018;362:k3349.
   PubMedGoogle Scholar
• Cassell A, Edwards D, Harshfield A, et al. The epidemiology of multimorbidity in primary care: a retrospective cohort study. Br J Gen Pract. 2018;68:e245–e251.
   PubMed Web of Science ®Google Scholar
• Tan SS-L, Goonawardene N. Internet health information seeking and the patient–physician relationship: a systematic review. J Med Internet Res. 2017;19:e9.
   PubMed Web of Science ®Google Scholar
• England N. Next steps on the NHS five year forward view. London (UK): NHS; 2017 [cited 2019 Aug 8]. Available from: https://www.england.nhs.uk/publication/next-steps-on-the-nhs-five-year-forward-view/
   Google Scholar
• Morrison C, Rooney L. Personalised health and care 2020: using data and technology to transform outcomes for patients and citizens. London (Uk): NHS; 2017 [cited 2019 Aug 8]. Available from: https://www.gov.uk/government/publications/personalised-health-and-care-2020
   Google Scholar
• WHO. Global diffusion of eHealth: making universal health coverage achievable. Report of the third global survey on eHealth. Geneva (Switzerland): World Health Organization; 2016 [cited 2019 Aug 8]. (License: CC BY-NC-SA 3.0 IGO). Available from: https://www.who.int/goe/publications/global_diffusion/en/
   Google Scholar
• Boogerd EA, Arts T, Engelen LJ, et al. “What is eHealth”: time for an update? JMIR Res Protoc. 2015;4:e29.
   PubMed Web of Science ®Google Scholar
• Eysenbach G. What is e-health? J Med Internet Res. 2001;3:e20.
   PubMed Web of Science ®Google Scholar
• Clegg A, Bates C, Young J, et al. Development and validation of an electronic frailty index using routine primary care electronic health record data. Age Ageing. 2016;45:353–360.
   PubMed Web of Science ®Google Scholar
• Shaw T, McGregor D, Brunner M, et al. What is eHealth (6)? Development of a conceptual model for eHealth: qualitative study with key informants. J Med Internet Res. 2017;19:e324.
   PubMed Web of Science ®Google Scholar
• Vijayakrishnan R, Steinhubl SR, Ng K, et al. Prevalence of heart failure signs and symptoms in a large primary care population identified through the use of text and data mining of the electronic health record. J Card Fail. 2014;20:459–464.
   PubMed Web of Science ®Google Scholar
• Wild SH, Hanley J, Lewis SC, et al. Supported telemonitoring and glycemic control in people with type 2 diabetes: the telescot diabetes pragmatic multicenter randomized controlled trial. Plos Med. 2016;13:e1002098.
   PubMed Web of Science ®Google Scholar
• Granja C, Janssen W, Johansen MA. Factors determining the success and failure of eHealth interventions: systematic review of the literature. J Med Internet Res. 2018;20:e10235.
   PubMed Web of Science ®Google Scholar
• Research2guidance [Internet]. Berlin (Germany): Research2guidance. [cited 2019 May 9]. Available from: http://www.uzelf.org/wp-content/uploads/2017/12/R2G-mHealth-Developer-Economics-2017-Status-And-Trends.pdf
   Google Scholar
• Ahmed B, Dannhauser T, Philip N. A systematic review of reviews to identify key research opportunities within the field of eHealth implementation. J Telemed Telecare. 2019;25:276–285.
   PubMed Web of Science ®Google Scholar
• Huckvale K, Prieto JT, Tilney M, et al. Unaddressed privacy risks in accredited health and wellness apps: a cross-sectional systematic assessment. BMC Med. 2015;13:214.
   PubMed Web of Science ®Google Scholar
• Huckvale K, Morrison C, Ouyang J, et al. The evolution of mobile apps for asthma: an updated systematic assessment of content and tools. BMC Med. 2015;13:58.
   PubMed Web of Science ®Google Scholar
• EU monitor [Internet]. Brussels (Belgium): EU Monitor. [cited 2019 Feb 8]. Available from: https://ec.europa.eu/digital-single-market/en/news/communication-enabling-digital-transformation-health-and-care-digital-single-market-empowering
   Google Scholar
• Department of health [Internet]. Dublin (Ireland): Government of Ireland. [cited 2019 Feb 8]. Available from: https://health.gov.ie/wp-content/uploads/2014/03/Ireland_eHealth_Strategy.pdf
   Google Scholar
• Bashshur RL, Howell JD, Krupinski EA, et al. The empirical foundations of telemedicine interventions in primary care. Telemed J E Health. 2016;22:342–375.
   PubMed Web of Science ®Google Scholar
• Flodgren G, Rachas A, Farmer AJ, et al. Interactive telemedicine: effects on professional practice and health care outcomes. Cochrane Database Syst Rev. 2015;9:Cd002098.
   Google Scholar
• Pinnock H, McKinstry B. Telehealth for chronic obstructive pulmonary disease: promises, populations, and personalized care. Am J Respir Crit Care Med. 2018;198:552–554.
   PubMed Web of Science ®Google Scholar
• Ho T-W, Huang C-T, Chiu H-C, et al. Effectiveness of telemonitoring in patients with chronic obstructive pulmonary disease in Taiwan—-a randomized controlled trial. Sci Rep. 2016;6:23797.
   PubMed Web of Science ®Google Scholar
• McMillan B, Hickey E, Mitchell C, et al. The need for quality assurance of health apps. Br Med J. 2015;351:h5915.
   PubMedGoogle Scholar
• Wouters M, Swinkels I, Sinnige J, et al. Kies bewust voor eHealth: eHealth-monitor 2017. Den Haag en Utrecht (Netherlands): Nictiz en Nivel; 2017 [cited 2019 Aug 8]. Available from: https://www.nivel.nl/en/publicatie/kies-bewust-voor-ehealth-ehealth-monitor-2017
   Google Scholar
• Peeters JM, Krijgsman JW, Brabers AE, et al. Use and uptake of ehealth in general practice: a cross-sectional survey and focus group study among health care users and general practitioners. JMIR Med Inform. 2016;4:e11.
   PubMed Web of Science ®Google Scholar
• van Gemert-Pijnen J, Nijland N, van Limburg M, et al. A holistic framework to improve the uptake and impact of ehealth technologies. J Med Internet Res. 2011;13:e111.
   PubMed Web of Science ®Google Scholar
• Dedehayir O, Steinert M. The hype cycle model: a review and future directions. Technol Forecast Soc Change. 2016;108:28–41.
   Web of Science ®Google Scholar
• van Limburg M, Wentzel J, Sanderman R, et al. Business modeling to implement an eHealth portal for infection control: a reflection on co-creation with stakeholders. JMIR Res Protoc. 2015;4:e104.
   PubMed Web of Science ®Google Scholar
• Kip H van Gemert-Pijnen L, et al.. Holistic development of eHealth technology In: Van Gemert-Pijnen L, Kelders S, Kip H, editors. eHealth research, theory and development. London (UK): Routledge; 2018. A Multi-Disciplinary Approach. London: Routledge; p. 131–166.
   Google Scholar
• van Limburg M, van Gemert-Pijnen E, Nijland N, et al. Why business modeling is crucial in the development of eHealth technologies. J Med Internet Res. 2011;13:e124.
   PubMed Web of Science ®Google Scholar
• Beerlage-de Jong N, van Gemert-Pijnen L, Wentzel J, et al. Technology to support integrated antimicrobial stewardship programs: a user centered and stakeholder driven development approach. Infect Dis Rep. 2017;30:6829.
   Google Scholar
• Greenhalgh T. Role of routines in collaborative work in healthcare organisations. BMJ. 2008;337:a2448
   PubMedGoogle Scholar
• Nijland N. Grounding eHealth: towards a holistic framework for sustainable eHealth technologies [dissertation]. Enschede (Netherlands): Universiteit Twente; 2011 [cited 2019 Aug 8]. Available from: https://research.utwente.nl/en/publications/grounding-ehealth-towards-a-holistic-framework-for-sustainable-eh
   Google Scholar
• Bernhard G, Mahler C, Seidling HM, et al. Developing a shared patient-centered, web-based medication platform for type 2 diabetes patients and their health care providers: qualitative study on user requirements. J Med Internet Res. 2018;20:e105.
   PubMed Web of Science ®Google Scholar
• Zeylemaker MM, Linn FH, Vermetten E. Blended care; development of a day treatment program for medically unexplained physical symptoms (MUPS) in the Dutch Armed Forces. Work. 2015;1:111–120.
   Google Scholar
• Andersson G, Cuijpers P. Internet-based and other computerized psychological treatments for adult depression: a meta-analysis. Cogn Behav Ther. 2009;38:196–205.
   PubMedGoogle Scholar
• Richards D, Richardson T. Computer-based psychological treatments for depression: a systematic review and meta-analysis. Clin Psychol Rev. 2012;32:329–342.
   PubMed Web of Science ®Google Scholar
• Talboom-Kamp EP, Verdijk NA, Kasteleyn MJ, et al. From chronic disease management to person-centered eHealth; a review on the necessity for blended care. Clinical eHealth. 2018;1:3–7.
   Google Scholar
• Kouwenhoven-Pasmooij TA, Robroek SJ, Kraaijenhagen RA, et al. Effectiveness of the blended-care lifestyle intervention 'PerfectFit': a cluster randomised trial in employees at risk for cardiovascular diseases. BMC Public Health. 2018;18:766.
   PubMed Web of Science ®Google Scholar
• Spoelman WA, Bonten TN, de Waal MWM, et al. Effect of an evidence-based website on healthcare usage: an interrupted time-series study. BMJ Open. 2016;6:e013166.
   PubMed Web of Science ®Google Scholar
• Kaptein M, Markopoulos P, De Ruyter B, et al. Personalizing persuasive technologies: explicit and implicit personalization using persuasion profiles. Int J Hum Comput Stud. 2015;77:38–51.
   Web of Science ®Google Scholar
• Bousquet J, Chavannes NH, Guldemond N, et al. Realising the potential of mHealth to improve asthma and allergy care: how to shape the future. Eur Respir J. 2017;49:1700447.
   PubMed Web of Science ®Google Scholar
• Holzinger A. Trends in interactive knowledge discovery for personalized medicine: cognitive science meets machine learning. IEEE Intell Inform Bull. 2014;15:6–14.
   Google Scholar
• Dilsizian SE, Siegel EL. Artificial intelligence in medicine and cardiac imaging: harnessing big data and advanced computing to provide personalized medical diagnosis and treatment. Curr Car Rep. 2014;16:441.
   PubMed Web of Science ®Google Scholar
• Menden MP, Iorio F, Garnett M, et al. Machine learning prediction of cancer cell sensitivity to drugs based on genomic and chemical properties. PLoS One. 2013;8:e61318.
   PubMed Web of Science ®Google Scholar
• Zeevi D, Korem T, Zmora N, et al. Personalized nutrition by prediction of glycemic responses. Cell. 2015;163:1079–1094.
   PubMed Web of Science ®Google Scholar
• Pinnock H, Steed L, Jordan R. Supported self-management for COPD: making progress, but there are still challenges. Eur Respir J. 2016;48:6–9.
   PubMed Web of Science ®Google Scholar
• Orchard P, Agakova A, Pinnock H, et al. Improving prediction of risk of hospital admission in chronic obstructive pulmonary disease: application of machine learning to telemonitoring data. J Med Internet Res. 2018;20:e263.
   PubMed Web of Science ®Google Scholar
• Latulippe K, Hamel C, Giroux D. Social health inequalities and eHealth: a literature review with qualitative synthesis of theoretical and empirical studies. J Med Internet Res. 2017;19:e136.
   PubMedGoogle Scholar
• Bodie GD, Dutta MJ. Understanding health literacy for strategic health marketing: eHealth literacy, health disparities, and the digital divide. Health Mark Q. 2008;25:175–203.
   PubMedGoogle Scholar
• Chib A, van Velthoven MH, Car J. mHealth adoption in low-resource environments: a review of the use of mobile healthcare in developing countries. J Health Commun. 2015;20:4–34.
   PubMed Web of Science ®Google Scholar
• WHO [Internet]. Geneva (Switzerland): World Health Organization. [cited 2019 Feb 14]. Available from: http://apps.who.int/gho/data/node.main.A1444?lang=en&showonly=HWF
   Google Scholar
• James SL, Abate D, Abate KH, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392:1789–1858.
   PubMed Web of Science ®Google Scholar
• Beratarrechea A, Lee AG, Willner JM, et al. The impact of mobile health interventions on chronic disease outcomes in developing countries: a systematic review. Telemed J E Health. 2014;20:75–82.
   PubMed Web of Science ®Google Scholar
• Bloomfield GS, Vedanthan R, Vasudevan L, et al. Mobile health for non-communicable diseases in Sub-Saharan Africa: a systematic review of the literature and strategic framework for research. Global Health. 2014;10:49.
   PubMed Web of Science ®Google Scholar
• Peiris D, Praveen D, Johnson C, et al. Use of mHealth systems and tools for non-communicable diseases in low-and middle-income countries: a systematic review. J Cardiovasc Trans Res. 2014;7:677–691.
   PubMed Web of Science ®Google Scholar
• Shariful Islam SM, Niessen LW, Ferrari U, et al. Effects of mobile phone SMS to improve glycemic control among patients with type 2 diabetes in Bangladesh: a prospective, parallel-group, randomized controlled trial. Dia Care. 2015;38:e112–113.
   PubMed Web of Science ®Google Scholar
• Xie X, Zhou W, Lin L, et al. Internet hospitals in China: cross-sectional survey. J Med Internet Res. 2017;19:e239.
   PubMed Web of Science ®Google Scholar
• Black AD, Car J, Pagliari C, et al. The impact of ehealth on the quality and safety of health care: a systematic overview. PLoS Med. 2011;8:e1000387
   PubMed Web of Science ®Google Scholar
• Jamaladin H, van de Belt TH, Luijpers LC, et al. Mobile apps for blood pressure monitoring: systematic search in app stores and content analysis. JMIR Mhealth Uhealth. 2018;6:e187.
   PubMed Web of Science ®Google Scholar
• Baker TB, Gustafson DH, Shah D. How can research keep up with eHealth? Ten strategies for increasing the timeliness and usefulness of ehealth research. J Med Internet Res. 2014;16:e36.
   PubMed Web of Science ®Google Scholar
• Glasgow RE, Phillips SM, Sanchez MA. Implementation science approaches for integrating eHealth research into practice and policy. Int J Med Inform. 2014;83:e1–e11.
   PubMed Web of Science ®Google Scholar
• Leviton LC, Khan LK, Rog D, et al. Evaluability assessment to improve public health policies, programs, and practices. Annu Rev Public Health. 2010;31:213–233.
   PubMed Web of Science ®Google Scholar
• Lillie EO, Patay B, Diamant J, et al. The n-of-1 clinical trial: the ultimate strategy for individualizing medicine? Per Med. 2011;8:161–173.
   PubMed Web of Science ®Google Scholar
• Campbell DT, Stanley JC. Experimental and quasi-experimental designs for research. Cambridge: Ravenio Books; 2015.
   Google Scholar
• Collins LM, Murphy SA, Strecher V. The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): new methods for more potent eHealth interventions. Am J Prev Med. 2007;32:S112–S118.
   PubMed Web of Science ®Google Scholar
• Kontopantelis E, Doran T, Springate DA, et al. Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis. Br Med J. 2015;350:h2750.
   PubMed Web of Science ®Google Scholar
• Lei H, Nahum-Shani I, Lynch K, et al. A ‘SMART’ design for building individualized treatment sequences. Annual review of clinical psychology. Annu Rev Clin Psychol. 2012;8:21–48.
   PubMed Web of Science ®Google Scholar
• Flynn D, Gregory P, Makki H, et al. Expectations and experiences of eHealth in primary care: a qualitative practice-based investigation. Int J Med Inform. 2009;78:588–604.
   PubMed Web of Science ®Google Scholar
• Ross J, Stevenson F, Lau R, et al. Factors that influence the implementation of e-health: a systematic review of systematic reviews (an update). Implement Sci. 2016;11:146.
   PubMed Web of Science ®Google Scholar
• Brockes C, Grischott T, Dutkiewicz M, et al. Evaluation of the education “Clinical Telemedicine/e-Health” in the curriculum of medical students at the University of Zurich. Telemed J E Health. 2017;23:899–904.
   PubMed Web of Science ®Google Scholar
• Fleming TM, De Beurs D, Khazaal Y, et al. Maximizing the impact of e-therapy and serious gaming: time for a paradigm shift. Front Psychiatry. 2016;7:65.
   PubMed Web of Science ®Google Scholar
• Shiyko M, Hallinan S, Seif El-Nasr M, et al. Effects of playing a serious computer game on body mass index and nutrition knowledge in women. JMIR Serious Games. 2016;4:e8.
   PubMed Web of Science ®Google Scholar
• Orr RD, Pang N, Pellegrino ED, et al. Use of the Hippocratic oath: a review of twentieth century practice and a content analysis of oaths administered in medical schools in the US and Canada in 1993. J Clin Ethics. 1997;8:377–388.
   PubMedGoogle Scholar
• Pussewalage HS, Oleshchuk VA. Privacy preserving mechanisms for enforcing security and privacy requirements in E-health solutions. Int J Inf Manage.. 2016;36:1161–1180. ​
   Web of Science ®Google Scholar
• Staffa M, Coppolino L, Sgaglione L, et al. KONFIDO: An OpenNCP-based secure eHealth data exchange system. Proceedings of the International ISCIS Security Workshop; 2018 Feb 26. Cham (Switzerland): Springer; 2018. p. 11–27.
   Google Scholar
• Gogia SB, Maeder A, Mars M, et al. Unintended consequences of tele health and their possible solutions: contribution of the IMIA working group on telehealth. Yearb Med Inform. 2016;10:41–46.
   Google Scholar
• Kim H, Xie B. Health literacy in the eHealth era: a systematic review of the literature. Patient Educ Couns. 2017;100:1073–1082.
   PubMed Web of Science ®Google Scholar
• Piette JD, Lun K, Moura LA, Jr, et al. Impacts of e-health on the outcomes of care in low-and middle-income countries: where do we go from here? Bull World Health Org. 2012;90:365–372.
   PubMed Web of Science ®Google Scholar
• Swinkels ICS, Huygens MWJ, Schoenmakers TM, et al. Lessons learned from a living lab on the broad adoption of eHealth in primary health care. J Med Internet Res. 2018;20:e83.
   PubMed Web of Science ®Google Scholar