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References

  1. Burden G, Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019: Update From the GBD 2019 Study. J Am Coll Cardiol. 2020; 76: 29823021.
  2. Abbafati C, Abbas KM, Abbasi-Kangevari M, Abd-Allah F, Abdelalim A, Abdollahi M, et al. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet. 2020; 396: 12231249. DOI: 10.1016/S0140-6736(20)30752-2
  3. Barber RM, Fullman N, Sorensen RJD, Bollyky T, McKee M, Nolte E, et al. Healthcare access and quality index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990–2015: A novel analysis from the global burden of disease study 2015. Lancet. 2017; 390: 231266. DOI: 10.1016/S0140-6736(17)30818-8
  4. Manne-Goehler J, Geldsetzer P, Agoudavi K, Andall-Brereton G, Aryal KK, Bicaba BW, et al. Health system performance for people withdiabetes in 28 low-and middle-incomecountries: A cross-sectional study of nationallyrepresentative surveys. PLoS Med. 2019; 16. DOI: 10.1371/journal.pmed.1002751
  5. Zhou B, Danaei G, Stevens GA, Bixby H, Taddei C, Carrillo-Larco RM, et al. Long-term and recent trends in hypertension awareness, treatment, and control in 12 high-income countries: an analysis of 123 nationally representative surveys. Lancet. 2019; 394: 639651. DOI: 10.1016/S0140-6736(19)31145-6
  6. World Health Organziation (WHO). Physicians (per 1,000 people). Data [Internet]. World Health Organization’s Global Health. Workforce. Statistics; 2016. (4 November 2021). Retrieved from http://data.worldbank.org/indicator/SH.MED.PHYS.ZS?locations=ZM%5Cnhttp://data.worldbank.org/indicator/SH.MED.PHYS.ZS.
  7. Battineni G, Sagaro GG, Chintalapudi N, Amenta F. The benefits of telemedicine in personalized prevention of cardiovascular diseases (CVD): A systematic review. J Pers Med. 2021; 11. DOI: 10.3390/jpm11070658
  8. Srinivasapura Venkateshmurthy N, Ajay VS, Mohan S, Jindal D, Anand S, Kondal D, et al. m-Power Heart Project – a nurse care coordinator led, mHealth enabled intervention to improve the management of hypertension in India: study protocol for a cluster randomized trial. Trials. 2018; 19(1): 19. DOI: 10.1186/s13063-018-2813-2
  9. Wilson D, Sheikh A, Görgens M, Ward K. Technology and Universal Health Coverage: Examining the role of digital health. J Glob Health. 2021; 11: 16006. DOI: 10.7189/jogh.11.16006
  10. Li R, Liang N, Bu F, Hesketh T. The effectiveness of self-management of hypertension in adults using mobile health: Systematic review and meta-analysis. JMIR mHealth uHealth. 2020; 8: e17776. DOI: 10.2196/17776
  11. Countdown N. NCD Countdown 2030: efficient pathways and strategic investments to accelerate progress towards the Sustainable Development Goal target 3.4 in low-income and middle-income countries. Lancet. 2022; 399: 12661278. DOI: 10.1016/S0140-6736(21)02347-3
  12. Frederix I, Caiani EG, Dendale P, Anker S, Bax J, Böhm A, et al. ESC e-Cardiology Working Group Position Paper: Overcoming challenges in digital health implementation in cardiovascular medicine. Eur J Prev Cardiol. 2019; 26: 11661177. DOI: 10.1177/2047487319832394
  13. Astley CM, Clarke RA, Cartledge S, Beleigoli A, Du H, Gallagher C, et al. Remote cardiac rehabilitation services and the digital divide: Implications for elderly populations during the COVID19 pandemic. Eur J Cardiovasc Nurs. 2021; 20: 521523. DOI: 10.1093/eurjcn/zvab034
  14. Lefevre AE, Shah N, Bashingwa JJH, George AS, Mohan Di. Does women’s mobile phone ownership matter for health? Evidence from 15 countries. BMJ Glob Heal. 2020; 5: e002524. DOI: 10.1136/bmjgh-2020-002524
  15. Pick JB, Azari R. Global digital divide: Influence of socioeconomic, governmental, and accessibility factors on information technology. Inf Technol Dev. 2008; 14: 91115. DOI: 10.1002/itdj.20095
  16. Whitelaw S, Pellegrini DM, Mamas MA, Cowie M, Van Spall HGC. Barriers and facilitators of the uptake of digital health technology in cardiovascular care: a systematic scoping review. Eur Hear J – Digit Heal. 2021; 2: 6274. DOI: 10.1093/ehjdh/ztab005
  17. Poole L, Ramasawmy M, Banerjee A. Digital first during the COVID-19 pandemic: does ethnicity matter? Lancet Public Health. 2021; 6: e628e630. DOI: 10.1016/S2468-2667(21)00186-9
  18. Redfern J, Coorey G, Mulley J, Scaria A, Neubeck L, Hafiz N, et al. A digital health intervention for cardiovascular disease management in primary care (CONNECT) randomized controlled trial. npj Digit Med. 2020; 3. DOI: 10.1038/s41746-020-00325-z
  19. Taniguchi D, LoGerfo J, Van Pelt M, Mielcarek B, Huster K, Haider M, et al. Evaluation of a multi-faceted diabetes care program including community-based peer educators in Takeo province, Cambodia, 2007–2013. PLoS One. 2017; 12. DOI: 10.1371/journal.pone.0181582
  20. Steinman L, van Pelt M, Hen H, Chhorvann C, Lan CS, Te V, et al. Can mHealth and eHealth improve management of diabetes and hypertension in a hard-to-reach population? —lessons learned from a process evaluation of digital health to support a peer educator model in Cambodia using the RE-AIM framework. mHealth. 2020; 6: 4040. DOI: 10.21037/mhealth-19-249
  21. Indraratna P, Biswas U, Liu H, Redmond SJ, Yu J, Lovell NH, et al. Process Evaluation of a Randomised Controlled Trial for TeleClinical Care, a Smartphone-App Based Model of Care. Front Med. 2022; 8: 3121. DOI: 10.3389/fmed.2021.780882
  22. Ferreira JP, Kraus S, Mitchell S, Perel P, Piñeiro D, Chioncel O, et al. World Heart Federation Roadmap for Heart Failure. Glob Heart. 2019; 14: 197214. DOI: 10.1016/j.gheart.2019.07.004
  23. Jeemon P, Séverin T, Amodeo C, Balabanova D, Campbell NRC, Gaita D, et al. World heart federation roadmap for hypertension – A 2021 update. Glob Heart. 2021; 16: 63. DOI: 10.5334/gh.1066
  24. Mitchell S, Malanda B, Damasceno A, Eckel RH, Gaita D, Kotseva K, et al. A Roadmap on the Prevention of Cardiovascular Disease Among People Living With Diabetes. Glob Heart. 2019; 14: 215240. DOI: 10.1016/j.gheart.2019.07.009
  25. Palafox B, Mocumbi AO, Kumar RK, Ali SKM, Kennedy E, Haileamlak A, et al. The WHF Roadmap for Reducing CV Morbidity and Mortality Through Prevention and Control of RHD. Glob Heart. 2017; 12: 4762. DOI: 10.1016/j.gheart.2016.12.001
  26. Grainger Gasser A, Welch C, Arora M, Greenland R, Bhatti L, Sanda L, et al. Reducing Cardiovascular Mortality Through Tobacco Control: A World Heart Federation Roadmap. Glob Heart. 2015; 10: 123133. DOI: 10.1016/j.gheart.2015.04.007
  27. Murphy A, Palafox B, O’Donnell O, Stuckler D, Perel P, AlHabib KF, et al. Inequalities in the use of secondary prevention of cardiovascular disease by socioeconomic status: evidence from the PURE observational study. Lancet Glob Heal. 2018; 6: e292e301. DOI: 10.1016/S2214-109X(18)30031-7
  28. Freedman B, Hindricks G, Banerjee A, Baranchuk A, Ching CK, Du X, et al. World Heart Federation Roadmap on Atrial Fibrillation – A 2020 Update. Glob Heart. 2021; 16: 41. DOI: 10.5334/gh.1023
  29. World Health Organization. WHO classification of digital health interventions (DHIs). Res Impact. 2018; 1: 1218.
  30. Administration UF and D. Guidances with Digital Health Content [Internet]. US Food Drug Adm; 2020. (4 November 2021); Retrieved from https://www.fda.gov/medical-devices/digital-health-center-excellence/guidances-digital-health-content.
  31. Gerke S, Stern AD, Minssen T. Germany’s digital health reforms in the COVID-19 era: lessons and opportunities for other countries. NPJ Digit Med. 2020; 3: 16. DOI: 10.1038/s41746-020-0306-7
  32. Herrmann M, Boehme P, Mondritzki T, Ehlers JP, Kavadias S, Truebel H. Digital transformation and disruption of the health care sector: Internet-based observational study. J Med Internet Res. 2018; 20. DOI: 10.2196/jmir.9498
  33. Whittaker R, Mcrobbie H, Bullen C, Rodgers A, Gu Y. Mobile phone-based interventions for smoking cessation. Cochrane Database Syst Rev; 2016. DOI: 10.1002/14651858.CD006611.pub4
  34. Shariful Islam SM, Farmer AJ, Bobrow K, Maddison R, Whittaker R, Pfaeffli Dale LA, et al. Mobile phone text-messaging interventions aimed to prevent cardiovascular diseases (Text2PreventCVD): Systematic review and individual patient data meta-analysis. Open Hear. 2019; 6. DOI: 10.1136/openhrt-2019-001017
  35. Kario K, Nomura A, Harada N, Okura A, Nakagawa K, Tanigawa T, et al. Efficacy of a digital therapeutics system in the management of essential hypertension: The HERB-DH1 pivotal trial. Eur Heart J. 2021; 42: 41114122. DOI: 10.1093/eurheartj/ehab559
  36. Santo K, Chow CK, Thiagalingam A, Rogers K, Chalmers J, Redfern J. MEDication reminder APPs to improve medication adherence in Coronary Heart Disease (MedApp-CHD) Study: A randomised controlled trial protocol. BMJ Open. 2017; 7. DOI: 10.1136/bmjopen-2017-017540
  37. Peiris D, Usherwood T, Panaretto K, Harris M, Hunt J, Redfern J, et al. Effect of a computer-guided, quality improvement program for cardiovascular disease risk management in primary health care: The treatment of cardiovascular risk using electronic decision support cluster-randomized trial. Circ Cardiovasc Qual Outcomes. 2015; 8: 8795. DOI: 10.1161/CIRCOUTCOMES.114.001235
  38. Smith DM, Duque L, Huffman JC, Healy BC, Celano CM. Text Message Interventions for Physical Activity: A Systematic Review and Meta-Analysis. Am J Prev Med. 2020; 58: 142151. DOI: 10.1016/j.amepre.2019.08.014
  39. Skinner R, Gonet V, Currie S, Hoddinott P, Dombrowski SU. A systematic review with meta-analyses of text message-delivered behaviour change interventions for weight loss and weight loss maintenance. Obes Rev. 2020; 21: e12999. DOI: 10.1111/obr.12999
  40. Adler AJ, Martin N, Mariani J, Tajer CD, Owolabi OO, Free C, et al. Mobile phone text messaging to improve medication adherence in secondary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2017; 2017. DOI: 10.1002/14651858.CD011851.pub2
  41. Thakkar J, Kurup R, Laba TL, Santo K, Thiagalingam A, Rodgers A, et al. Mobile telephone text messaging for medication adherence in chronic disease a meta-analysis. JAMA Intern Med. 2016; 176: 340349. DOI: 10.1001/jamainternmed.2015.7667
  42. Chow CK, Redfern J, Hillis GS, Thakkar J, Santo K, Hackett ML, et al. Effect of lifestyle-focused text messaging on risk factor modification in patients with coronary heart disease: A randomized clinical trial. JAMA – J Am Med Assoc. 2015; 314: 12551263. DOI: 10.1001/jama.2015.10945
  43. Redfern J, Thiagalingam A, Jan S, Whittaker R, Hackett ML, Mooney J, et al. Development of a set of mobile phone text messages designed for prevention of recurrent cardiovascular events. Eur J Prev Cardiol. 2014; 21: 492499. DOI: 10.1177/2047487312449416
  44. Coorey GM, Neubeck L, Mulley J, Redfern J. Effectiveness, acceptability and usefulness of mobile applications for cardiovascular disease self-management: Systematic review with meta-synthesis of quantitative and qualitative data. Eur J Prev Cardiol. 2018; 25: 505521. DOI: 10.1177/2047487317750913
  45. Merriel SWD, Andrews V, Salisbury C. Telehealth interventions for primary prevention of cardiovascular disease: A systematic review and meta-analysis. Prev Med (Baltim). 2014; 64: 8895. DOI: 10.1016/j.ypmed.2014.04.001
  46. Jin K, Khonsari S, Gallagher R, Gallagher P, Clark AM, Freedman B, et al. Telehealth interventions for the secondary prevention of coronary heart disease: A systematic review and meta-analysis. Eur J Cardiovasc Nurs. 2019; 18: 260271. DOI: 10.1177/1474515119826510
  47. Rawstorn JC, Gant N, Direito A, Beckmann C, Maddison R. Telehealth exercise-based cardiac rehabilitation: A systematic review and meta-analysis. Heart. 2016; 102: 11831192. DOI: 10.1136/heartjnl-2015-308966
  48. Chokshi NP, Adusumalli S, Small DS, Morris A, Feingold J, Ha YP, et al. Loss-framed financial incentives and personalized goal-setting to increase physical activity among ischemic heart disease patients using wearable devices: The ACTIVE REWARD randomized trial. J Am Heart Assoc. 2018; 7. DOI: 10.1161/JAHA.118.009173
  49. Bayoumy K, Gaber M, Elshafeey A, Mhaimeed O, Dineen EH, Marvel FA, et al. Smart wearable devices in cardiovascular care: where we are and how to move forward. Nat Rev Cardiol. 2021; 18: 581599. DOI: 10.1038/s41569-021-00522-7
  50. Brickwood KJ, Watson G, O’brien J, Williams AD. Consumer-based wearable activity trackers increase physical activity participation: Systematic review and meta-analysis. JMIR mHealth uHealth. 2019; 7. DOI: 10.2196/11819
  51. Tromp J, Seekings PJ, Hung C-L, Iversen MB, Frost MJ, Ouwerkerk W, et al. Automated interpretation of systolic and diastolic function on the echocardiogram: a multicohort study. Lancet Digit Heal. 2021; Accepted. DOI: 10.1016/S2589-7500(21)00235-1
  52. Ghazi L, Yamamoto Y, Riello RJ, Coronel-Moreno C, Martin M, O’Connor KD, et al. Electronic Alerts to Improve Heart Failure Therapy in Outpatient Practice: A Cluster Randomized Trial. J Am Coll Cardiol; 2022. DOI: 10.1016/j.jacc.2022.03.338
  53. Neubeck L, Lowres N, Benjamin EJ, Freedman SB, Coorey G, Redfern J. The mobile revolution-using smartphone apps to prevent cardiovascular disease. Nat Rev Cardiol. 2015; 12: 350360. DOI: 10.1038/nrcardio.2015.34
  54. Steinhubl SR, Waalen J, Edwards AM, Ariniello LM, Mehta RR, Ebner GS, et al. Effect of a home-Based wearable continuous ECG monitoring patch on detection of undiagnosed atrial fibrillation the mSToPS randomized clinical trial. JAMA – J Am Med Assoc. 2018; 320: 146155. DOI: 10.1001/jama.2018.8102
  55. Perez MV, Mahaffey KW, Hedlin H, Rumsfeld JS, Garcia A, Ferris T, et al. Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation. N Engl J Med. 2019; 381: 19091917. DOI: 10.1056/NEJMoa1901183
  56. Banerjee A. Big is not always beautiful: the Apple Heart Study – Catalog of Bias [Internet]. (1 July 2022); Retrieved from: https://catalogofbias.org/2019/11/14/big-is-not-always-beautiful-the-apple-heart-study/.
  57. Expert Training Tool [Internet]. [cited 2022 Apr 12]; Retrieved from: https://www.escardio.org/Education/Practice-Tools/CVD-prevention-toolbox/expert-tool.
  58. Ouyang D, He B, Ghorbani A, Yuan N, Ebinger J, Langlotz CP, et al. Video-based AI for beat-to-beat assessment of cardiac function. Nature. 2020; 580: 252256. DOI: 10.1038/s41586-020-2145-8
  59. Zhang J, Gajjala S, Agrawal P, Tison GH, Hallock LA, Beussink-Nelson L, et al. Fully automated echocardiogram interpretation in clinical practice: Feasibility and diagnostic accuracy. Circulation. 2018; 138: 16231635. DOI: 10.1161/CIRCULATIONAHA.118.034338
  60. World Health Organzation (WHO) guideline. Recommendations on digital interventions for health system strengthening. World Health Organization; 2019.
  61. World Health Organzation (WHO). National eHealth Strategy Toolkit Overview. World Heal Organ Int Telecommun Union. 2012; 9.
  62. Chowdhury SR, Sunna TC, Ahmed S. Telemedicine is an important aspect of healthcare services amid COVID-19 outbreak: Its barriers in Bangladesh and strategies to overcome. Int J Health Plann Manage. 2021; 36: 412. DOI: 10.1002/hpm.3064
  63. Duggal R, Brindle I, Bagenal J. Digital healthcare: Regulating the revolution. BMJ. 2018; 360. DOI: 10.1136/bmj.k6
  64. Topol EJ. High-performance medicine: the convergence of human and artificial intelligence. Nat. Med. 2019; 25: 4456. DOI: 10.1038/s41591-018-0300-7
  65. World Health Organization. mHealth: new horizons for health through mobile technologies: second global survey on eHealth [Internet]; 2011. (3 May 2022); 3: 1102. Retrieved from http://apps.who.int/iris/handle/10665/44607.
  66. Guo C, Ashrafian H, Ghafur S, Fontana G, Gardner C, Prime M. Challenges for the evaluation of digital health solutions—A call for innovative evidence generation approaches. NPJ Digit Med. 2020; 3: 114. DOI: 10.1038/s41746-020-00314-2
  67. Nagendran M, Chen Y, Lovejoy CA, Gordon AC, Komorowski M, Harvey H, et al. Artificial intelligence versus clinicians: Systematic review of design, reporting standards, and claims of deep learning studies in medical imaging. BMJ. 2020; 368. DOI: 10.1136/bmj.m689
  68. Skivington K, Matthews L, Simpson SA, Craig P, Baird J, Blazeby JM, et al. A new framework for developing and evaluating complex interventions: Update of Medical Research Council guidance. BMJ. 2021; 374. DOI: 10.1136/bmj.n2061
  69. Rajkomar A, Hardt M, Howell MD, Corrado G, Chin MH. Ensuring fairness in machine learning to advance health equity. Ann Intern Med. 2018; 169: 866872. DOI: 10.7326/M18-1990
  70. Agarwal S, Lefevre AE, Lee J, L’engle K, Mehl G, Sinha C, et al. Guidelines for reporting of health interventions using mobile phones: Mobile health (mHealth) Evidence reporting and assessment (mERA) checklist. BMJ. 2016; 352. DOI: 10.1136/bmj.i1174
  71. World Health Organization. Monitoring and evaluating digital health interventions. A practical guide to conducting research and assessment [Internet]. WHO. 2016 (12 April 2022); 1144. Retrieved from https://www.who.int/reproductivehealth/publications/mhealth/digital-health-interventions/en/%0Ahttp://www.who.int/reproductivehealth/publications/mhealth/digital-health-interventions/en/.
  72. NICE. Evidence standards framework for digital health technologies [Internet]. 2019 (17 May 2022); Retrieved from https://www.nice.org.uk/about/what-we-do/our-programmes/evidence-standards-framework-for-digital-health-technologies.
  73. Prabhakaran D, Jha D, Prieto-Merino D, Roy A, Singh K, Ajay VS, et al. Effectiveness of an mHealth-Based Electronic Decision Support System for Integrated Management of Chronic Conditions in Primary Care: The mWellcare Cluster-Randomized Controlled Trial. Circulation. 2019; 139: 380391. DOI: 10.1161/CIRCULATIONAHA.118.038192
  74. Glasgow RE, Harden SM, Gaglio B, Rabin B, Smith ML, Porter GC, et al. RE-AIM planning and evaluation framework: Adapting to new science and practice with a 20-year review. Front Public Heal. 2019; 7: 64. DOI: 10.3389/fpubh.2019.00064
  75. Carolan JE, McGonigle J, Dennis A, Lorgelly P, Banerjee A. Technology-Enabled, Evidence-Driven, and Patient-Centered: The Way Forward for Regulating Software as a Medical Device. JMIR Med Informatics. 2022; 10: e34038. DOI: 10.2196/34038
  76. US Food and Drug Administration. Artificial Intelligence and Machine Learning in Software as a Medical Device [Internet]. 2019 [cited 2022 Jul 4]; 120. Retrieved from: https://www.fda.gov/downloads/medicaldevices/deviceregulationandguidance/guidancedocuments/ucm514737.pdf.
  77. Li Y. Empirical studies on online information privacy concerns: Literature review and an integrative framework. Commun Assoc Inf Syst. 2011; 28: 453496. DOI: 10.17705/1CAIS.02828
  78. Fischer SH, David D, Crotty BH, Dierks M, Safran C. Acceptance and use of health information technology by community-dwelling elders. Int J Med Inform. 2014; 83: 624635. DOI: 10.1016/j.ijmedinf.2014.06.005
  79. Fox G, Connolly R. Mobile health technology adoption across generations: Narrowing the digital divide. Inf Syst J. 2018; 28: 9951019. DOI: 10.1111/isj.12179
  80. Dhagarra D, Goswami M, Kumar G. Impact of Trust and Privacy Concerns on Technology Acceptance in Healthcare: An Indian Perspective. Int J Med Inform. 2020; 141: 104164. DOI: 10.1016/j.ijmedinf.2020.104164
  81. Ramdani B, Duan B, Berrou I. Exploring the determinants of mobile health adoption by hospitals in China: Empirical study. JMIR Med Informatics. 2020; 8. DOI: 10.2196/14795
  82. van Olmen J, Erwin E, García-Ulloa AC, Meessen B, Miranda JJ, Bobrow K, et al. Implementation barriers for mHealth for non-communicable diseases management in low and middle income countries: a scoping review and field-based views from implementers. Wellcome Open Res. 2020; 5. DOI: 10.12688/wellcomeopenres.15581.2
  83. Leigh S, Ashall-Payne L, Andrews T. Barriers and Facilitators to the Adoption of Mobile Health among Health Care Professionals from the United Kingdom: Discrete Choice Experiment. JMIR mHealth uHealth. 2020; 8: e17704. DOI: 10.2196/17704
  84. Tiffin N, George A, Lefevre AE. How to use relevant data for maximal benefit with minimal risk: Digital health data governance to protect vulnerable populations in low-income and middle-income countries. BMJ Glob Heal. 2019; 4: e001395. DOI: 10.1136/bmjgh-2019-001395
  85. GPDR.eu. General Data Protection Regulation (GDPR) Compliance Guidelines [Internet]. Gpdr.Eu.; 2020. (13 April 2022); Retrieved from https://gdpr.eu/.
  86. Vazirani AA, O’Donoghue O, Brindley D, Meinert E. Blockchain vehicles for efficient Medical Record management. npj Digit Med. 2020; 3: 15. DOI: 10.1038/s41746-019-0211-0
  87. Gagnon MP, Desmartis M, Labrecque M, Car J, Pagliari C, Pluye P, et al. Systematic review of factors influencing the adoption of information and communication technologies by healthcare professionals. J Med Syst. 2012; 36: 241277. DOI: 10.1007/s10916-010-9473-4
  88. Palacholla RS, Fischer N, Coleman A, Agboola S, Kirley K, Felsted J, et al. Provider- and Patient-Related Barriers to and Facilitators of Digital Health Technology Adoption for Hypertension Management: Scoping Review. JMIR Cardio. 2019; 3. DOI: 10.2196/11951
  89. Broadband Commission Working Group on Digital Health. The Promise of Digital Health: Addressing Non-communicable Diseases to Accelerate Universal Health Coverage in LMICs [Internet]; 2018. (3 May 2022); 1150. Retrieved from https://broadbandcommission.org/Documents/publications/DigitalHealthReport2018.pdf.
  90. Wilson K, Gertz B, Arenth B, Salisbury N. The Journey to Scale: Moving Together Past Digital Health Pilots; 2014.
  91. Kiberu VM, Mars M, Scott RE. Barriers and opportunities to implementation of sustainable e-Health programmes in Uganda: A literature review. African J Prim Heal Care Fam Med. 2017; 9. DOI: 10.4102/phcfm.v9i1.1277
  92. Labrique AB, Wadhwani C, Williams KA, Lamptey P, Hesp C, Luk R, et al. Best practices in scaling digital health in low and middle income countries. Global Health. 2018; 14: 18. DOI: 10.1186/s12992-018-0424-z
  93. Blandford A, Wesson J, Amalberti R, AlHazme R, Allwihan R. Opportunities and challenges for telehealth within, and beyond, a pandemic. Lancet Glob Heal. 2020; 8: e1364e1365. DOI: 10.1016/S2214-109X(20)30362-4
  94. Chen M, Said NM, Rais NCM, Ho F, Ling N, Chun M, et al. Remaining agile in the COVID-19 pandemic healthcare landscape – How we adopted a hybrid telemedicine geriatric oncology care model in an academic tertiary cancer center. J Geriatr Oncol; 2022. DOI: 10.1016/j.jgo.2022.04.006
  95. Taylor A, Caffery LJ, Gesesew HA, King A, Bassal AR, Ford K, et al. How Australian Health Care Services Adapted to Telehealth During the COVID-19 Pandemic: A Survey of Telehealth Professionals. Front Public Heal. 2021; 9: 121. DOI: 10.3389/fpubh.2021.648009
  96. Desveaux L, Soobiah C, Bhatia RS, Shaw J. Identifying and overcoming policy-level barriers to the implementation of digital health innovation: Qualitative study. J Med Internet Res. 2019; 21: e14994. DOI: 10.2196/14994
  97. Zahabi M, Kaber DB, Swangnetr M. Usability and Safety in Electronic Medical Records Interface Design: A Review of Recent Literature and Guideline Formulation. Hum Factors. 2015; 57: 805834. DOI: 10.1177/0018720815576827
  98. Wilson J, Heinsch M, Betts D, Booth D, Kay-Lambkin F. Barriers and facilitators to the use of e-health by older adults: a scoping review. BMC Public Health. 2021; 21. DOI: 10.1186/s12889-021-11623-w
  99. Savigny D, Adam T. Systems thinking for health systems strengthening. Alliance for Health Policy and Systems Research & World Health Organization; 2009.
  100. Fort MP, Mundo W, Paniagua-Avila A, Cardona S, Figueroa JC, Hernández-Galdamez D, et al. Hypertension in Guatemala’s Public Primary Care System: A Needs Assessment Using the Health System Building Blocks Framework. BMC Health Serv Res. 2021; 21: 114. DOI: 10.1186/s12913-021-06889-0
  101. World Health Organization. Monitoring the Building Blocks of Health Systems: a Handbook of Indicators and Their Measurement Strategies [Internet]. World Heal Organization; 2010. (29 April 2022); 35: 192. Retrieved from http://www.annualreviews.org/doi/10.1146/annurev.ecolsys.35.021103.105711
  102. Saparamadu AADNS, Fernando P, Zeng P, Teo H, Goh A, Lee JMY, et al. User-centered design process of an mHealth app for health professionals: Case study. JMIR mHealth uHealth. 2021; 9. DOI: 10.2196/18079
  103. Mathews SC, McShea MJ, Hanley CL, Ravitz A, Labrique AB, Cohen AB. Digital health: a path to validation. NPJ Digit Med. 2019; 2: 19. DOI: 10.1038/s41746-019-0111-3
  104. W3C Web Accessibility Initiative (www.w3.org). Notes on User Centered Design Process – https://www.w3.org/WAI/redesign/ucd [Internet]. (3 May 2022); Retrieved from https://www.w3.org/WAI/redesign/ucd.
  105. 9241-210 ISO. Ergonomics of human-system interaction — Part 210: Human-centred design for interactive systems [Internet]. Int. Stand.; 2019. (3 May 2022); 2: 133. Retrieved from https://www.iso.org/standard/77520.html.
  106. Hilbert M. The end justifies the definition: The manifold outlooks on the digital divide and their practical usefulness for policy-making. Telecomm Policy. 2011; 35: 715736. DOI: 10.1016/j.telpol.2011.06.012
  107. ITU. Measuring digital development. Facts and figures 2020 [Internet]. ITU Publ.; 2020. (3 May 2022); 115. Retreived from https://www.itu.int/en/mediacentre/Documents/MediaRelations/ITU Facts and Figures 2019 – Embargoed 5 November 1200 CET.pdf
  108. Makri A. Bridging the digital divide in health care. Lancet Digit Heal. 2019; 1: e204e205. DOI: 10.1016/S2589-7500(19)30111-6
  109. Okediran OO, Sijuade AA, Wahab WB, Oladimeji AI. A Framework for a Cloud-Based Electronic Health Records System for Developing Countries. 2nd Int Conf Electr Commun Comput Eng ICECCE 2020; 2020. DOI: 10.1109/ICECCE49384.2020.9179276
  110. World Health Organization (WHO). Atlas of eHealth country profiles. The use of eHealth in support of universal health coverage [Internet]. Geneva: WHO; 2016. (3 May 2022); 392. Retreived from www.who.int/%0Awww.who.int/%0Ahttp://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:Atlas+of+eHealth+Country+Profiles#0.
  111. Patel SA, Vashist K, Jarhyan P, Sharma H, Gupta P, Jindal D, et al. A model for national assessment of barriers for implementing digital technology interventions to improve hypertension management in the public health care system in India. BMC Health Serv Res. 2021; 21: 111. DOI: 10.1186/s12913-021-06999-9
  112. ITU-WHO. Digital Health Platform Handbook: Building a Digital Information Infrastructure (Infostructure) for Health; 2017.
  113. Association AM. Telehealth Implementation Playbook of the American Medical Association [Internet]; 2020. (3 May 2022). Retrieved from https://www.ama-assn.org/practice-management/digital/telehealth-implementation-playbook-overview.
  114. Celi LA, Cellini J, Charpignon M-L, Dee EC, Dernoncourt F, Eber R, et al. Sources of bias in artificial intelligence that perpetuate healthcare disparities—A global review. PLOS Digit Heal. 2022; 1: e0000022. DOI: 10.1371/journal.pdig.0000022
  115. Collaborative H data. Digital Health & Interoperability [Internet]. (3 May 2022); Retreived from https://www.healthdatacollaborative.org/working-groups/digital-health-interoperability/.
  116. ODK. ODK – Collect Data Anywhere [Internet]; 2022. (3 May 2022); Retrieved from https://getodk.org/.
  117. Openmrs. OpenMRS.org [Internet]. (3 May 2022); Retreived from https://openmrs.org/.
  118. Dimagi. CommCare [Internet]; 2021. (3 May 2022); Retrieved from https://www.dimagi.com/commcare/.
  119. Surka S, Edirippulige S, Steyn K, Gaziano T, Puoane T, Levitt N. Evaluating the use of mobile phone technology to enhance cardiovascular disease screening by community health workers. Int J Med Inform. 2014; 83: 648654. DOI: 10.1016/j.ijmedinf.2014.06.008
  120. Flynn MR, Barrett C, Cosío FG, Gitt AK, Wallentin L, Kearney P, et al. The Cardiology Audit and Registration Data Standards (CARDS), European data standards for clinical cardiology practice. Eur Heart J. 2005; 26: 308313. DOI: 10.1093/eurheartj/ehi079
  121. McKinsey. Patients love telehealth–physicians are not so sure [Internet]; 2022. (4 July 2022). Retrieved from: https://www.mckinsey.com/industries/healthcare-systems-and-services/our-insights/patients-love-telehealth-physicians-are-not-so-sure.
  122. Asteggiano R, Cowie MR, Richter D, Christodorescu R, Guasti L, Ferrini M. Survey on e-health knowledge and usage in general cardiology of the Council of Cardiology Practice and the Digital Health Committee. Eur Hear J – Digit Heal. 2021; 2: 342347. DOI: 10.1093/ehjdh/ztab032
  123. Ware P, Bartlett SJ, Paré G, Symeonidis I, Tannenbaum C, Bartlett G, et al. Using eHealth Technologies: Interests, Preferences, and Concerns of Older Adults. Interact J Med Res. 2017; 6: e3. DOI: 10.2196/ijmr.4447
  124. Torrent-Sellens J, Díaz-Chao Á, Soler-Ramos I, Saigí-Rubió F. Modelling and predicting eHealth usage in Europe: A multidimensional approach from an online survey of 13,000 European Union Internet Users. J Med Internet Res. 2016; 18. DOI: 10.2196/jmir.5605
  125. Kontos E, Blake KD, Chou WYS, Prestin A. Predictors of ehealth usage: Insights on the digital divide from the health information national trends survey 2012. J Med Internet Res. 2014; 16. DOI: 10.2196/jmir.3117
  126. Yao R, Zhang W, Evans R, Cao G, Rui T, Shen L. Inequities in Health Care Services Caused by the Adoption of Digital Health Technologies: Scoping Review. J Med Internet Res. 2022; 24: e34144. DOI: 10.2196/34144
  127. Ajay VS, Jindal D, Roy A, Venugopal V, Sharma R, Pawar A, et al. Development of a Smartphone-Enabled Hypertension and Diabetes Mellitus Management Package to Facilitate Evidence-Based Care Delivery in Primary Healthcare Facilities in India: The mPower Heart Project. J Am Heart Assoc. 2016; 5. DOI: 10.1161/JAHA.116.004343
  128. Jindal D, Roy A, Ajay VS, Yadav SK, Prabhakaran D, Tandon N. Strategies for Stakeholder Engagement and Uptake of New Intervention: Experience From State-Wide Implementation of mHealth Technology for NCD Care in Tripura, India. Glob Heart. 2019; 14: 165172. DOI: 10.1016/j.gheart.2019.06.002
  129. National Health Authority. Ayushman Bharat Digital Mission [Internet]. (4 July 2022); Retrieved from https://healthid.ndhm.gov.in/.
  130. Patel SA, Sharma H, Mohan S, Weber MB, Jindal D, Jarhyan P, et al. The Integrated Tracking, Referral, and Electronic Decision Support, and Care Coordination (I-TREC) program: scalable strategies for the management of hypertension and diabetes within the government healthcare system of India. BMC Health Serv Res. 2020; 20. DOI: 10.1186/s12913-020-05851-w
  131. Coorey G, Peiris D, Usherwood T, Neubeck L, Mulley J, Redfern J. Persuasive design features within a consumer-focused eHealth intervention integrated with the electronic health record: A mixed methods study of effectiveness and acceptability. PLoS One. 2019; 14: e0218447. DOI: 10.1371/journal.pone.0218447
  132. Neubeck L, Coorey G, Peiris D, Mulley J, Heeley E, Hersch F, et al. Development of an integrated e-health tool for people with, or at high risk of, cardiovascular disease: The Consumer Navigation of Electronic Cardiovascular Tools (CONNECT) web application. Int J Med Inform. 2016; 96: 2437. DOI: 10.1016/j.ijmedinf.2016.01.009
  133. Bhatt A. Healthcare information technology for cardiovascular medicine: telemedicine & digital health; 2021. DOI: 10.1007/978-3-030-81030-6
  134. SwyMed. Why swyMed – Overview – swyMed [Internet]. (4 July 2022); Retireved from https://swymed.com/why-swymed-overview/.
  135. Sierra Wireless. AirLink® MG90/MG90 5G high performance multi-network vehicle routers [Internet]. (4 July 2022); Retireved from https://www.sierrawireless.com/router-solutions/mg90/.
DOI: https://doi.org/10.5334/gh.1141 | Journal eISSN: 2211-8179
Language: English
Submitted on: Jul 14, 2022
Accepted on: Jul 20, 2022
Published on: Aug 26, 2022
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2022 Jasper Tromp, Devraj Jindal, Julie Redfern, Ami B. Bhatt, Tania Séverin, Amitava Banerjee, Junbo Ge, Dipti Itchhaporia, Tiny Jaarsma, Fernando Lanas, Francisco Lopez-Jimenez, Awad Mohamed, Pablo Perel, Gonzalo Emanuel Perez, Fausto J. Pinto, Rajesh Vedanthan, Axel Verstrael, Khung Keong Yeo, Kim Zulfiya, Dorairaj Prabhakaran, Carolyn S.P. Lam, Martin R. Cowie, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.