Skip to main content

Digital Innovation in Healthcare Entrepreneurship

  • Chapter
  • First Online:
Medical Entrepreneurship

Abstract

Advances in technological development are ever increasing at all times; consequently, a rapid increase and changes in digital technology have revolutionized healthcare delivery globally. Digital technologies, which are electronic tools, systems, devices, and resources that generate, store or process data, are known to have impacted health care. They have simplified access to health, lower cost of diagnosis and treatments, and improved communication between doctors and patients in the areas of electronic health (eHealth), storage of and access to medical information and data, generating and storing of big data, improving lines of communication between patients and their doctors, electronic health records (EHRs), telemedicine and telehealth, mobile health (mHealth), online learning (eLearning), health applications, and drones. Following the COVID-19 pandemic, the digital health transformation has increased by leap and bound and would likely play a vital role in fighting current and future pandemics by enabling fundamental shifts in medical care, both during the pandemic and in the aftermath. Despite the gains from digital innovation in health care, they did not come without challenges, which are likely to be more with future advancements in digital technology and health. Virtually all technological tools in health care are associated with challenges, limitations or drawbacks. Notable areas of challenges are related to societal problems, ethical issues, connected health solutions, artificial intelligence, and genomics in precision medicine. The challenges are currently being addressed through digital health research, which, hopefully, would proffer lasting solutions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 179.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Abaza, H., & Marschollek, M. (2017). mHealth application areas and technology combinations: A comparison of literature from high and low/middle income countries. Methods of Information in Medicine, 56(7), e105–e122.

    Google Scholar 

  • Adadi, A., & Berrada, M. (2018). Peeking inside the black-box: A survey on explainable artificial intelligence (XAI). IEEE Access, 6, 52138–52160.

    Article  Google Scholar 

  • Agboola, S. O., Bates, D. W., & Kvedar, J. C. (2016). Digital health and patient safety. Journal of American Medical Association, 315, 1697–1698.

    Article  Google Scholar 

  • Agnihothri, S., Cui, L., Delasay, M., & Rajan, B. (2020). The value of mHealth for managing chronic conditions. Health Care Management Sciences, 23(2), 185–202.

    Article  Google Scholar 

  • Alcaraz, K. I., Sly, J., Ashing, K., Fleisher, L., Gil-Rivas, V., et al. (2017). The ConNECT framework: A model for advancing behavioral medicine science and practice to foster health equity. Journal of Behavioural Medicine, 40, 23–38.

    Article  Google Scholar 

  • Alvarez-Perea, A., Dimov, V., Popescu, F., & Zubeldia, J. M. (2021). The applications of eHealth technologies in the management of asthma and allergic diseases. Clinical and Translational Allergy, 11(7), e12061. https://doi.org/10.1002/clt2.12061

    Article  Google Scholar 

  • Amukele, T. K., Sokoll, L. J., Pepper, D., Howard, D. P., & Street, J. (2015). Can unmanned aerial systems (drones) be used for the routine transport of chemistry, hematology, and coagulation laboratory specimens? PLoS ONE, 10(7), 1–15.

    Article  Google Scholar 

  • Andersen, B. L., Conley, C. C., & Blevins, T. R. (2022). 8.12 – Cancer. In Gordon, J.G. Asmundson (Ed.). Comprehensive clinical psychology (2nd Ed, pp. 211–226), Elsevier.

    Google Scholar 

  • Antonicelli, R., Testarmata, P., Spazzafumo, L., Gagliardi, C., Bilo, G., Valentini, M., et al. (2008). Impact of telemonitoring at home on the management of elderly patients with congestive heart failure. Journal of Telemedicine and Telecare, 14(6), 300–305.

    Article  Google Scholar 

  • Bounfour, A. (2016). Digital futures, digital transformation: From lean production to acceluction. Springer International Publishing Switzerland. https://doi.org/10.1007/978-3-319-23279-9

    Book  Google Scholar 

  • Baro, E., Degoul, S., Beuscart, R., & Chazard, E. (2015). Toward a literature-driven definition of big data in healthcare. BioMed Research International, vol. 2015, Article ID 639021, p. 9. https://doi.org/10.1155/2015/639021

  • Cao, J., Zhang, G., & Liu, D. (2022). The impact of using mHealth Apps on improving public health satisfaction during the COVID-19 pandemic: A digital content value chain perspective. Healthcare (basel), 10(3), 479. https://doi.org/10.3390/healthcare10030479

    Article  Google Scholar 

  • Chandrashekar, P. (2018). Do mental health mobile apps work: Evidence and recommendations for designing high-efficacy mental health mobile apps. mHealth, 4, 6. https://doi.org/10.21037/mhealth.2018.03.02.

  • Charles, B. L. (2000). Telemedicine can lower costs and improve access. Healthcare Financial Management, 54(4), 66–69.

    Google Scholar 

  • Chauhan, B., George, R., & Coffin, J. (2012). Social media and you: What every physician needs to know. Journal of Medical Practice Management, 28(3), 206–209.

    Google Scholar 

  • Christiansen, C., Waldeck, A., & Fogg, R. (2017). How disruptive innovation can finally revolutionize healthcare. The Clayton Christensen Institute.

    Google Scholar 

  • Conde, J. G., De, S., Hall, R. W., Johansen, E., Meglan, D., & Peng, G. C. (2010). Telehealth innovations in health education and training. Telemedicine Journal and e-Health: The Official Journal of the American Telemedicine Association, 16(1), 103–106.

    Google Scholar 

  • Cordeiro, J. V. (2021). Digital technologies and data science as health enablers: An outline of appealing Promises and compelling ethical, legal, and social challenges. Front Med (lausanne), 8, 647897. https://doi.org/10.3389/fmed.2021.647897

    Article  Google Scholar 

  • Cortez, N. (2018). 18. In: The evolving law and ethics of digital health. Springer International Publishing, pp. 249–269. doi: https://doi.org/10.1007/978-3-319-61446-5_18.

  • Cummins, N., Schuller, B. W., & Baird, A. (2018). Speech analysis for health: Current state-of-the-art and the increasing impact of deep learning. Methods, 151, 41–54.

    Article  Google Scholar 

  • Cunningham, P., Cunningham, M., & Ekenberg, L. (2016). Factors impacting on the current level of open innovation and ICT entrepreneurship in Africa. Electronic Journal of Information Systems in Developing Countries, 73(1), 1–2.

    Article  Google Scholar 

  • Dafny, L., & Mohta, N. S. (2017). New marketplace survey: The sources of health care innovation. New England Journal of Medicine Catalyst, 16, 2017.

    Google Scholar 

  • Dash, S., Shakyawar, S. K., Sharma, M., & Kaushik, S. (2019). Big data in healthcare: Management, analysis and future prospects. Journal of Big Data 6, 54. https://doi.org/10.1186/s40537-019-0217-0

  • Davidson, E., & Vaast, E. (2010). Digital entrepreneurship and its sociomaterial enactment. In Proceedings of the Annual Hawaii International Conference on System Sciences, pp. 1–10. IEEE.

    Google Scholar 

  • de Wit, M., Cooper, C., & Reginster, J. Y. (2019). Practical guidance for patient-centred health research. Lancet, 393, 1095–1096.

    Article  Google Scholar 

  • DeBusk, W. M. (2010). Unmanned aerial vehicle systems for disaster relief: Tornado alley. AIAA Infotech at Aerospace, Article Number 2010–3506.

    Google Scholar 

  • Dizon, D. S., Graham, D., Thompson, M. A., et al. (2012). Practical guidance: The use of social media in oncology practice. Journal of Oncology Practice, 8(5), 114–124.

    Article  Google Scholar 

  • Doherty, P., & Rudol, P. (2007). A UAV search and rescue scenario with human body detection and geolocalization. In M. A. Orgun, & J. Thornton (Eds.). AI 2007: Advances in artificial intelligence, lecture notes in computer science, vol. 4830. Springer.

    Google Scholar 

  • Dongyele, M., Ansong, D., Osei, F. A., Amuzu, E. X., Mensah, N. K., Kwame Owusu, A., Dankwa, B., (2021). Communication Medium Used by Clients and Health Professionals in Accessing and Providing Healthcare in Low Resource Setting: A Descriptive Cross-Sectional Study. Advances in Public Health, 2021, 7 p. Article ID 7419305. https://doi.org/10.1155/2021/7419305.

  • Drew, L. (2022). The brain-reading devices helped paralysed people to move, talk and touch. Nature, 604, 416–419.

    Article  Google Scholar 

  • European Commission. (2010). Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions: A digital agenda for Europe. Brussels, 19.5.2010. COM/2010/245 final. Available at: https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=COM:2010:0245:FIN:EN:PDF (Accessed 2 May 2022).

  • European Commission. (2013). Commission launched 'Opening up Education' to boost innovation and digital skills in schools and universities. Brussels, 25 September 2013. COM/2013/654/final. Available at: https://ec.europa.eu/commission/presscorner/detail/en/IP_13_859 (Accessed 2 May 2022).

  • Evaluation of Genomic Applications in Practice and Prevention (EGAPP) Working Group. (2007). Recommendations from the EGAPP working group: Testing for cytochrome P450 polymorphisms in adults with nonpsychotic depression treated with selective serotonin reuptake inhibitors. Genet Med., 819–25.

    Google Scholar 

  • Ehrenstein, V., Nielsen, H., Pedersen, A. B., Johnsen, S. P., & Pedersen, L. (2017). Clinical epidemiology in the era of big data: New opportunities, familiar challenges. Clinical Epidemiology, 9, 245–250.

    Article  Google Scholar 

  • Erlinge, D., James, S., Duvvuru, S., Jakubowski, J. A., Wagner, H., Varenhorst, C., et al. (2014). Clopidogrel metabolizer status based on point-of-care CYP2C19 genetic testing in patients with coronary artery disease. Thrombosis and Haemostasis, 111(5), 943–950.

    Article  Google Scholar 

  • Fahey, R. A., & Hino, A. (2020). COVID-19, digital privacy, and the social limits on data- focused public health responses. International Journal of Information Management, 55, 102181. https://doi.org/10.1016/j.ijinfomgt.2020.102181

    Article  Google Scholar 

  • Farnan, J. M., Snyder, S. L., Worster, B. K., Chaudhry, H. J., Rhyne, J. A., Arora, V. M., et al. (2013). Online medical professionalism: Patient and public relationships: Policy statement from the American College of Physicians and the Federation of State Medical Boards. Annals of Internal Medicine, 158(8), 620–627.

    Article  Google Scholar 

  • Flott, K., Callahan, R., Darzi, A., & Mayer, E. (2016). A patient-centered framework for evaluating digital maturity of health services: A systematic review. Journal of Medical Internet Research, 18(4), e75. https://doi.org/10.2196/jmir.5047

    Article  Google Scholar 

  • Furu, K., Kieler, H., Haglund, B., Engeland, A., Selmer, R., Stephansson, O., Valdimarsdottir, U. A., et al. (2015). Selective serotonin reuptake inhibitors and venlafaxine in early pregnancy and risk of birth defects: Population-based cohort study and sibling design. British Medical Journal (clinical Research Ed.), 350, h1798.

    Google Scholar 

  • Gajarawala, S. N., & Pelkowski, J. N. (2021). Telehealth benefits and barriers. The Journal for Nurse Practitioners, 17(2), 218–221.

    Article  Google Scholar 

  • Gasser, U., Ienca, M., Scheibner, J., Sleigh, J., & Vayena, E. (2020). Digital tools against COVID-19: Taxonomy, ethical challenges, and navigation aid. The Lancet. Digital Health, 2(8), e425–e434.

    Article  Google Scholar 

  • Giones, F., & Brem, A. (2017). Digital technology entrepreneurship: A definition and research agenda. Technology Innovation Management Review, 7(5), 44–51.

    Article  Google Scholar 

  • Gohmann, S. F. (2012). Institutions, latent entrepreneurship, and self-employment: An international comparison. Entrepreneurship: Theory and Practice, 36(2), 295–321.

    Google Scholar 

  • Goyal, P., Cohen-Mekelburg, S., Egan, C., Unterbrink, M., Francis-Heaven, Y., Giambrone, A. E., & Gupta, R. (2018). New uses of old technology: Can nurse-pagers improve communication between resident-physicians and nurses. Applied Nursing Research, 44, 1–5.

    Article  Google Scholar 

  • Grimm, P. W., Grossman, M. R., & Cormack, G. V. (2021). Artificial intelligence as evidence. Northwestern Journal of Technology and Intellectual Property, 9(1), 9–106.

    Google Scholar 

  • Haleem, A., Javaid, M., Singh, R. P., & Suman, R. (2021). Telemedicine for healthcare: Capabilities, features, barriers, and applications. Sensors International, 2, 100117. https://doi.org/10.1016/j.sintl.2021.100117

    Article  Google Scholar 

  • Han, S., Pool, J., Tran, J., & Dally, W. J. (2015). Learning both weights and connections for efficient neural networks. In C. Cortes, N. D. Lawrence, D. D. Lee, M. Sugiyama, R. Garnett (Ed.), Proceedings of the 28th International Conference on Neural Information Processing Systems (Vol. 1, pp. 1135–1143). Curran Associates, Inc.

    Google Scholar 

  • Hassibian, R. M., & Hassibian, S. (2016). Telemedicine acceptance and implementation in developing countries: Benefits, categories, and barriers. Razavi International Journal of Medicine, 4(3), e38332. https://doi.org/10.17795/rijm38332

    Article  Google Scholar 

  • He, M., & Li, W. (2007). PediDraw: A web-based tool for drawing a pedigree in genetic counselling. BMC Medical Genetics, 8, 31. https://doi.org/10.1186/1471-2350-8-31

    Article  Google Scholar 

  • Hulot, J. S., Bura, A., Villard, E., Azizi, M., Remones, V., Goyenvalle, C., et al. (2006). Cytochrome P450 2C19 loss-of-function polymorphism is a major determinant of clopidogrel responsiveness in healthy subjects. Blood, 108(7), 2244–2247.

    Article  Google Scholar 

  • Hoque, M. R., Rahman, M. S., Nipa, N. J., & Hasan, M. R. (2020). Mobile health interventions in developing countries: A systematic review. Health Informatics Journal, 26(4), 2792–2810.

    Article  Google Scholar 

  • Htet, Z. B. (Ed.). (2016). Disaster drones: Great potential, few challenges? RSIS Commentaries. Nanyang Technological University.

    Google Scholar 

  • Ibn, E., Ahrache, S., Hassan, B., Tabaa, Y., & Medouri, A. (2013). Massive open online courses: A new dawn for higher education? International Journal on Computer Science and Engineering, 5(5), 323–327.

    Google Scholar 

  • IESO. (2020). Digital health: Written evidence. Retrieved May 2, 2022 from https://committees.parliament.uk/writtenevidence/19183/pdf/.

  • Inan, O. T., Tenaerts, P., Prindiville, S. A., Reynolds, H. R., Dizon, D. S., Cooper-Arnold, K., et al. (2020). Digitizing Clinical Trials. Npj Digital Medicine, 3, 101. https://doi.org/10.1038/s41746-020-0302-y

  • ITU. (2016). Be He@lthy be mobile: Making digital and mobile health deliver for the SDGs. Retrieved May 15, 2022 from https://www.itu.int/en/ITU-D/Membership/Documents/2.2%20Prasad%20WHO-ITU%20.pdf.

  • ITU. (2022a). Partners BeHe@lthy BeMobile. Retrieved May 3, 2022a from https://www.itu.int/en/ITU-D/ICT-Applications/Pages/partners-behealthy-bemobile.aspx.

  • ITU. (2022b). EU mHealth innovation and knowledge hub. Retrieved May 3, 2022b from https://www.itu.int/en/ITU-D/ICT-Applications/Pages/EU-mhealth-hub.aspx.

  • Jamoom, E. W., Heisey-Grove, D., Yang, N., & Scanlon, P. (2016). Physician opinions about EHR use by EHR experience and by whether the practice had optimized its EHR use. Journal of Health and Medical Informatics, 7(4), 1000240. https://doi.org/10.4172/2157-7420.1000240

    Article  Google Scholar 

  • Singh, J. L., & H., Couch, D., & Yap, K. (2020). Mobile health apps that help with COVID-19 management: Scoping review. JMIR Nursing, 3(1), e20596. https://doi.org/10.2196/20596

    Article  Google Scholar 

  • Keesara, S., Jonas, A., & Schulman, K. (2020). Covid-19 and health care’s digital revolution. The New England Journal of Medicine, 382(23), e82. https://doi.org/10.1056/NEJMp2005835

    Article  Google Scholar 

  • Khin, S., & Ho, T. C. (2020). Digital technology, digital capability and organizational performance: A mediating role of digital innovation. International Journal of Innovation Science, 11(2), 177–195.

    Article  Google Scholar 

  • King, J., Patel, V., Jamoom, E. W., & Furukawa, M. F. (2014). Clinical benefits of electronic health record use: National findings. Health Services Research, 49(1 Pt 2), 392–404.

    Article  Google Scholar 

  • Kostkova, P., Brewer, H., de Lusignan, S., Fottrell, E., Goldacre, B., Hart, G., et al. (2016). Who owns the data? Open data for healthcare. Frontier in Public Health, 4, 7. https://doi.org/10.3389/fpubh.2016.00007

    Article  Google Scholar 

  • Kraus, S., Palmer, C., Kailer, N., Kallinger, F., & Spitzer, J. (2019a). Digital entrepreneurship. International Journal of Entrepreneurial Behavior and Research, 25(2), 353–375.

    Google Scholar 

  • Kraus, S., Roig-Tierno, N., & Bouncken, R. B. (2019b). Digital innovation and venturing: An introduction into digitalization of entrepreneurship. Review of Management Science, 13, 519–528.

    Google Scholar 

  • Laato, S., Islam, A. K. M. N., Islam, M. N., & Whelan, E. (2020). What drives unverified information sharing and cyberchondria during the COVID-19 pandemic? European Journal of Information System, 29(1), 1–18.

    Google Scholar 

  • Lambert, K. M., Barry, P., & Stokes, G. (2012). Risk management and legal issues with the use of social media in the healthcare setting. Journal of Healthcare Risk Management, 31(4), 41–47.

    Article  Google Scholar 

  • Lanham, K. J., Oestreich, J. H., & Dunn, S. P. (2010). Impact of genetic polymorphisms on clinical response to antithrombotics. Pharmacogenomics and Personalized Medicine, 3, 87–99.

    Article  Google Scholar 

  • Lee, T. H., Campion, E. W., Morrissey, S., & Drazen, J. M. (2015). Leading the transformation of health care delivery, the launch of the NEJM catalyst. The New England Journal of Medicine, 373(25), 2468–2469.

    Article  Google Scholar 

  • Lennon, M. R., Bouamrane, M. M., Devlin, A. M., O’Connor, S., O’Donnell, C., Chetty, U., et al. (2017). Readiness for delivering digital health at scale: Lessons from a longitudinal qualitative evaluation of a national digital health innovation program in the United Kingdom. Journal of Medical Internet Research, 19, e4. https://doi.org/10.2196/jmir.6900

    Article  Google Scholar 

  • Lewis, J., Ray, P., & Liaw, S. T. (2016). Recent worldwide developments in eHealth and mHealth to more effectively manage cancer and other chronic diseases—A systematic review. Yearbook of Medical Informatics, 16(1), 93–108.

    Google Scholar 

  • Lippi, G., & Mattiuzzi, C. (2016). Biological sample transportation by drones: ready for prime time? Annals of Translational Medicine, 4(5), 92. https://doi.org/10.21037/atm.2016.02.03.

  • Lipsitz, L. A. (2012). Understanding health care as a complex system: The foundation for unintended consequences. Journal of American Medical Association, 308(3), 243–244.

    Article  Google Scholar 

  • Liu, X., Faes, L., Kale, A. U., Wagner, S. K., Fu, D. J., Bruynseels, A., et al. (2019). A comparison of deep learning performance against healthcare professionals in detecting diseases from medical imaging: A systematic review and meta-analysis. The Lancet Digital Health, 1, e271–e297.

    Article  Google Scholar 

  • Luo, J., Wu, M., Gopukumar, D., & Zhao, Y. (2016). Big data application in Biomedical research and health care: A literature review. Biomedical Informatics Insights, 8, 1–10.

    Article  Google Scholar 

  • Maranville, S. (1992). Entrepreneurship in the business curriculum. Journal of Education for Business, 68(1), 27–31.

    Article  Google Scholar 

  • Marcano Belisario, J. S., Huckvale, K., Greenfield, G., Car, J., & Gunn, L. H. (2013). Smartphone and tablet self-management apps for asthma. The Cochrane Database of Systematic Review, 2013(11), CD010013. https://doi.org/10.1002/14651858.CD010013.pub2.

  • Markus, M. L., & Loebbecke, C. (2013). Commoditized digital processes and business community platforms: New opportunities and challenges for digital business strategies. MIS Quarterly, 37(2), 649–654.

    Google Scholar 

  • Mathews, S. C., McShea, M. J., Hanley, C. L., Ravitz, A., Labrique, A. B., & Cohen, A. B. (2019). Digital health: A path to validation. npj Digital Medicine, 2, 38. https://doi.org/10.1038/s41746-019-0111-3

  • Matricardi, P. M., Dramburg, S., Alvarez-Perea, A., Antolín-Amérigo, D., Apfelbacher, C., Atanaskovic-Markovic, M., et al. (2020). The role of mobile health technologies in allergy care: An EAACI position paper. Allergy. European Journal of Allergy and Clinical Immunology, 75(2), 259–272.

    Google Scholar 

  • May, E. (2021). How digital health apps empower patients, improve outcomes, and increase accessibility. Deloitte. Retrieved May 2, 2022 from https://blogs.deloitte.co.uk/health/2021/10/how-digital-health-apps-are-empowering-patients-improving-outcomes-and-increasing-accessibility.html.

  • McClellan, M. (2007). Drug safety reform at the FDA-pendulum swing or systematic improvement? The New England Journal of Medicine, 356(17), 1700–1702.

    Article  Google Scholar 

  • Medhekar, A., & Nguyen, J. (2020). Chapter 8, My digital healthcare record: Innovation, challenge, and patient empowerment. In K. Sandhu (Ed.), Opportunities and challenges in digital healthcare innovation, pp. 131–150). https://doi.org/10.4018/978-1-7998-3274-4.ch008.

  • Mega, J. L., Simon, T., Collet, J. P., et al. (2010). Reduced-function CYP2C19 genotype and risk of adverse clinical outcomes among patients treated with clopidogrel predominantly for PCI: A meta-analysis. The Journal of the American Medical Association, 304(16), 1821–1830.

    Article  Google Scholar 

  • Muse, E. D., Torkamani, A., & Topol, E. J. (2018). When genomics goes digital. The Lancet, 391(10138), 2405.

    Article  Google Scholar 

  • Mirchev, M. (2019). Patient information ownership in the age of digital health and big data. European Journal of Public Health, 2(Suppl 4). https://doi.org/10.1093/eurpub/ckz186.078

  • Naeem, F., Mohsin, M., Rauf, U., & Ali Khan, L. (2021). Formal approach to thwart against drone discovery attacks: A taxonomy of novel 3D obfuscation mechanisms. Future Generation Computer Systems, 115, 374–386.

    Article  Google Scholar 

  • Neal, D. (2011). Choosing an electronic health records system: Professional liability considerations. Innovations in Clinical Neuroscience, 8(6), 43–45.

    Google Scholar 

  • Nedelkoska, L., & Glenda, Q. (2018). Automation, skills use and training. In OECD Social, Employment and Migration Working Papers. OECD Publishing.

    Google Scholar 

  • Narayanan, R. G. L., & Ibe, O. C. (2015). 6-Joint network for disaster relief and search and rescue network operations. In D. Câmara, & N. Nikaein (Eds.), Wireless public safety networks (pp.163–193). Elsevier.

    Google Scholar 

  • NHS. (2021). Milestone hit with over 16 million NHS app users. Retrieved May 2, 2022 from https://www.nhsx.nhs.uk/news/milestone-hit-with-over-16-million-nhs-app-users.

  • O’Connor, Y., Rowan, W., Lynch, L., & Heavin, C. (2017). Privacy by design: Informed consent and internet of things for smart health. Procedia Computer Science, 113, 653–658. https://doi.org/10.1016/j.procs.2017.08.329

    Article  Google Scholar 

  • Oluyede, L., Cochran, A. L., Wolfe, M., Prunkl, L., & McDonald, N. (2020). Addressing transportation barriers to health care during the COVID-19 pandemic: Perspectives of care coordinators. Transportation Reearch, Part A Policy Practice, 159, 157–168.

    Article  Google Scholar 

  • Olsen, E. (2021). Digital health apps balloon to more than 350,000 available on the market, according to IQVIA report. Mobihealth News: Digital Health. Retrieved May 2, 2022 from https://www.mobihealthnews.com/news/digital-health-apps-balloon-more-350000-available-market-according-iqvia-report.

  • Osei, E., & Mashamba-Thompson, T. P. (2021). Mobile health applications for disease screening and treatment support in low-and middle-income countries: A narrative review. Heliyon, 7(3), e06639. https://doi.org/10.1016/j.heliyon.2021.e06639

    Article  Google Scholar 

  • Panch, T., Mattie, H., & Atun, R. (2019). Artificial intelligence and algorithmic bias: Implications for health systems. Journal of Global Health, 9, 010318. https://doi.org/10.7189/jogh.09.020318

    Article  Google Scholar 

  • Psaty, B. M., & Breckenridge, A. M. (2014). Mini-Sentinel and regulatory science- big data rendered fit and functional. The New England Journal Medicine, 370(23), 2165–2167.

    Article  Google Scholar 

  • Pai, A. (2014). Google unveils Google fit, a fitness platform for developers. Retrieved May 12, 2022 from https://www.mobihealthnews.com/34430/google-unveils-google-fit-a-fitness-platform-for-developers.

  • Patil, S., Lu, H., Saunders, C. L., Potoglou, D., & Robinson, N. (2016). Public preferences for electronic health data storage, access, and sharing—Evidence from a pan-European survey. Journal of American Medical Informatics Association, 23, 1096–1106.

    Article  Google Scholar 

  • Patrick, K., Hekler, E. B., Estrin, D., Mohr, D. C., Riper, H., Crane, D., et al. (2016). The pace of technologic change: Implications for digital health behavior intervention research. The American Journal of Preventive Medicine, 51, 816–824.

    Article  Google Scholar 

  • Pattichis, C. S., & Panayides, A. S. (2019). Connected health. Frontiers in Digital. Health, 1, 1. https://doi.org/10.3389/fdgth.2019.00001

    Article  Google Scholar 

  • Peck, J. L. (2014). Social media in nursing education: Responsible integration for meaningful use. Journal of Nursing Education, 53(3), 164–169.

    Article  Google Scholar 

  • Pennycook, G., McPhetres, J., Zhang, Y., Lu, J. G., & Rand, D. G. (2020). Fighting COVID-19 misinformation on social media: Experimental evidence for a scalable accuracy-nudge intervention. Psychological Science, 31, 770–780.

    Article  Google Scholar 

  • Plsek, P. E., & Greenhalgh, T. (2021). The challenge of complexity in health care. British Medical Journal, 323(7313), 625–628.

    Article  Google Scholar 

  • Porterfield, A., Engelbert, K., & Coustasse, A. (2014). Electronic prescribing: Improving the efficiency and accuracy of prescribing in the ambulatory care setting. Perspectives in Health Information Management, 11(Spring), 1 g.

    Google Scholar 

  • Radanliev, P., De Roure, D., Walton, R., Van Kleek, M., Montalvo, R. M., Santos, O., et al. (2020). What have we learned from COVID-19? The rise of social machines and connected devices in pandemic management follows the concepts of predictive, preventive and personalized medicine. EPMA Journal, 11, 311–332.

    Article  Google Scholar 

  • Ramirez, A. V., Ojeaga, M., Espinoza, V., Hensler, B., & Honrubia, V. (2021). Telemedicine in minority and socioecnomically disadvantaged communities amidst the COVID-19 pandemic. Otolaryngology, Head and Neck Surgery, 164(1), 91–92.

    Article  Google Scholar 

  • Ramsetty, A., & Adams, C. (2020). Impact of the digital divide in the age of COVID-19. Journal of the American Medical Informatics Association, 27(7), 1147–1148.

    Article  Google Scholar 

  • Reddy, M. C., Pratt, W., McDonald, D. W., & Shabot, M. M. (2003). Challenges to physicians’ use of a wireless alert pager. AMIA. Annual Symposium Proceedings. AMIA Symposium, 2003, 544–548.

    Google Scholar 

  • Rehm, H. L. (2017). Evolving health care through personal genomics. Nature Reviews. Genetics, 18(4), 259–267.

    Article  Google Scholar 

  • Richter, C., Kraus, S., Brem, A., Durst, S., & Giselbrecht, C. (2017). Digital entrepreneurship: Innovative business models for the sharing economy. Creativity and Innovation Management, 26(3), 300–310.

    Article  Google Scholar 

  • Roberts, J. D., Wells, G. A., Le May, M. R., Labinaz, M., Glover, C., Froeschl, M., Dick, A., et al. (2012). Point-of-care genetic testing for personalization of antiplatelet treatment (RAPID GENE): A prospective, randomized, proof-of-concept trial. The Lancet, 379(9827), 1705–1711.

    Article  Google Scholar 

  • Robbins, D., & Dunn, P. (2019). Digital health literacy in a person-centric world. International Journal of Cardiology, 290, 154–155.

    Article  Google Scholar 

  • Rowland, S.P., Fitzgerald, J.E., Holme, T., Powell, J., & McGregor, A. (2020). What is the clinical value of mHealth for patients? npj Digital Medicine, 3, 4. https://doi.org/10.1038/s41746-019-0206-x

  • Rouse, W. (2008). Health care as a complex adaptive system: Implications for design and management. Bridge, 38(1), 17–25.

    Google Scholar 

  • Ruotsalainen, P. S. (2017). Chapter 5–privacy, trust and security in two-sided markets. In V. Vimarlund (Ed.), e-Health two-sided markets (pp. 65–89). Academic Press. https://doi.org/10.1016/B978-0-12-805250-1.00005-8

  • Safi, S., Thiessen, T., & Schmailzl, K. J. (2018). Acceptance and resistance of new digital technologies in medicine: Qualitative study. JMIR Research Protocols, 7(12), e11072. https://doi.org/10.2196/11072

    Article  Google Scholar 

  • Saljoughian, M. (2021). The benefits and limitations of Telehealth. US Pharm, 46(8), 5–8.

    Google Scholar 

  • Seymour, T., Frantsvog, D., & Graeber, T. (2012). Electronic Health Records (EHR). American Journal of Health Sciences (AJHS), 3(3), 201–210.

    Article  Google Scholar 

  • Schmietow, B., & Marckmann, G. (2019). Mobile health ethics and the expanding role of autonomy. Medicine, Healthcare and Philosophy, 22(4), 623–630.

    Article  Google Scholar 

  • Schwartz, P. H., Caine, K., Alpert, S. A., Meslin, E. M., Carroll, A. E., & Tierney, W. M. (2014). Patient preferences in controlling access to their electronic health records: A prospective cohort study in primary care. Journal of General Internal Medicine, 30(Suppl 1), S25-30.

    Google Scholar 

  • Scott, J., & Scott, C. (2017). Drone delivery models for healthcare. Proceedings of the 50th Hawaii International Conference on System Sciences, 3297–3304.

    Google Scholar 

  • Shamsrizi, M., Pakura, A., Wiechers, J., Pakura, S., & Dauster, D.V. (2021). Digital entrepreneurship for the “Decade of action”. In M. Soltanifar, M. Hughes, & L. Göcke (Eds.), Digital entrepreneurship. Future of Business and Finance Publisher: Springer. https://doi.org/10.1007/978-3-030-53914-6_15.

  • Sharon, T. (2016). The Googlization of health research: From disruptive innovation to disruptive ethics. Personalized Medicine, 13(6), 563–574.

    Article  Google Scholar 

  • Sibbing, D., Stegherr, J., Latz, W., Koch, W., Mehilli, J., Dörrler, K., et al. (2009). Cytochrome P450 2C19 loss-of-function polymorphism and stent thrombosis following percutaneous coronary intervention. European Heart Journal, 30(8), 916–922.

    Article  Google Scholar 

  • Sibbing, D., Aradi, D., Jacobshagen, C., Gross, L., Trenk, D., Geisler, T., et al. (2017). A randomized trial on platelet function-guided de-escalation of antiplatelet treatment in ACS patients undergoing PCI. Rationale and design of the Testing Responsiveness to Platelet Inhibition on Chronic Antiplatelet Treatment for Acute Coronary Syndromes (TROPICAL-ACS) Trial. Thrombosis and Haemostasis,117(1),188–195.

    Google Scholar 

  • Sinsky, C., Colligan, L., Li, L., Prgomet, M., Reynolds, S., Goeders, L., et al. (2016). Allocation of physician time in ambulatory practice: A time and motion study in 4 specialties. Annals of Internal Medicine, 165(11), 753–760.

    Article  Google Scholar 

  • Stausberg, J., Koch, D., Ingenerf, J., & Betzler, M. (2003). Comparing paper-based with electronic patient records: Lessons learned during a study on diagnosis and procedure codes. Journal of the American Medical Informatics Association, 10(5), 470–477.

    Article  Google Scholar 

  • Steinberg, D., Horwitz, G., & Zohar, D. (2015). Building a business model in digital medicine. Nature Biotechnology, 33(9), 910–920.

    Article  Google Scholar 

  • Suresh, D., Chaudhari, S., Saxena, A., & Gupta, P. K. (2021). Telemedicine and telehealth: The current update. In A. K. Manocha, S. Jain, M. Singh, & S. Paul (Eds.), Computational intelligence in healthcare. Health Information Science: Springer. https://doi.org/10.1007/978-3-030-68723-6_4.

  • Syrowatka, A., Kuznetsova, M., Alsubai, A. et al. (2021). Leveraging artificial intelligence for pandemic preparedness and response: A scoping review to identify key use cases. npj Digital Medicine, 4, 96. https://doi.org/10.1038/s41746-021-00459-8

  • Tarkkala, H., Helén, I., & Snell, K. (2019). From health to wealth: The future of personalized medicine in the making. Futures, 109, 142–152.

    Article  Google Scholar 

  • Teviu, E. A., Aikins, M., Abdulai, T. I., Sackey, S., Boni, P., Afari, E., & Wurapa, F. (2012). Improving medical records filing in a municipal hospital in Ghana. Ghana Medical Journal, 46(3), 136–141.

    Google Scholar 

  • Thakur, S., & Lahiry, S. (2021). Digital clinical trial: A new norm in clinical research. Perspectives in Clinical Research, 12(4), 184–188.

    Article  Google Scholar 

  • Tharpe, C. (2020). Types of EHR systems. Retrieved May 2, 2022 from https://www.wheel.com/companies-blog/types-of-ehr-systems.

  • The 1000 Genomes Project Consortium. (2015). A global reference for human genetic variation. Nature, 526, 68–74.

    Article  Google Scholar 

  • Thiels, C. A., Aho, J. M., Zietlow, S. P., & Jenkins, D. H. (2015). Use of unmanned aerial vehicles for medical product transport. Journal of Air Medicine Transport, 34(2), 104–148.

    Article  Google Scholar 

  • Topol, E. J. (2012). The creative destruction of medicine: How the digital revolution will create better health care. Basic Books.

    Google Scholar 

  • Trent, R. J. (2012). Chapter 4—Omics, molecular medicine (4th Edn.). Academic Press, pp. 117–152. https://doi.org/10.1016/B978-0-12-381451-7.00004-9.

  • Trifirò, G., Coloma, P. M., Rijnbeek, P. R., Romio, S., Mosseveld, B., Weibel, D., et al. (2014). Combining multiple healthcare databases for postmarketing drug and vaccine safety surveillance: Why and how? Journal of Internal Medicine, 275(6), 551–561.

    Article  Google Scholar 

  • Tsai, J., & Bond, G. (2008). A comparison of electronic records to paper records in mental health centers. International Journal of Quality Healthcare, 20(2), 136–143.

    Article  Google Scholar 

  • UNCTAD. (2021). Technology and innovation Report 2021: Catching technological waves Innovation with equity. United Nations Conference on Trade and Development (UNCTAD).

    Google Scholar 

  • Unicef. (2019). Drones for Good Corridor launched as drones take flight to deliver medicine to remote areas in Sierra Leone. Retrieved May 12, 2022 from https://www.unicef.org/wca/press-releases/drones-good-corridor-launched-drones-take-flight-deliver-medicine-remote-areas.

  • United Nations. (2018). The technology and innovation report 2018: Harnessing frontier technologies for sustainable development. Retrieved May 13, 2022 from https://unctad.org/system/files/official-document/tir2018_en.pdf.

  • Van Driest, S. L., Shi, Y., Erica, A., Bowton, E. A., Schildcrout, J. S., Peterson, J. F., et al. (2014). Clinically actionable genotypes among 10,000 patients with preemptive pharmacogenomic testing. Clinical Pharmacology and Therapeutics, 95(4), 423–431.

    Article  Google Scholar 

  • van der Stelt, P. F. (2008). Better imaging: The advantages of digital radiography. Journal of American Dental Association, 139(Suppl), 7S-13S.

    Article  Google Scholar 

  • Vayena, E., Haeusermann, T., Adjekum, A., & Blasimme, A. (2018). Digital health: Meeting the ethical and policy challenges. Swiss Medical Weekly, 148, w14571. https://doi.org/10.4414/smw.2018.14571

    Article  Google Scholar 

  • Ventola, C. L. (2014). Social media and health care professionals: Benefits, risks, and best practices. P & t: A Peer-Reviewed Journal for Formulary Management, 39(7), 491–520.

    Google Scholar 

  • Voigt, P., & Von dem Bussche, A. (2017). The EU General Data Protection Regulation (GDPR): A practical guide. Springer.

    Book  Google Scholar 

  • Von Muhlen, M., & Ohno-Machado, L. (2012). Reviewing social media use by clinicians. Journal of American Medical Informatics Association, 19(5), 77–781.

    Google Scholar 

  • Watcher, R. M. (2017). The digital doctor: Hope, hype and harm at the dawn of medicine’s computer age. McGraw-Hill Education.

    Google Scholar 

  • WHO. (1998). A health telematics policy: In support of WHO’s health-for-all strategy for global health development. Report of the WHO Group Consultation on Health Telematics, 11–16 December, Geneva, 1997. WHO/DGO/98.1.

    Google Scholar 

  • WHO. (2011). World Health Organization global observatory for eHealth, mHealth: New horizons for health through mobile technologies. Based on the findings of the second global survey on health, in global observatory for eHealth Series. Volume 3. Geneva: World Health Organization.

    Google Scholar 

  • WHO. (2012). ITU and WHO launch mHealth initiative to combat noncommunicable diseases. Retrieved May 3, 2022 from https://www.who.int/news/item/17-10-2012-itu-and-who-launch-mhealth-initiative-to-combat-noncommunicable-diseases.

  • WHO-ITU. (2017). Be He@lthy Be Mobile Annual Report 2017. Retrieved May 3, 2022 from https://www.itu.int/en/ITU-D/ICT-Applications/Documents/Reports-BeHealthy-BeMobile/BD_19-00006_BHBM_Annual-report-2017.pdf.

  • WHO. (2016a). From innovation to implementation: eHealth in the WHO European Region. mHealth, pp. 40–51. Retrieved May 15, 2022 from https://www.euro.who.int/__data/assets/pdf_file/0012/302331/From-Innovation-to-Implementation-eHealth-Report-EU.pdf.

  • WHO. (2016b). From innovation to implementation: eHealth in the WHO European Region. eLearning, pp. 52–58. Retrieved May 15, 2022 from https://www.euro.who.int/__data/assets/pdf_file/0012/302331/From-Innovation-to-Implementation-eHealth-Report-EU.pdf.

  • WHO. (2018). Working together: An integration resource guide for immunization services throughout the life course. World Health Organization.

    Google Scholar 

  • WHO. (2021). Leveraging telehealth for efficient delivery of primary health care in the WHO South-East Asia Region.

    Google Scholar 

  • WHO. (2022). Be Healthy Be Mobile: Country implementation. Be He@lthy, Be Mobile messaging for health programmes. Retrieved May 3, 2022 from https://www.who.int/initiatives/behealthy/bhbm-country-work.

  • WHO-ITC. (2022). mHealth for noncommunicable diseases: A guide for countries joining the mHealth program. Retrieved May 3, 2022 from https://www.itu.int/en/ITU-D/ICT-Applications/eHEALTH/Be_healthy/Documents/guide_for_countries-072013.pdf.

  • Williams, D. C., Warren, R. W., Ebeling, M., Andrews, A. L., & Teufel Ii, R. J. (2019). Physician use of electronic health records: Survey study assessing factors associated with provider reported satisfaction and perceived patient impact. JMIR Medical Informatics, 7(2), e10949. https://doi.org/10.2196/10949

    Article  Google Scholar 

  • Winfield, A. (2019). Ethical standards in robotics and AI. Nature Electronics, 2(2), 46–48.

    Article  Google Scholar 

  • Wulfovich, S., Rivas, H., & Matabuena, P. (2018). Drones in Healthcare. In H. Rivas, & K. Wac (Eds.), Digital Health. Health Informatics. Springer. https://doi.org/10.1007/978-3-319-61446-5_11.

  • Wulfovich, S., & Meyers, A. (Eds). (2020). Digital health entrepreneurship. Springer Nature.

    Google Scholar 

  • Yang, Y., Wu, L., Yin, G., Li, L., & Zhao, H. (2017). A survey on security and privacy issues in internet-of-things. IEEE Internet Things Journal, 4, 1250–2125.

    Article  Google Scholar 

  • Zangoei, S. (2016). Digital entrepreneurship criteria on the Amazon website. Karafan Quarterly Scientific Journal, 13(2), 49–62.

    Google Scholar 

  • Zajicek, H., & Meyers, A. (2018). Digital health entrepreneurship. In H. Rivas & K. Wac (Eds.), Digital health: Scaling healthcare to the world (pp. 271–288). Springer.

    Chapter  Google Scholar 

  • Zhao, F., Li, M., & Tsien, J. Z. (2015). Technology platforms for remote monitoring of vital signs in the new era of telemedicine. Expert Reviews of Medical Devices, 12(4), 411–429.

    Article  Google Scholar 

  • Zillner, S., Neururer, S. (2016). Big data in the health sector. In J. Cavanillas, E. Curry, & W. Wahlster (Eds.), New horizons for a data-driven economy. Springer. https://doi.org/10.1007/978-3-319-21569-3_10.

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kazeem Adeola Oshikoya .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Mohammed-Nasir, R., Oshikoya, K.A., Oreagba, I.A. (2023). Digital Innovation in Healthcare Entrepreneurship. In: Raimi, L., Oreagba, I.A. (eds) Medical Entrepreneurship. Springer, Singapore. https://doi.org/10.1007/978-981-19-6696-5_22

Download citation

Publish with us

Policies and ethics