Skip to main content
Have a personal or library account? Click to login
Digital Health: Opportunities and Challenges to Develop the Next-Generation Technology-Enabled Models of Cardiovascular Care Cover

Digital Health: Opportunities and Challenges to Develop the Next-Generation Technology-Enabled Models of Cardiovascular Care

Methodist DeBakey Cardiovascular Journal
Volume 16 (2020): Issue 4
By:   
Open Access
|Oct 2020
References

References

  1. Bhavnani SP Sitapati AM . Virtual Care 2.0-a Vision for the Future of Data-Driven Technology-Enabled Healthcare. Curr Treat Options Cardiovasc Med. 2019 Apr 15; 21( 5): 21.
    Search in Google ScholarBack to article
  2. Bhavnani SP , Narula J , Sengupta PP . Mobile technology and the digitization of healthcare. Eur Heart J. 2016 May 7; 37( 18): 1428– 38.
    Search in Google ScholarBack to article
  3. Topol EJ . High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019 Jan; 25( 1): 44– 56.
    Search in Google ScholarBack to article
  4. Sengupta PP Adjeroh DA . AI tracks a beating heart's function over time. Nature. 2020 Apr; 580( 7802): 192– 4.
    Search in Google ScholarBack to article
  5. Rock Health [Internet]. San Francisco, CA: Rock Health; c2020. 2019 Mid-year Digital Health Market Update: Exits are heating up; 2018 [cited 2020 Aug 3]. Available from: https://rockhealth.com/reports/2019-midyear-digital-health-market-update-exits-are-heating-up.
    Search in Google ScholarBack to article
  6. Bhavnani SP , Parakh K , Atreja A , . 2017 Roadmap for Innovation-ACC Health Policy Statement on Healthcare Transformation in the Era of Digital Health, Big Data, and Precision Health: A Report of the American College of Cardiology Task Force on Health Policy Statements and Systems of Care. J Am Coll Cardiol. 2017 Nov 28; 70( 21): 2696– 718.
    Search in Google ScholarBack to article
  7. Bhavnani SP Harzand A . From false-positives to technological Darwinism: controversies in digital health. Per Med. 2018 Jul 1; 15( 4): 247– 50.
    Search in Google ScholarBack to article
  8. Venkatesh V . Technology acceptance model and a research agenda on interventions. Decis Sci. 2008 May; 39( 2): 273– 315.
    Search in Google ScholarBack to article
  9. Michie S , Yardley L , West R , Patrick K , Greaves F . Developing and Evaluating Digital Interventions to Promote Behavior Change in Health and Health Care: Recommendations Resulting From an International Workshop. J Med Internet Res. 2017 Jun 29; 19( 6): e232.
    Search in Google ScholarBack to article
  10. Banbury A , Nancarrow S , Dart J , . Adding value to remote monitoring: Co-design of a health literacy intervention for older people with chronic disease delivered by telehealth - The telehealth literacy project. Patient Educ Couns. 2020 Mar; 103( 3): 597– 606.
    Search in Google ScholarBack to article
  11. Walsh DMJ , Moran K , Cornelissen V , . The development and codesign of the PATHway intervention: a theory-driven eHealth platform for the self-management of cardiovascular disease. Transl Behav Med. 2019 Jan 1; 9( 1): 76– 98.
    Search in Google ScholarBack to article
  12. Steventon A , Bardsley M , Billings J , .; Whole System Demonstrator Evaluation Team. Effect of telehealth on use of secondary care and mortality: findings from the Whole System Demonstrator cluster randomised trial. BMJ. 2012 Jun 21; 344: e3874.
    Search in Google ScholarBack to article
  13. Sanders C , Rogers A , Bowen R , . Exploring barriers to participation and adoption of telehealth and telecare within the Whole System Demonstrator trial: a qualitative study. BMC Health Serv Res. 2012 Jul 26; 12: 220.
    Search in Google ScholarBack to article
  14. Cruz-Martínez RR , Wentzel J , Asbjørnsen RA , . Supporting Self-Management of Cardiovascular Diseases Through Remote Monitoring Technologies: aMetaethnography Review of Frameworks, Models, and Theories Used in Research and Development. J Med Internet Res. 2020 May 21; 22( 5): e16157.
    Search in Google ScholarBack to article
  15. Abdolkhani R , Gray K , Borda A , DeSouza R . Patient-generated health data management and quality challenges in remote patient monitoring. JAMIA Open. 2019 Sep 20; 2( 4): 471– 8.
    Search in Google ScholarBack to article
  16. McManus RJ , Mant J , Franssen M , . Efficacy of self-monitored blood pressure, with or without telemonitoring, for titration of antihypertensive medication (TASMINH4): an unmasked randomised controlled trial. Lancet. 2018 Mar 10; 391( 10124): 949– 59.
    Search in Google ScholarBack to article
  17. Puhr S , Calhoun P , Welsh JB , Walker TC . The Effect of Reduced Self-Monitored Blood Glucose Testing After Adoption of Continuous Glucose Monitoring on Hemoglobin A1c and Time in Range. Diabetes Technol Ther. 2018 Aug; 20( 8): 557– 60.
    Search in Google ScholarBack to article
  18. Heywood JT , Jermyn R , Shavelle D , . Impact of Practice-Based Management of Pulmonary Artery Pressures in 2000 Patients Implanted With the CardioMEMS Sensor. Circulation. 2017 Apr 18; 135( 16): 1509– 17.
    Search in Google ScholarBack to article
  19. Desai AS , Bhimaraj A , Bharmi R , . Ambulatory Hemodynamic Monitoring Reduces Heart Failure Hospitalizations in “Real-World” Clinical Practice. J Am Coll Cardiol. 2017 May 16; 69( 19): 2357– 65.
    Search in Google ScholarBack to article
  20. Banda JM , Seneviratne M , Hernandez-Boussard T , Shah NH . Advances in Electronic Phenotyping: From Rule-Based Definitions to Machine Learning Models. Annu Rev Biomed Data Sci. 2018 Jul; 1: 53– 68.
    Search in Google ScholarBack to article
  21. Shickel B , Tighe PJ , Bihorac A , Rashidi P . Deep EHR: A Survey of Recent Advances in Deep Learning Techniques for Electronic Health Record (EHR) Analysis. IEEE J Biomed Health Inform. 2018 Sep; 22( 5): 1589– 604.
    Search in Google ScholarBack to article
  22. Tokodi M , Shrestha S , Bianco C , . Interpatient Similarities in Cardiac Function: A Platform for Personalized Cardiovascular Medicine. JACC Cardiovasc Imaging. 2020 May; 13( 5): 1119– 32.
    Search in Google ScholarBack to article
  23. Guo Q , Lu X , Gao Y , . Cluster analysis: a new approach for identification of underlying risk factors for coronary artery disease in essential hypertensive patients. Sci Rep. 2017 Mar 7; 7: 43965.
    Search in Google ScholarBack to article
  24. Shameer K , Badgeley MA , Miotto R , Glicksberg BS , Morgan JW , Dudley JT . Translational bioinformatics in the era of real-time biomedical, health care and wellness data streams. Brief Bioinform. 2017 Jan; 18( 1): 105– 24.
    Search in Google ScholarBack to article
  25. Miotto R , Li L , Kidd BA , Dudley JT . Deep Patient: An Unsupervised Representation to Predict the Future of Patients from the Electronic Health Records. Sci Rep. 2016 May 17; 6: 26094.
    Search in Google ScholarBack to article
  26. Badgeley MA , Shameer K , Glicksberg BS , . EHDViz: clinical dashboard development using open-source technologies. BMJ Open. 2016 Mar 24; 6( 3): e010579.
    Search in Google ScholarBack to article
  27. Gianfrancesco MA , Tamang S , Yazdany J , Schmajuk G . Potential Biases in Machine Learning Algorithms Using Electronic Health Record Data. JAMA Intern Med. 2018 Nov 1; 178( 11): 1544– 7.
    Search in Google ScholarBack to article
  28. Obermeyer Z , Powers B , Vogeli C , Mullainathan S . Dissecting racial bias in an algorithm used to manage the health of populations. Science. 2019 Oct 25; 366( 6464): 447– 53.
    Search in Google ScholarBack to article
  29. Betancourt JA , Rosenberg MA , Zevallos A , Brown JR , Mileski M . The Impact of COVID-19 on Telemedicine Utilization Across Multiple Service Lines in the United States. Health care (Basel). 2020 Oct 1; 8( 4): E380.
    Search in Google ScholarBack to article
  30. Yancy CW . COVID-19 and African Americans. JAMA. 2020 May 19; 323( 19): 1891– 2.
    Search in Google ScholarBack to article
  31. Eberly LA , Khatana SAM , Nathan AS , . Telemedicine Outpatient Cardiovascular Care during the COVID-19 Pandemic: Bridging or Opening the Digital Divide? Circulation. 2020 Aug 4; 142( 5): 510– 512.
    Search in Google ScholarBack to article
  32. Bhavnani SP , Sola S , Adams D , Venkateshvaran A , Dash PK , Sengupta PP ; ASEF-VALUES Investigators. A Randomized Trial of Pocket-Echocardiography Integrated Mobile Health Device Assessments in Modern Structural Heart Disease Clinics. JACC Cardiovasc Imaging. 2018 Apr; 11( 4): 546– 57.
    Search in Google ScholarBack to article
  33. Kichloo A , Albosta M , Dettloff K , . Telemedicine, the current COVID-19 pandemic, and the future: a narrative review and perspectives moving forward in the USA. Fam Med Community Health. 2020 Aug; 8( 3): e000530.
    Search in Google ScholarBack to article
  34. Bandodkar AJ Wang J . Non-invasive wearable electrochemical sensors: a review. Trends Biotechnol. 2014 Jul; 32( 7): 363– 71.
    Search in Google ScholarBack to article
  35. Keum DH , Kim SK , Koo J , . Wireless smart contact lens for diabetic diagnosis and therapy. Sci Adv. 2020 Apr 24; 6( 17): eaba3252.
    Search in Google ScholarBack to article
  36. Boutry CM , Nguyen A , Lawal QO , Chortos A , Rondeau-Gagné S , Bao Z . A Sensitive and Biodegradable Pressure Sensor Array for Cardiovascular Monitoring. Adv Mater. 2015 Nov 18; 27( 43): 6954– 61.
    Search in Google ScholarBack to article
  37. Goverdovsky V , von Rosenberg W , Nakamura T , . Hearables: Multimodal physiological in-ear sensing. Sci Rep. 2017 Jul 31; 7( 1): 6948.
    Search in Google ScholarBack to article
DOI: https://doi.org/10.14797/mdcj-16-4-296 | Journal eISSN: 1947-6108
Journal RSS Feed
Language: English
Page range: 296 - 303
Published on: Oct 1, 2020
Published by: Houston Methodist DeBakey Heart & Vascular Center
In partnership with: Paradigm Publishing Services
Keywords:
digital health,
remote patient monitoring,
clinical decision support,
electronic phenotyping,
data analytics

© 2020 Sanjeev P. Bhavnani, published by Houston Methodist DeBakey Heart & Vascular Center
This work is licensed under the Creative Commons Attribution-NonCommercial 4.0 License.

Volume 16 (2020): Issue 4
Previous article
Next article