Governance nell’innovazione: Sanità Digitale, Mobile Health, Big Data, Virtual Reality

Autori

  • Francesco Burrai SC Formazione, Ricerca e Cambiamento Organizzativo, ATS Sardegna, Sassari - Italy http://orcid.org/0000-0002-5912-1857
  • Valentina Micheluzzi Azienda Ospedaliero-Universitaria di Sassari, Sassari - Italy
  • Luigi Apuzzo Hospice Carlo Chenis, Asl Roma 4, Rome - Italy

DOI:

https://doi.org/10.33393/gcnd.2021.2240

Parole chiave:

Augmented Reality, Big Data, Digital Health, HTA, Mobile technology, Virtual Reality

Abstract

The introduction of modern Information and Communication Technologies (ICT) was one of the most remarkable innovations of recent decades. ICT brings with it a remarkable technological background that conveys all kinds of information and multimedia content with a significant change in human-technology interaction and significant implications also in the health sector. The constant process of digitization is increasingly affecting national health systems (SSN) and they turn out to be influenced by the process itself, where the literature shows itself in favor of the use of technologies in health, improving their effectiveness and efficiency. These include eHealth, Telemedicine, Electronic Health File, Big Data, Virtual Reality, Augmented Reality, ePrescription. The technologies allow, even remotely, to have an always active and direct contact, between the various professionals, and between professionals and users, and are also useful for the training of both healthcare professionals and users themselves. The use of technology in the healthcare sector should therefore be encouraged as it allows direct contacts between users and healthcare personnel, speed and correlation of data analysis, tracking, time and cost savings, reduction of errors and a positive environmental impact with a reduction in the use of printed paper. For all the points listed, the technological revolution in hospital and territorial care can no longer be postponed.

Riferimenti bibliografici

Marcolino MS, Oliveira JAQ, D’Agostino M, Ribeiro AL, Alkmim MBM, Novillo-Ortiz D. The Impact of mHealth Interventions: Systematic Review of Systematic Reviews. JMIR Mhealth Uhealth. 2018;6(1):e23. https://doi.org/10.2196/mhealth.8873 PMID:29343463

Gordon WJ, Landman A, Zhang H, Bates DW. Beyond validation: getting health apps into clinical practice. NPJ Digit Med. 2020;3(1):14. https://doi.org/10.1038/s41746-019-0212-z PMID:32047860

Davis J, Morgans A, Stewart J. Developing an Australian health and aged care research agenda: a systematic review of evidence at the subacute interface. Aust Health Rev. 2016;40(4):420-427. https://doi.org/10.1071/AH15005 PMID:26536066

Huxley CJ, Atherton H, Watkins JA, Griffiths F. Digital communication between clinician and patient and the impact on marginalised groups: a realist review in general practice. Br J Gen Pract. 2015;65(641):e813-e821. https://doi.org/10.3399/bjgp15X687853 PMID:26622034

Partel K. Toward better implementation: Australia's My Health Record. 2015. Available at https://ahha.asn.au/system/files/docs/publications/deeble_institute_issues_brief_no_13_partel_toward_better_implementation_my_health_record.pdf (accessed february 02, 2021).

Decreto 02 novembre 2011. https://www.trovanorme.salute.gov.it/norme/dettaglioAtto?id=40581 (accessed february 02, 2021).

Bragazzi NL, Damiani G, Martini M. From Rheumatology 1.0 to Rheumatology 4.0 and beyond: the contributions of Big Data to the field of rheumatology. Mediterr J Rheumatol. 2019;30(1):3-6. https://doi.org/10.31138/mjr.30.1.3 PMID:31938766

Dini G, Bragazzi NL, Montecucco A, Toletone A, Debarbieri N, Durando P. Big Data in occupational medicine: the convergence of -omics sciences, participatory research and e-health. Med Lav. 2019;110(2):102-114. PMID:30990472

Bragazzi NL, Guglielmi O, Garbarino S. SleepOMICS: How Big Data Can Revolutionize Sleep Science. Int J Environ Res Public Health. 2019;16(2):291. https://doi.org/10.3390/ijerph16020291PMID:30669659

Gianfredi V, Bragazzi NL, Nucci D, et al. Harnessing Big Data for Communicable Tropical and Sub-Tropical Disorders: Implications From a Systematic Review of the Literature. Front Public Health. 2018;6:90. https://doi.org/10.3389/fpubh.2018.00090 PMID:29619364

Bragazzi NL, Gianfredi V, Villarini M, et al. Vaccines Meet Big Data: State-of-the-Art and Future Prospects. From the Classical 3Is (“Isolate-Inactivate-Inject”) Vaccinology 1.0 to Vaccinology 3.0, Vaccinomics, and Beyond: A Historical Overview. Front Public Health. 2018;6:62. https://doi.org/10.3389/fpubh.2018.00062 PMID:29556492

Bragazzi NL, Dini G, Toletone A, Brigo F, Durando P. Leveraging Big Data for Exploring Occupational Diseases-Related Interest at the Level of Scientific Community, Media Coverage and Novel Data Streams: The Example of Silicosis as a Pilot Study. PLoS One. 2016;11(11):e0166051. https://doi.org/10.1371/journal.pone.0166051 PMID:27806115

Weersma RK, Xavier RJ, Vermeire S, et al; IBD Multi Omics Consortium. Multiomics analyses to deliver the most effective treatment to every patient with inflammatory bowel disease. Gastroenterology. 2018;155(5):e1-e4. https://doi.org/10.1053/j.gastro.2018.07.039PMID:30077628

Gligorijević V, Pržulj N. Methods for biological data integration: perspectives and challenges. J R Soc Interface. 2015;12(112):20150571. https://doi.org/10.1098/rsif.2015.0571 PMID:26490630

Mashamba-Thompson TP, Crayton ED. Blockchain and Artificial Intelligence Technology for Novel Coronavirus Disease-19 Self-Testing. Diagnostics (Basel). 2020;10(4):198. https://doi.org/10.3390/diagnostics10040198 PMID:32244841

Bhattacharya S, Singh A, Hossain MM. Strengthening public health surveillance through blockchain technology. AIMS Public Health. 2019;6(3):326-333. https://doi.org/10.3934/publichealth.2019.3.326 PMID:31637281

Chattu VK, Nanda A, Chattu SK, Kadri SM, Knight AW. The Emerging Role of Blockchain Technology Applications in Routine Disease Surveillance Systems to Strengthen Global Health Security. Big Data Cogn Comput. 2019;3(2):25. https://doi.org/10.3390/bdcc3020025

Korcsmaros T, Schneider MV, Superti-Furga G. Next generation of network medicine: interdisciplinary signaling approaches. Integr Biol. 2017;9(2):97-108. https://doi.org/10.1039/c6ib00215c PMID:28106223

Sheehan D, Shanahan F. The gut microbiota in inflammatory bowel disease. Gastroenterol Clin North Am. 2017;46(1):143-154. https://doi.org/10.1016/j.gtc.2016.09.011 PMID: 28164847

Kay M, Santos J, Takane M. Mhealth: New Horizons for Health Through Mobile Technologies. Geneva, Switzerland: World Health Organization; 2011.

Marzano L, Bardill A, Fields B, et al. The application of mHealth to mental health: opportunities and challenges. Lancet Psychiatry. 2015;2(10):942-948. https://doi.org/10.1016/S2215-0366(15)00268-0 PMID:26462228

Fiordelli M, Diviani N, Schulz PJ. Mapping mHealth research: a decade of evolution. J Med Internet Res. 2013;15(5):e95. https://doi.org/10.2196/jmir.2430 PMID:23697600

Cortez NG, Cohen IG, Kesselheim AS. FDA regulation of mobile health technologies. N Engl J Med. 2014;371(4):372-379. https://doi.org/10.1056/NEJMhle1403384 PMID:25054722

Matricardi PM, Dramburg S, Alvarez-Perea A, et al. The role of mobile health technologies in allergy care: an EAACI position paper. Allergy. 2020;75(2):259-272. https://doi.org/10.1111/all.13953 PMID:31230373

Imtiaz R, Atkinson K, Guerinet J, Wilson K, Leidecker J, Zimmerman D. A pilot study of OkKidney, a phosphate counting application in patients on peritoneal dialysis. 2017;37:613-618. PMID 28970367. https://doi.org/10.3747/pdi.2017.00050

Stark S, Snetselaar L, Piraino B, et al. Personal digital assistant-based self-monitoring adherence rates in 2 dialysis dietary intervention pilot studies: BalanceWise-HD and BalanceWise-PD. J Ren Nutr. 2011;21(6):492-498. https://doi.org/10.1053/j.jrn.2010.10.026PMID:21420316

Kiberd J, Khan U, Stockman C, et al. Effectiveness of a web-based eHealth portal for delivery of care to home dialysis patients: A single-arm pilot study. 2018. https://doi.org/10.1177/2054358118794415

Han M, Williams S, Mendoza M, et al. Quantifying physical activity levels and sleep in hemodialysis patients using a commercially available activity tracker. 2016;41:194-204. https://doi.org/10.1159/000441314

Sieverdes JC, Raynor PA, Armstrong T, Jenkins CH, Sox LR, Treiber FA. Attitudes and perceptions of patients on the kidney transplant waiting list toward mobile health-delivered physical activity programs. 2015;25:26-34. https://doi.org/10.7182/pit2015884

Lew SQ, Sikka N. Telehealth awareness in a US urban peritoneal dialysis clinic: From 2018 to 2019. Perit Dial Int 2020;40:227-229. https://doi.org/10.1177/0896860819893560 PMID: 32067558

Lew SQ, Sikka N. Are patients prepared to use telemedicine in home peritoneal dialysis programs? 2013;33:714-715. pmid:24335134. https://doi.org/10.3747/pdi.2012.00203

Burns T, Fernandez R, Stephens M. The experiences of adults who are on dialysis and waiting for a renal transplant from a deceased donor: a systematic review. JBI Database System Rev Implement Rep. 2015;13(2):169-211. https://doi.org/10.11124/jbisrir-2015-1973 PMID: 26447040

Chaturvedi A. Top 10 Popular Smartphone Apps to Track COVID-19; 2020. Available from: https://www.geospatialworld.net/blogs/popular-apps-covid-19/ (last accessed may 01, 2020).

Centers for Disease Control and Prevention, Testing for COVID-19. 2020. Available from: https://www.cdc.gov/coronavirus/2019-ncov/symptoms-testing/testing.html (last accessed may 01, 2020).

World Health Organization. WHO Launches a Chatbot on Facebook Messenger to Combat COVID-19 misinformation; 2020. Available from: https://www.who.int/news-room/feature-stories/detail/who -launches-a-chatbot-powered-facebook-messenger-to-combat-covid-19-misinformation (accessed february 02, 2021).

Google Cloud, Rapid Response Virtual Agent. https://cloud.google.com/solutions/contact-center/covid19-rapid-response (accessed february 02, 2021)

International Business Machines Corporation, IBM Watson Assistant Deliver Fast, Accurate Answers around COVID-19 for your Customers, Employees and Citizens-on any Channel; 2020. Available from: https://www.ibm.com/in-en/watson/covid-response

Fighting against COVID-19. https://www.reddit.com/r/pcmasterrace/comments/fhb5e4/coronavirus_specific_gpu_projects_are_now (accessed february 02, 2021).

O'Grady C, Melia R, Bogue J, O'Sullivan M, Young K, Duggan J. A Mobile Health Approach for Improving Outcomes in Suicide Prevention (SafePlan). J Med Internet Res 2020;22(7):e17481. https://doi.org/10.2196/17481 PMID: 32729845

International Organization for Standardization. Ergonomic requirements for office work with visual display terminals (VDTs) Part 11 Guidance on usability. Geneva: ISO; 1998.

Baysari MT, Westbrook JI. Mobile Applications for Patient-centered Care Coordination: A Review of Human Factors Methods Applied to their Design, Development, and Evaluation. Yearb Med Inform. 2015;10(1):47-54. PMID:26293851

Wildenbos GA, Peute LW, Jaspers MW. Influence of human factor issues on patient-centered mHealth apps' impact; Where do we stand. Stud Health Technol Inform. 2016;228:190-4. https://doi.org/10.3233/978-1-61499-678-1-190 PMID: 27577369

Bernier A, Fedele D, Guo Y, et al. New-Onset Diabetes Educator to Educate Children and Their Caregivers About Diabetes at the Time of Diagnosis: usability Study. JMIR Diabetes. 2018;3(2):e10. https://doi.org/10.2196/diabetes.9202 PMID:30291069

Janatkhah R, Tabari-Khomeiran R, Asadi-Louyeh A, Kazemnejad E. Usability of a Disease Management Mobile Application as Perceived by Patients With Diabetes. Comput Inform Nurs. 2019;37(8):413-419. https://doi.org/10.1097/CIN.0000000000000532 PMID:31394560

Pérez-Gandía C, García-Sáez G, Subías D, et al. Decision Support in Diabetes Care: The Challenge of Supporting Patients in Their Daily Living Using a Mobile Glucose Predictor. J Diabetes Sci Technol. 2018;12(2):243-250. https://doi.org/10.1177/1932296818761457PMID:29493361

Giordanengo A, Årsand E, Woldaregay AZ, et al. Design and Prestudy Assessment of a Dashboard for Presenting Self-Collected Health Data of Patients With Diabetes to Clinicians: Iterative Approach and Qualitative Case Study. JMIR Diabetes. 2019;4(3):e14002. https://doi.org/10.2196/14002 PMID:31290396

Isaković M, Sedlar U, Volk M, Bešter J. Usability Pitfalls of Diabetes mHealth Apps for the Elderly. J Diabetes Res. 2016;2016:1604609. https://doi.org/10.1155/2016/1604609PMID:27034957

VHA kidney Program. https://www.va.gov/health/services/renal/ (last accessed march 14, 2021).

Beste LA, Mattox EA, Pichler R, et al. Primary Care Team Members Report Greater Individual Benefits from Long- Versus Short-Term Specialty Telemedicine Mentorship. Telemed J E Health. 2016;22(8):699-706. https://doi.org/10.1089/tmj.2015.0185 PMID:26959098

Forbes RC, Broman KK, Johnson TB, et al. Implementation of telehealth is associated with improved timeliness to kidney transplant waitlist evaluation. J Telemed Telecare. 2018;24(7):485-491. https://doi.org/10.1177/1357633X17715526 PMID:28649902

Rohatgi R, Ross MJ, Majoni SW. Telenephrology: current perspectives and future directions. Kidney Int. 2017;92(6):1328-1333. https://doi.org/10.1016/j.kint.2017.06.032 PMID:28893419

Ishani A, Christopher J, Palmer D, et al; Center for Innovative Kidney Care. Telehealth by an Interprofessional Team in Patients With CKD: A Randomized Controlled Trial. Am J Kidney Dis. 2016;68(1):41-49. https://doi.org/10.1053/j.ajkd.2016.01.018 PMID:26947216

Jensen PB, Jensen LJ, Brunak S. Mining electronic health records: towards better research applications and clinical care. Nat Rev Genet. 2012;13(6):395-405. https://doi.org/10.1038/nrg3208 PMID:22549152

Pons E, Braun LM, Hunink MG, Kors JA. Natural language processing in radiology: a systematic review. Radiology. 2016;279(2):329-343. https://doi.org/10.1148/radiol.16142770PMID:27089187

Rizzetto F, Bernareggi A, Rantas S, Vanzulli A, Vertemati M. Immersive Virtual Reality in surgery and medical education: diving into the future. Am J Surg. 2020;220(4):856-857. https://doi.org/10.1016/j.amjsurg.2020.04.033 PMID:32386709

Huber T, Wunderling T, Paschold M, Lang H, Kneist W, Hansen C. Highly immersive virtual reality laparoscopy simulation: development and future aspects. Int J CARS. 2018;13(2):281-290. https://doi.org/10.1007/s11548-017-1686-2 PMID:29151194

Fasel JH, Aguiar D, Kiss-Bodolay D, et al. Adapting anatomy teaching to surgical trends: a combination of classical dissection, medical imaging, and 3D-printing technologies. Surg Radiol Anat. 2016;38(3):361-367. https://doi.org/10.1007/s00276-015-1588-3 PMID:26553051

Damewood RB, Blair PG, Park YS, Lupi LK, Newman RW, Sachdeva AK. “Taking Training to the Next Level”: The American College of Surgeons Committee on Residency Training Survey. J Surg Educ. 2017;74(6):e95-e105. https://doi.org/10.1016/j.jsurg.2017.07.008 PMID:28781132

Parkhomenko E, O’Leary M, Safiullah S, et al. Pilot Assessment of Immersive Virtual Reality Renal Models as an Educational and Preoperative Planning Tool for Percutaneous Nephrolithotomy. J Endourol. 2019;33(4):283-288. https://doi.org/10.1089/end.2018.0626PMID:30460860

Bernardo A. Virtual Reality and Simulation in Neurosurgical Training. World Neurosurg. 2017;106:1015-1029. https://doi.org/10.1016/j.wneu.2017.06.140 PMID:28985656

Lee C, Wong GKC. Virtual reality and augmented reality in the management of intracranial tumors: A review. J Clin Neurosci. 2019;62:14-20. https://doi.org/10.1016/j.jocn.2018.12.036PMID:30642663

Drouin S, Kochanowska A, Kersten-Oertel M, et al. IBIS: an OR ready open-source platform for image-guided neurosurgery. Int J CARS. 2017;12(3):363-378. https://doi.org/10.1007/s11548-016-1478-0 PMID:27581336

Pieterse AD, Huurman VAL, Hierck BP, Reinders MEJ. Introducing the innovative technique of 360° virtual reality in kidney transplant education. Transpl Immunol. 2018;49:5-6. https://doi.org/10.1016/j.trim.2018.03.001 PMID:29563056

Wake N, Nussbaum JE, Elias MI, Nikas CV, Bjurlin MA. 3D Printing, Augmented Reality, and Virtual Reality for the Assessment and Management of Kidney and Prostate Cancer: A Systematic Review. Urology. 2020;143:20-32. https://doi.org/10.1016/j.urology.2020.03.066PMID:32535076

Maggio MG, Latella D, Maresca G, et al. Virtual Reality and Cognitive Rehabilitation in People With Stroke: an Overview. J Neurosci Nurs. 2019;51(2):101-105. https://doi.org/10.1097/JNN.0000000000000423 PMID:30649091

Aramaki AL, Sampaio RF, Reis ACS, Cavalcanti A, Dutra FCMSE. Virtual reality in the rehabilitation of patients with stroke: an integrative review. Arq Neuropsiquiatr. 2019;77(4):268-278. https://doi.org/10.1590/0004-282x20190025 PMID:31090808

Semeraro F, Scapigliati A, Ristagno G, et al. Virtual Reality for CPR training: how cool is that? Dedicated to the “next generation”. Resuscitation. 2017;121:e1-e2. https://doi.org/10.1016/j.resuscitation.2017.09.024 PMID:28951295

McGrath JL, Taekman JM, Dev P, et al. Using Virtual Reality Simulation Environments to Assess Competence for Emergency Medicine Learners. Acad Emerg Med. 2018;25(2):186-195. https://doi.org/10.1111/acem.13308 PMID:28888070

Li C, Liang W, Quigley C, Zhao Y, Yu LF. Earthquake Safety Training through Virtual Drills. IEEE Trans Vis Comput Graph. 2017;23(4):1275-1284. https://doi.org/10.1109/TVCG.2017.2656958 PMID:28129163

Duan YY, Zhang JY, Xie M, Feng XB, Xu S, Ye ZW. Application of Virtual Reality Technology in Disaster Medicine. Curr Med Sci. 2019;39(5):690-693. https://doi.org/10.1007/s11596-019-2093-4. Erratum in: Curr Med Sci. 2020 Dec;40. 6.: 1205. PMID: 31612384. PMID:31612384

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Pubblicato

2021-04-14

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Burrai F, Micheluzzi V, Apuzzo L. Governance nell’innovazione: Sanità Digitale, Mobile Health, Big Data, Virtual Reality. G Clin Nefrol Dial [Internet]. 14 aprile 2021 [citato 24 ottobre 2021];33:42-50. Available at: https://journals.aboutscience.eu/index.php/gcnd/article/view/2240

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