Download PDF
CC BY-NC-ND 4.0 · Yearb Med Inform 2021; 30(01): 061-068
DOI: 10.1055/s-0041-1726491
Special Section: Managing Pandemics with Health Informatics
Working Group Contributions

How to Improve Information Technology to Support Healthcare to Address the COVID-19 Pandemic: an International Survey with Health Informatics Experts

Max Topaz
1   School of Nursing, Columbia University, New York, USA
,
Laura-Maria Peltonen
2   Department of Nursing Science, University of Turku, Finland
,
James Mitchell
3   School of Computing and Mathematics, Keele University, UK
,
Dari Alhuwail
4   Information Science Department, Kuwait University, Kuwait
5   Health Informatics Unit, Dasman Diabetes Institute, Kuwait
,
Seyedeh-Samin Barakati
6   Daphne Cockwell School of Nursing, Ryerson University, Toronto, Canada
,
Adrienne Lewis
7   Splatsin Health Services, Enderby, BC, Canada
,
Hans Moen
8   Department of Future Technologies, University of Turku, Finland
,
Sai Pavan Kumar Veeranki
9   Health & Bioresources/Molecular Diagnostics, AIT Austrian Institute of Technology GmbH, Graz, Austria
10   Technical University of Graz, Graz, Austria
,
Lori Block
11   School of Nursing, University of British Columbia Vancouver, BC, Canada
,
Tracie Risling
12   College of Nursing, University of Saskatchewan, Saskatoon, SK, Canada
,
Charlene Ronquillo
6   Daphne Cockwell School of Nursing, Ryerson University, Toronto, Canada
11   School of Nursing, University of British Columbia Vancouver, BC, Canada
› Author Affiliations
› Further Information
   Permissions and Reprints

Summary

Objectives: To identify the ways in which healthcare information and communication technologies can be improved to address the challenges raised by the COVID-19 pandemic.

Methods: The study population included health informatics experts who had been involved with the planning, development and deployment of healthcare information and communication technologies in healthcare settings in response to the challenges presented by the COVID-19 pandemic. Data were collected via an online survey. A non-probability convenience sampling strategy was employed. Data were analyzed with content analysis.

Results: A total of 65 participants from 16 countries responded to the conducted survey. The four major themes regarding recommended improvements identified from the content analysis included: improved technology availability, improved interoperability, intuitive user interfaces and adoption of standards of care. Respondents also identified several key healthcare information and communication technologies that can help to provide better healthcare to patients during the COVID-19 pandemic, including telehealth, advanced software, electronic health records, remote work technologies (e.g., remote desktop computer access), and clinical decision support tools.

Conclusions: Our results help to identify several important healthcare information and communication technologies, recommended by health informatics experts, which can help to provide better care to patients during the COVID-19 pandemic. The results also highlight the need for improved interoperability, intuitive user interfaces and advocating the adoption of standards of care.

Keywords

Health Informatics - COVID-19 - international survey - telehealth


Publication History

Article published online:
21 April 2021

© 2021. IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/)

Georg Thieme Verlag KG
Rüdigerstraße 14, 70469 Stuttgart, Germany

 

  • References

  • 1 Turale S, Meechamnan C, Kunaviktikul W. Challenging times: ethics, nursing and the COVID-19 pandemic. Int Nurs Rev 2020; 67 (02) 164-7
    CrossrefPubMedGoogle Scholar
  • 2 Ng K, Poon BH, KiatPuar TH, ShanQuah JL, Loh WJ, Wong YJ. et al. COVID-19 and the Risk to Health Care Workers: A Case Report. Ann Intern Med 2020; 172 (11) 766-7
    CrossrefPubMedGoogle Scholar
  • 3 Gordon AL, Goodman C, Achterberg W, Barker RO, Burns E, Hanratty B. et al. Commentary: COVID in care homes-challenges and dilemmas in healthcare delivery. Age Ageing 2020; 49 (05) 701-5
    CrossrefPubMedGoogle Scholar
  • 4 Moazzami B, Razavi-Khorasani N, DooghaieMoghadam A, Farokhi E, Rezaei N. COVID-19 and telemedicine: Immediate action required for maintaining healthcare providers well-being. J Clin Virol 2020; 126: 104345
    CrossrefPubMedGoogle Scholar
  • 5 Zerbini G, Ebigbo A, Reicherts P, Kunz M, Messman H. Psychosocial burden of healthcare professionals in times of COVID-19 - a survey conducted at the University Hospital Augsburg. Ger Med Sci 2020; 18: Doc05
    CrossrefPubMedGoogle Scholar
  • 6 Arcadi P, Simonetti V, Ambrosca R, Cicolini G, Simeone S, Pucciarelli G. et al. Nursing during the COVID-19 outbreak: a phenomenological study. J Nurs Manag 2021
    PubMedGoogle Scholar
  • 7 Nagesh S, Chakraborty S. Saving the frontline health workforce amidst the COVID-19 crisis: Challenges and recommendations. J Glob Health 2020; 10 (01) 010345
    CrossrefPubMedGoogle Scholar
  • 8 Ranney ML, Griffeth V, Jha AK. Critical Supply Shortages - The Need for Ventilators and Personal Protective Equipment during the Covid-19 Pandemic. N Engl J Med 2020; 382 (18) e41
    CrossrefPubMedGoogle Scholar
  • 9 Kang JY, Michels A, Lyu F, Wang S, Agbodo N, Freeman VL. et al. Rapidly measuring spatial accessibility of COVID-19 healthcare resources: a case study of Illinois, USA. Int J Health Geogr 2020; 19 (01) 36
    CrossrefPubMedGoogle Scholar
  • 10 Farrell TW, Francis L, Brown T, Ferrante LE, Widera E, Rhodes R. et al. Rationing Limited Healthcare Resources in the COVID-19 Era and Beyond: Ethical Considerations Regarding Older Adults. J Am Geriatr Soc 2020; 68 (06) 1143-9
    CrossrefPubMedGoogle Scholar
  • 11 Bos˘koski I, Gallo C, Wallace MB, Costamagna G. COVID-19 pandemic and personal protective equipment shortage: protective efficacy comparing masks and scientific methods for respirator reuse. Gastrointest Endosc 2020; 92 (03) 519-23
    CrossrefPubMedGoogle Scholar
  • 12 The Lancet. COVID-19: protecting health-care workers. Lancet 2020; 395 (10228): 922
    CrossrefPubMedGoogle Scholar
  • 13 Scott BK, Miller GT, Fonda SJ, Yeaw RE, Gaudaen JC, Pavliscsak HH. et al. Advanced Digital Health Technologies for COVID-19 and Future Emergencies. Telemed J E Health 2020; 26 (10) 1226-33
    CrossrefPubMedGoogle Scholar
  • 14 Ye J. The Role of Health Technology and Informatics in a Global Public Health Emergency: Practices and Implications From the COVID-19 Pandemic. JMIR Med Inform 2020; 8 (07) e19866
    CrossrefPubMedGoogle Scholar
  • 15 Vaishya R, Javaid M, Khan IH, Haleem A. Artificial Intelligence (AI) applications for COVID-19 pandemic. Diabetes Metab Syndr 2020; 14 (04) 337-9
    CrossrefPubMedGoogle Scholar
  • 16 James HM, Papoutsi C, Wherton J, Greenhalgh T, Shaw SE. Spread, Scale-up, and Sustainability of Video Consulting in Health Care: Systematic Review and Synthesis Guided by the NASSS Framework. J Med Internet Res 2021; 23 (01) e23775
    CrossrefPubMedGoogle Scholar
  • 17 Bokolo AJ. Exploring the adoption of telemedicine and virtual software for care of outpatients during and after COVID-19 pandemic. Ir J Med Sci 2021; 190 (01) 1-10
    CrossrefPubMedGoogle Scholar
  • 18 Li Z, Chen Q, Feng L, Rodewald L, Xia Y, Yu H. et al. China CDC COVID-19 Emergency Response Strategy Team. Active case finding with case management: the key to tackling the COVID-19 pandemic. Lancet 2020; 396 (10243): 63-70
    CrossrefPubMedGoogle Scholar
  • 19 Cheng W, Hao C. Case-Initiated COVID-19 Contact Tracing Using Anonymous Notifications. JMIR Mhealth Uhealth 2020; 8 (06) e20369
    CrossrefPubMedGoogle Scholar
  • 20 Budd J, Miller BS, Manning EM, Lampos V, Zhuang M, Edelstein M. et al. Digital technologies in the public-health response to COVID-19. Nat Med 2020; 26 (08) 1183-92
    CrossrefPubMedGoogle Scholar
  • 21 Khan H, Kushwah KK, Singh S, Urkude H, Maurya MR, Sadasivuni KK. Smart technologies driven approaches to tackle COVID-19 pandemic: a review. 3 Biotech 2021; 11 (02) 50
    CrossrefPubMedGoogle Scholar
  • 22 Clipper B. The Influence of the COVID-19 Pandemic on Technology: Adoption in Health Care. Nurse Lead 2020; 18 (05) 500-3
    CrossrefPubMedGoogle Scholar
  • 23 Uohara MY, Weinstein JN, Rhew DC. The Essential Role of Technology in the Public Health Battle Against COVID-19. Popul Health Manag 2020; 23 (05) 361-7
    CrossrefPubMedGoogle Scholar
  • 24 Syeda HB, Syed M, Sexton KW, Syed S, Begum S, Syed F. et al. Role of Machine Learning Techniques to Tackle the COVID-19 Crisis: Systematic Review. JMIR Med Inform 2021; 9 (01) e23811
    CrossrefPubMedGoogle Scholar
  • 25 HL7 FHIR Foundation. Welcome to the HL7 FHIR Foundation [Internet]. 2021 [cited January 30, 2021]. Available from: http://www.fhir.org/
    PubMed
  • 26 openEHR Foundation. What is openEHR? [Internet]. 2021 [cited January 30, 2021]. Available from https://openehr.org/
    PubMed
  • 27 SNOMED International. SNOMED International determines global standards for health terms, an essential part of improving the health of humankind [Internet]. 2021 [cited January 30, 2021]. Available from: https://www.snomed.org/
    PubMed
  • 28 Schulz S, Stegwee R, Chronaki C, . Standards in Healthcare Data. In: Kubben P, Dumontier M, Dekker A. editors. Fundamentals of Clinical Data Science. Cham: Springer; 2019: 19-36
    CrossrefGoogle Scholar
  • 29 Marcilly R, Schiro J, Beuscart-Zéphir MC, Magrabi F. Building Usability Knowledge for Health Information Technology: A Usability-Oriented Analysis of Incident Reports. Appl Clin Inform 2019; 10 (03) 395-408
    Article in Thieme ConnectPubMedGoogle Scholar
  • 30 Carayon P, Xie A, Kianfar S. Human factors and ergonomics as a patient safety practice. BMJ Qual Saf 2014; 23 (03) 196-205
    CrossrefPubMedGoogle Scholar
  • 31 Avanesova AA, Shamliyan TA. Worldwide implementation of telemedicine programs in association with research performance and health policy. Health Policy Technol 2019; 8 (02) 179-91
    CrossrefPubMedGoogle Scholar
  • 32 Feild L, Pruchno RA, Bewley J, Lemay Jr EP, Levinsky NG. Using probability vs. nonprobability sampling to identify hard-to-access participants for health-related research: costs and contrasts. J Aging Health 2006; 18 (04) 565-83
    CrossrefPubMedGoogle Scholar
  • 33 Etikan I, Bala K. Sampling and sampling methods. Biom Biostat Int J 2017; 5 (06) 00149
    PubMedGoogle Scholar
  • 34 Dillman DA, Smyth JD, Christian LM. Internet, phone, mail, and mixed-mode surveys: the tailored design method. N.Y.: John Wiley & Sons; 2014
    Google Scholar
  • 35 Dillman DA. Mail and Internet surveys: The tailored design method--2007 Update with new Internet, visual, and mixed-mode guide. N.Y.: John Wiley & Sons; 2011
    Google Scholar
  • 36 Reja U, Manfreda KL, Hlebec V, Vehovar V. Open-ended vs. close-ended questions in web questionnaires. Developments in applied statistics 2003; 19 (01) 159-77
    PubMedGoogle Scholar
  • 37 Elo S, Kyngäs H. The qualitative content analysis process. J Adv Nurs 2008; 62 (01) 107-15
    CrossrefPubMedGoogle Scholar
  • 38 Atreja A, Gordon SM, Pollock DA, Olmsted RN, Brennan PJ. Healthcare Infection Control Practices Advisory Committee. Opportunities and challenges in utilizing electronic health records for infection surveillance, prevention, and control. Am J Infect Control 2008; 36 (3 Suppl): S37-46
    CrossrefPubMedGoogle Scholar
  • 39 Ohannessian R, Duong TA, Odone A. Global Telemedicine Implementation and Integration Within Health Systems to Fight the COVID-19 Pandemic: A Call to Action. JMIR Public Health Surveill 2020; 6 (02) e18810
    CrossrefPubMedGoogle Scholar
  • 40 Lee D, Moy N, Tritter J, Paolucci F. The COVID-19 pandemic: Global health policy and technology responses in the making. Health Policy Technol 2020; 9 (04) 397-8
    CrossrefPubMedGoogle Scholar
  • 41 Fisk M, Livingstone A, Pit SW. Telehealth in the Context of COVID-19: Changing Perspectives in Australia, the United Kingdom, and the United States. J Med Internet Res 2020; 22 (06) e19264
    CrossrefPubMedGoogle Scholar
  • 42 Atique S, Bautista JR, Block LJ, Lee JJ, Lozada-Perezmitre E, Nibber R. et al. A nursing informatics response to COVID-19: Perspectives from five regions of the world. J Adv Nurs 2020; 76 (10) 2462-8
    CrossrefPubMedGoogle Scholar
  • 43 Han E, Tan MMJ, Turk E, Sridhar D, Leung GM, Shibuya K. et al. Lessons learnt from easing COVID-19 restrictions: an analysis of countries and regions in Asia Pacific and Europe. Lancet 2020; 396 (10261): 1525-34
    CrossrefPubMedGoogle Scholar
  • 44 Whitelaw S, Mamas MA, Topol E, VanSpall HGC. Applications of digital technology in COVID-19 pandemic planning and response. Lancet Digit Health 2020; 2 (08) e435-e440
    CrossrefPubMedGoogle Scholar
  • 45 Monaghesh E, Hajizadeh A. The role of telehealth during COVID-19 outbreak: a systematic review based on current evidence. BMC Public Health 2020; 20 (01) 1193
    CrossrefPubMedGoogle Scholar
  • 46 Krausz M, Westenberg JN, Vigo D, Spence RT, Ramsey D. Emergency Response to COVID-19 in Canada: Platform Development and Implementation for eHealth in Crisis Management. JMIR Public Health Surveill 2020; 6 (02) e18995
    CrossrefPubMedGoogle Scholar
  • 47 Bauer DC, Metke-Jimenez A, Maurer-Stroh S, Tiruvayipati S, Wilson LOW, Jain Y. et al. Interoperable medical data: the missing link for understanding COVID-19. Transbound Emerg Dis 2020
    PubMedGoogle Scholar
  • 48 O’Reilly-Shah VN, Gentry KR, VanCleve W, Kendale SM, Jabaley CS, Long DR. The COVID-19 Pandemic Highlights Shortcomings in US Health Care Informatics Infrastructure: A Call to Action. Anesth Analg 2020; 131 (02) 340-4
    CrossrefPubMedGoogle Scholar
  • 49 Mostashari F, McClellan MB. White paper: Data Interoperability and Exchange to Support COVID-19 Containment [Internet]. 2020 [cited January 30, 2021]. Available from: https://healthpolicy.duke.edu/publications/data-interoperability-and-exchange-support-covid-19-containment
    PubMedGoogle Scholar
  • 50 Ratwani RM, Reider J, Singh H. A Decade of Health Information Technology Usability Challenges and the Path Forward. JAMA 2019; 321 (08) 743-4
    CrossrefPubMedGoogle Scholar
  • 51 Topaz M, Ronquillo C, Peltonen LM, Pruinelli L, Sarmiento RF, Badger MK. et al. Nurse Informaticians Report Low Satisfaction and Multi-level Concerns with Electronic Health Records: Results from an International Survey. AMIA Annu Symp Proc 2017; 2016: 2016-25
    PubMedGoogle Scholar
  • 52 Schrager JD, Schuler K, Isakov AP, Wright DW, Yaffee AQ, Jacobson KL. et al. Development and Usability Testing of a Web-based COVID-19 Self-triage Platform. West J Emerg Med 2020; 21 (05) 1054-8
    CrossrefPubMedGoogle Scholar
  • 53 Pal D, Vanijja V. Perceived usability evaluation of Microsoft Teams as an online learning platform during COVID-19 using system usability scale and technology acceptance model in India. Child Youth Serv Rev 2020; 119: 105535
    CrossrefPubMedGoogle Scholar
  • 54 Lian W, Wen L, Zhou Q, Zhu W, Duan W, Xiao X. et al. Digital Health Technologies Respond to the COVID-19 Pandemic In a Tertiary Hospital in China: Development and Usability Study. J Med Internet Res 2020; 22 (11) e24505
    CrossrefPubMedGoogle Scholar
  • 55 Garcia M, Lipskiy N, Tyson J, Watkins R, Esser ES, Kinley T. Centers for Disease Control and Prevention 2019 novel coronavirus disease (COVID-19) information management: addressing national health-care and public health needs for standardized data definitions and codified vocabulary for data exchange. J Am Med Inform Assoc 2020; 27 (09) 1476-87
    CrossrefPubMedGoogle Scholar
  • 56 Dong X, Li J, Soysal E, Bian J, DuVall SL, Hanchrow E. et al. COVID-19 TestNorm: A tool to normalize COVID-19 testing names to LOINC codes. J Am Med Inform Assoc 2020; 27 (09) 1437-42
    CrossrefPubMedGoogle Scholar
  • 57 Sass J, Bartschke A, Lehne M, Essenwanger A, Rinaldi E, Rudolph S. et al. The German Corona Consensus Dataset (GECCO): a standardized dataset for COVID-19 research in university medicine and beyond. BMC Med Inform Decis Mak 2020; 20 (01) 341
    CrossrefPubMedGoogle Scholar
  • 58 Bakken S. Informatics impact requires effective, scalable tools and standards-based infrastructure. J Am Med Inform Assoc 2020; 27 (09) 1341-2
    CrossrefPubMedGoogle Scholar