International Comparison of Six Basic eHealth Indicators Across 14 Countries: An eHealth Benchmarking Study

Abstract

Background Many countries adopt eHealth applications to support patient-centered care. Through information exchange, these eHealth applications may overcome institutional data silos and support holistic and ubiquitous (regional or national) information logistics. Available eHealth indicators mostly describe usage and acceptance of eHealth in a country. The eHealth indicators focusing on the cross-institutional availability of patient-related information for health care professionals, patients, and care givers are rare.

Objectives This study aims to present eHealth indicators on cross-institutional availability of relevant patient data for health care professionals, as well as for patients and their caregivers across 14 countries (Argentina, Australia, Austria, Finland, Germany, Hong Kong as a special administrative region of China, Israel, Japan, Jordan, Kenya, South Korea, Sweden, Turkey, and the United States) to compare our indicators and the resulting data for the examined countries with other eHealth benchmarks and to extend and explore changes to a comparable survey in 2017. We defined “availability of patient data” as the ability to access data in and to add data to the patient record in the respective country.

Methods The invited experts from each of the 14 countries provided the indicator data for their country to reflect the situation on August 1, 2019, as date of reference. Overall, 60 items were aggregated to six eHealth indicators.

Results Availability of patient-related information varies strongly by country. Health care professionals can access patients' most relevant cross-institutional health record data fully in only four countries. Patients and their caregivers can access their health record data fully in only two countries. Patients are able to fully add relevant data only in one country. Finland showed the best outcome of all eHealth indicators, followed by South Korea, Japan, and Sweden.

Conclusion Advancement in eHealth depends on contextual factors such as health care organization, national health politics, privacy laws, and health care financing. Improvements in eHealth indicators are thus often slow. However, our survey shows that some countries were able to improve on at least some indicators between 2017 and 2019. We anticipate further improvements in the future.

Keywords

health information exchange - health information systems - continuity of patient care - patient-centered care - eHealth - international health

^* Joint senior authorship.

Publication History

Received: 14 March 2020

Accepted: 21 June 2020

Article published online:
18 November 2020

• References

• 1 Organisation for Economic Co-operation and Development (OECD). Draft OECD Guide to Measuring ICTs in the Health Sector. Available at: https://www.oecd.org/health/health-systems/Draft-oecd-guide-to-measuring-icts-in-the-health-sector.pdf . Accessed July 15, 2020
• 2 Kruse CS, Beane A. Health information technology continues to show positive effect on medical outcomes: systematic review. J Med Internet Res 2018; 20 (02) e41
• 3 Hersh WR, Totten AM, Eden KB. et al. Outcomes from health information exchange: systematic review and future research needs. JMIR Med Inform 2015; 3 (04) e39
• 4 Kuhn KA, Giuse DA. From hospital information systems to health information systems. Problems, challenges, perspectives. Methods Inf Med 2001; 40 (04) 275-287IS
• 5 Eysenbach G. What is e-health?. J Med Internet Res 2001; 3 (02) E20
• 6 Hyppönen H, Faxvaag A, Gilstad H. et al. Nordic eHealth indicators: organisation of research, first results and plan for the future. Stud Health Technol Inform 2013; 192: 273-277
• 7 Nordic Council of Ministers. Nordic EHealth Benchmarking. Available at: https://norden.diva-portal.org/smash/get/diva2:1093162/FULLTEXT01.pdf . Accessed July 25, 2020
• 8 European Commission. Benchmarking Deployment of EHealth among General Practitioners. Available at: http://ec.europa.eu/information_society/newsroom/cf/dae/document.cfm?doc_id=4897 . Accessed July 15, 2020
• 9 World Health Organization. E-health: Indicators & visualizations. Available at: https://gateway.euro.who.int/en/themes/e-health/indicators-visualizations/ . Accessed July 15, 2020
• 10 Centers for Disease Control and Prevention. Public Health and Promoting Interoperability Programs. Available at: https://www.cdc.gov/ehrmeaningfuluse/introduction.html . Accessed July 15, 2020
• 11 Haux R, Ammenwerth E, Koch S, et al. A Brief Survey on Six Basic and Reduced eHealth Indicators in Seven Countries in 2017. Appl Clin Inform. 2018;9(3):704–713. doi:10.1055/s-0038-1669458
• 12 ISO. ISO/TR 20514:2005. Health informatics—Electronic health record—Definition, scope and context. Available at: https://www.iso.org/standard/39525.html . Accessed July 15, 2020
• 13 World Health Organization. Global Diffusion of EHealth: Making Universal Health Coverage Achievable. Available at: https://apps.who.int/iris/bitstream/handle/10665/252529/9789241511780-eng.pdf;jsessionid=B7E7B4CF6BA92C6F4CC674C962BC395B?sequence=1 . Accessed July 15, 2020
• 14 Granja C, Janssen W, Johansen MA. Factors determining the success and failure of ehealth interventions: systematic review of the literature. J Med Internet Res 2018; 20 (05) e10235
• 15 Rigby M, Ammenwerth E, Talmon J. Forward outlook: the need for evidence and for action in health informatics. Stud Health Technol Inform 2016; 222: 355-363
• 16 Zelmer J, Ronchi E, Hyppönen H. et al. International health IT benchmarking: learning from cross-country comparisons. J Am Med Inform Assoc 2017; 24 (02) 371-379
• 17 World Health Organization. From Innovation to Implementation. EHealth in the WHO European Region(2016). Available at: https://www.euro.who.int/__data/assets/pdf_file/0012/302331/From-Innovation-to-Implementation-eHealth-Report-EU.pdf . Accessed July 15, 2020
• 18 Esdar M, Hüsers J, Weiß JP, Rauch J, Hübner U. Diffusion dynamics of electronic health records: a longitudinal observational study comparing data from hospitals in Germany and the United States. Int J Med Inform 2019; 131: 103952
• 19 Naumann L, Esdar M, Ammenwerth E, Baumberger D, Hübner U. Same goals, yet different outcomes: analysing the current state of ehealth adoption and policies in Austria, Germany, and Switzerland using a mixed methods approach. Stud Health Technol Inform 2019; 264: 1012-1016
• 20 Tsai CH, Koch S. Towards a framework for national ehealth evaluation and monitoring: a combined top-down and bottom-up approach using sweden as example. Stud Health Technol Inform 2019; 264: 954-958
• 21 Price M, Lau F. The clinical adoption meta-model: a temporal meta-model describing the clinical adoption of health information systems. BMC Med Inform Decis Mak 2014; 14 (01) 43
• 22 Winter A, Haux R, Ammenwerth E, Brigl B, Hellrung N, Jahn F. Health Information Systems: Architectures and Strategies. 2nd ed. New York, NY: Springer-Verlag; 2011