Abstract
This Chapter discusses fundamental approaches that will drive the shift from today’s systems to those that will be successful in the “new normal.”. It highlights the changes and emerging technologies that are already affecting health systems. The authors suggest that the evolving post-COVID-19 ecosystem will need Health Intelligence tools to provide timely and useful insights. These insights will be drawn from many diverse and rapidly expanding data sources, including social media, anonymized financial, mobility, and IoT data. The authors suggest that ‘new normal’ systems should be built on a Complex Adaptive System (CAS) framework, much like the Internet, to address the flexibility and extensibility required in the twenty-first Century. It also describes some of the challenges facing the Health Informatics community. It also presents how Health Intelligence tools can support the evolution from today’s health ecosystem into the set of successful systems for the “next normal.” The Chapter concludes with exemplar cases for Health Intelligence that support public health and individuals. Users will have always-on access points with them and have more timely, actionable insights.
Insanity, doing the same thing and expecting different results.
Albert Einstein
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
Complex Adaptive Systems are characterized by a high degree of adaptive capacity, giving them the ability to succeed and flourish in the face of change. They are adaptive, communicative, cooperative, specialized, spatially and temporally organized, and reproduce, often with new parts that are more resilient and effective than earlier ones (Wikipedia, complex adaptive system, accessed 12/28/2020).
References
Silva JS, Ball MJ. Engineering the next generation of health systems. In: Weaver C, et al., editors. Healthcare information management systems. 4th ed. New York: Springer-Verlag; 2015. p. 461–76.
Provost J, Fawcett T. Data science and its relationship to big data and data-driven decision making. Big Data. 2013;1(1):51–9. https://doi.org/10.1089/big.2013.1508.
Curran E, Jamrisko M, et al. Ten ways Covid-19 has changed the world economy forever (yahoo.com). Accessed 30 Dec 2020.
AHA report on lost revenues 2020. https://www.aha.org/system/files/media/file/2020/06/aha-covid19-financial-impact-report.pdf. Accessed 2 Mar 2021.
Bakalar R. Telemedicine: its past, present & future. In: Healthcare information management systems: cases, strategies, and solutions. New York, NY: Springer; 2016.
Fair Health. Monthly telehealth regional tracker | FAIR Health. Accessed 3 Feb 2021.
Empowered patients - The Medical Futurist. Accessed 8 Mar 2021.
Meditation and mindfulness apps continue their surge amid pandemic | TechCrunch. Accessed 7 Mar 2021.
COVID-19 deaths analyzed by race and ethnicity — APM Research Lab. Accessed 5 Jan 2021.
Lee J, Korba C. https://www2.deloitte.com/content/dam/Deloitte/us/Documents/life-sciences-health-care/us-lshc-addressing-social-determinants-of-health.pdf. Accessed 2 Feb 2021.
Kelly JT, Campbell KL, Gong E, Scuffham P. The Internet of Things: impact and implications for health care delivery. J Med Internet Res. 2020;22(11):e20135. https://doi.org/10.2196/20135.
Wearables 2019 - Insider intelligence trends, forecasts & statistics (emarketer.com). Accessed 8 Mar 2021.
https://techjury.net/blog/big-data-statistics/#gref. Accessed 5 Nov 2020.
Martin CM. Complex adaptive systems approaches in health care—A slow but real emergence? J Eval Clin Pract. 2018;24(1):266–8. https://doi.org/10.1111/jep.12878.
Stevens P, et al. Healthcare’s earthquake: Lessons from complex adaptive systems to develop Covid-19-responsive measures and models | Catalyst non-issue content (nejm.org). Accessed 10 Mar 2021.
What we believe in – The Medical Futurist mission statement. The Medical Futurist. Accessed 8 Mar 2021.
Where innovation is happening | CMS Innovation Center. Accessed 13 Jan 2021.
Ritchie C, et al. Medical Care at Home Comes of Age. Medical Care at Home Comes of Age (chcf.org). Accessed 13 Jan 2021.
Nazir N, et al. Internet of things for healthcare using effects of mobile computing: a systematic literature review. Wireless Commun Mobile Comput. 2019;2019:5931315.
Healthcare Is Coming Home With Sensors And Algorithms - The Medical Futurist. Accessed 8 Mar 2021.
Hubner. IPE chapter in N.I.
Public Health Intelligence in Practice (who.int). Accessed 4 Mar 2021.
Aiello A, et al. Social media and internet-based disease surveillance for public health. Annu Rev Public Health. 2020;41(1):101–18.
Ipsos Biosurveillance Atlas, 20-03-59_bioatlas_v6_0.pdf (ipsos.com) Accessed 14 Jan 2021.
Gao S, Patz J. Association of mobile phone location data indications of travel and stay-at-home mandates with COVID-19 infection rates in the U.S. JAMA Netw Open. 2020;3(9):e2020485. https://doi.org/10.1001/jamanetworkopen.2020.20485.
Ipsos Biosurveillance Atlas. Ipsos Biosurveillance Atlas: COVID-19 Monitoring | Ipsos. Accessed 19 Oct 2021.
Wilson G, et al. Health intelligence atlas: a Core tool for public health intelligence. Appl Clin Inform. 2021;12:944–53.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Silva, J.S., Ball, M.J., Polyak, M., Wilson, G.M. (2022). The Future of Health Systems: Health Intelligence. In: Kiel, J.M., Kim, G.R., Ball, M.J. (eds) Healthcare Information Management Systems. Health Informatics. Springer, Cham. https://doi.org/10.1007/978-3-031-07912-2_31
Download citation
DOI: https://doi.org/10.1007/978-3-031-07912-2_31
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-07911-5
Online ISBN: 978-3-031-07912-2
eBook Packages: MedicineMedicine (R0)