Abstract
Decision-making by public health leaders requires data, information, and knowledge. Information systems that support transformation of data into information and knowledge, and that inform decision-making processes, are referred to as decision support systems (DSS). There exist a variety of DSS in clinical and public health contexts. For example, clinical DSS aid physicians in diagnosing a patient or prevent the prescribing of a medication that might cause harm. Public health DSS inform population health decisions, such as calculation of vaccination levels in a community or which areas in a community might benefit most from a mobile prevention clinic. The information and communications technologies (ICT) components for clinical and public health DSS are the same, even though they might be deployed in different ways to achieve better outcomes for individuals and populations. This chapter defines the concepts and components of DSS. The chapter also distinguishes between clinical and public health uses of DSS as well as the challenges with implementing DSS in real-world settings.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Friedman CP. A “fundamental theorem” of biomedical informatics. J Am Med Inform Assoc. 2009;16(2):169–70. https://doi.org/10.1197/jamia.M3092.
Bae J, Ford EW, Kharrazi HHK, Huerta TR. Electronic medical record reminders and smoking cessation activities in primary care. Addict Behav. 2018;77:203–9. https://doi.org/10.1016/j.addbeh.2017.10.009.
Bright TJ, Wong A, Dhurjati R, Bristow E, Bastian L, Coeytaux RR, et al. Effect of clinical decision-support systems: a systematic review. Ann Intern Med. 2012;157(1):29–43. https://doi.org/10.7326/0003-4819-157-1-201207030-00450.
Kempe A, Hurley LP, Cardemil CV, Allison MA, Crane LA, Brtnikova M, et al. Use of immunization information systems in primary care. Am J Prev Med. 2017;52(2):173–82. https://doi.org/10.1016/j.amepre.2016.07.029.
Greenes RA. Definition, scope and challenges. In: Greenes RA, editor. Clinical decision support: the road to broad adoption. 2nd ed. Waltham: Elsevier; 2014.
Ancker JS, Edwards A, Nosal S, Hauser D, Mauer E, Kaushal R. Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system. BMC Med Inform Decis Mak. 2017;17(1):36. https://doi.org/10.1186/s12911-017-0430-8.
Greenes RA. A brief history of clinical decision support: technical, social, cultural, economic, and governmental perspectives. In: Greenes RA, editor. Clinical decision support. 2nd ed. Oxford: Academic; 2014. p. 49–109.
Middleton B, Sittig DF, Wright A. Clinical decision support: a 25 year retrospective and a 25 year vision. Yearb Med Inform. 2016;1(Suppl 1):S103–S16. https://doi.org/10.15265/IYS-2016-s034.
Brown SH, Lincoln MJ, Groen PJ, Kolodner RM. VistA—U.S. Department of Veterans Affairs national-scale HIS. Int J Med Inform. 2003;69(2–3):135–56.
Evans RS, Pestotnik SL, Classen DC, Clemmer TP, Weaver LK, Orme JF Jr, et al. A computer-assisted management program for antibiotics and other antiinfective agents. N Engl J Med. 1998;338(4):232–8. https://doi.org/10.1056/nejm199801223380406.
Duke JD, Morea J, Mamlin B, Martin DK, Simonaitis L, Takesue BY, et al. Regenstrief Institute’s medical gopher: a next-generation homegrown electronic medical record system. Int J Med Inform. 2014;83(3):170–9. https://doi.org/10.1016/j.ijmedinf.2013.11.004.
Biondich PG, Dixon BE, Duke J, Mamlin B, Grannis S, Takesue BY, et al. Regenstrief medical informatics: experiences with clinical decision support systems. In: Greenes RA, editor. Clinical decision support: the road to broad adoption. 2nd ed. Burlington: Elsevier; 2014. p. 165–87.
Boxwala AA, Rocha BH, Maviglia S, Kashyap V, Meltzer S, Kim J, et al. A multi-layered framework for disseminating knowledge for computer-based decision support. J Am Med Inform Assoc. 2011;18(Suppl 1):i132–9. https://doi.org/10.1136/amiajnl-2011-000334.
Goldberg HS, Paterno MD, Rocha BH, Schaeffer M, Wright A, Erickson JL, et al. A highly scalable, interoperable clinical decision support service. J Am Med Inform Assoc. 2014;21(e1):e55–62. https://doi.org/10.1136/amiajnl-2013-001990.
Dixon BE, Simonaitis L, Goldberg HS, Paterno MD, Schaeffer M, Hongsermeier T, et al. A pilot study of distributed knowledge management and clinical decision support in the cloud. Artif Intell Med. 2013;59(1):45–53. https://doi.org/10.1016/j.artmed.2013.03.004.
Dixon BE, Simonaitis L, Perkins SM, Wright A, Middleton B. Measuring agreement between decision support reminders: the cloud vs. the local expert. BMC Med Inform Decis Mak. 2014;14(1):31. https://doi.org/10.1186/1472-6947-14-31.
Dixon BE, Gamache RE, Grannis SJ. Towards public health decision support: a systematic review of bidirectional communication approaches. J Am Med Inform Assoc. 2013;20(3):577–83. https://doi.org/10.1136/amiajnl-2012-001514.
IOM. The future of public health. Washington: National Academy Press; 1988.
Gamache R, Stevens KC, Merriwether R, Dixon BE, Grannis S. Development and assessment of a public health alert delivered through a community health information exchange. J Public Health Inform. 2010;2(2):23569583. https://doi.org/10.5210/ojphi.v2i2.3214.
Lurio J, Morrison FP, Pichardo M, Berg R, Buck MD, Wu W, et al. Using electronic health record alerts to provide public health situational awareness to clinicians. J Am Med Inform Assoc. 2010;17(2):217–9. https://doi.org/10.1136/jamia.2009.000539.
Committee on Integrating Primary Care, Public Health, Board on Population Health, Public Health Practise, Institute of Medicine. Primary care and public health: exploring integration to improve population health. Washington: National Academies Press; 2012.
Centers for Disease Control and Prevention US. About immunization information systems. Washington, DC: U.S. Department of Health and Human Services; 2019. https://www.cdc.gov/vaccines/programs/iis/about.html. Accessed 15 Nov 2019.
Centers for Disease Control and Prevention US. Clinical decision support for immunization (CDSi). Washington, DC: Department of Health and Human Services; 2019. https://www.cdc.gov/vaccines/programs/iis/cdsi.html. Accessed 15 Nov 2019.
National Center for Immunization and Respiratory Diseases. Clinical decision support for immunizaTION (CDSI): logic specification for ACIP recommendations; 2019.
Myerburg S, Larson E. Clinical decision support for immunization (CDSi). In: Centers for Disease Control and Prevention US, Ed. Atlanta, GA: Centers for Disease Control and Prevention; 2019.
Office of the National Coordinator for Health Information Technology US. Interoperability roadmap. Washington, DC: Department of Health and Human Services; 2014. https://www.healthit.gov/topic/interoperability/interoperability-roadmap. Accessed 15 Nov 2019.
Black J, Hulkower R, Suarez W, Patel S, Elliott B. Public health surveillance: electronic reporting as a point of reference. J Law Med Ethics. 2019;47(2):19–22. https://doi.org/10.1177/1073110519857309.
Digital Bridge. Implementation overview; 2019. https://digitalbridge.us/infoex/implementation/. Accessed Jul 1 2019.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Dixon, B.E., Kharrazi, H., Papagari Sangareddy, S.R. (2020). Public Health Decision Support Systems. In: Magnuson, J., Dixon, B. (eds) Public Health Informatics and Information Systems . Health Informatics. Springer, Cham. https://doi.org/10.1007/978-3-030-41215-9_20
Download citation
DOI: https://doi.org/10.1007/978-3-030-41215-9_20
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-41214-2
Online ISBN: 978-3-030-41215-9
eBook Packages: MedicineMedicine (R0)