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==Public health informatics evolution and COVID-19== | ==Public health informatics evolution and COVID-19== | ||
Over two decades ago, Yasnoff ''et al.''<ref name=":0">{{Cite journal |last=Yasnoff |first=William A. |last2=OʼCarroll |first2=Patrick W. |last3=Koo |first3=Denise |last4=Linkins |first4=Robert W. |last5=Kilbourne |first5=Edwin M. |date=2000 |title=Public Health Informatics: Improving and Transforming Public Health in the Information Age: |url=http://journals.lww.com/00124784-200006060-00010 |journal=Journal of Public Health Management and Practice |language=en |volume=6 |issue=6 |pages=67–75 |doi=10.1097/00124784-200006060-00010 |issn=1078-4659}}</ref> defined the discipline of [[public health informatics]] (PHI) as the “systematic application of [[information]] and computer science and technology to [[public health]] practice, research, and learning.”<ref name=":0" /> The prevailing impression at that time was that all stakeholders must be engaged in coordinated activities related to PHI, but the public health workforce were deemed to not have the training and experience to make decisions about IT.<ref name=":1">{{Cite journal |last=Yasnoff |first=W. A. |last2=Overhage |first2=J. M. |last3=Humphreys |first3=B. L. |last4=LaVenture |first4=M. |date=2001-11-01 |title=A National Agenda for Public Health Informatics: Summarized Recommendations from the 2001 AMIA Spring Congress |url=https://academic.oup.com/jamia/article-lookup/doi/10.1136/jamia.2001.0080535 |journal=Journal of the American Medical Informatics Association |language=en |volume=8 |issue=6 |pages=535–545 |doi=10.1136/jamia.2001.0080535 |issn=1067-5027 |pmc=PMC130064 |pmid=11687561}}</ref> If public health professionals were left out of the PHI decision making, is it any surprise that this practice resulted in some high risk level of technology failures, and in other cases slow adoption of the technology.<ref name=":1" /> Besides bringing public health professionals into the decision making circle, what can be done to help PHI flourish? | |||
In the last two decades, we have seen a myriad of innovative technologies applied to public health practice in areas such as disease surveillance, immunization registries, [[electronic health record]] (EHR) integration, vital statistics, etc. Public health organizations such as the Association of State and Territorial Health Officials (ASTHO), Public Health Informatics Institute (PHII), and [[Centers for Disease Control and Prevention]] (CDC) recognized that the decentralized United States public health system is enormous in scale and immense in diversity, making it difficult to implement innovative technology successfully.<ref>{{Cite journal |last=Beck |first=Angela J. |last2=Boulton |first2=Matthew L. |last3=Coronado |first3=Fátima |date=2014-11 |title=Enumeration of the Governmental Public Health Workforce, 2014 |url=https://linkinghub.elsevier.com/retrieve/pii/S0749379714003857 |journal=American Journal of Preventive Medicine |language=en |volume=47 |issue=5 |pages=S306–S313 |doi=10.1016/j.amepre.2014.07.018 |pmc=PMC6944190 |pmid=25439250}}</ref><ref>{{Cite journal |last=Hilliard |first=Tracy M. |last2=Boulton |first2=Matthew L. |date=2012-05 |title=Public Health Workforce Research in Review |url=https://linkinghub.elsevier.com/retrieve/pii/S074937971200092X |journal=American Journal of Preventive Medicine |language=en |volume=42 |issue=5 |pages=S17–S28 |doi=10.1016/j.amepre.2012.01.031}}</ref><ref>{{Cite journal |last=Tao |first=Donghua |last2=Evashwick |first2=Connie J. |last3=Grivna |first3=Michal |last4=Harrison |first4=Roger |date=2018-02-19 |title=Educating the Public Health Workforce: A Scoping Review |url=http://journal.frontiersin.org/article/10.3389/fpubh.2018.00027/full |journal=Frontiers in Public Health |volume=6 |pages=27 |doi=10.3389/fpubh.2018.00027 |issn=2296-2565 |pmc=PMC5826052 |pmid=29515988}}</ref> Complicating successful implementations are [[Informatics (academic field)|informatics]] factors and organizational culture barriers that do not allow for evidence-based public health to be implemented in practice.<ref name=":1" /><ref>{{Cite journal |last=Novick |first=Lloyd F. |date=2020-09 |title=JPHMP and The Guide to Community Preventive Services |url=https://journals.lww.com/10.1097/PHH.0000000000001217 |journal=Journal of Public Health Management and Practice |language=en |volume=26 |issue=5 |pages=399–400 |doi=10.1097/PHH.0000000000001217 |issn=1078-4659}}</ref> | |||
To help public health leaders to understand these digital technologies and make informed decisions on technology integration, ASTHO, PHII, and the CDC have created several reports and frameworks.<ref name=":2">{{Cite web |last=Centers for Disease Control and Prevention |date=09 April 2021 |title=Data Modernization Initiative |work=Public Health Surveillance and Data |url=https://www.cdc.gov/surveillance/surveillance-data-strategies/data-IT-transformation.html |publisher=Centers for Disease Control and Prevention}}</ref><ref>{{Cite web |last=ASTHO |date=July 2020 |title=Issue Guide: COVID-19 Case Investigation and Contact Tracing - Considerations for Using Digital Technologies |url=https://astho.org/ASTHOReports/COVID-19-Case-Investigation-and-Contact-Tracing-Considerations-for-Using-Digital-Technologies/07-16-20/ |format=PDF |publisher=ASTHO}}</ref><ref>{{Cite web |last=Public Health Informatics Institute |date=June 2020 |title=Digital Tools to Support Contact Tracing: Tool Assessment Report |url=https://phii.org/sites/default/files/DT4CT%20Assessment%20Report%206.29.20%20_FINAL-v2.pdf |format=PDF |publisher=Public Health Informatics Institute}}</ref> These documents are filled with standards, discussion about security, confidentiality and privacy, system architectures and infrastructure, training, and workforce development. They are detailed about the technology and their implementations, with recommendations of such things as overhauling of computer systems, changes in operability, and upgrades to hardware and software. These guides and frameworks primarily define the workforce in the domain of technical skills. One example is the CDC’s roadmap for public health informatics and data modernization, which identifies the need for a future workforce with stronger skills in data science, analytics, modeling, and informatics. | |||
Clearly, improved technical skills are a necessary condition, but we argue that alone is insufficient to the challenge at hand. Kaplan and Harris-Salamone<ref name=":3">{{Cite journal |last=Kaplan |first=B. |last2=Harris-Salamone |first2=K. D. |date=2009-05-01 |title=Health IT Success and Failure: Recommendations from Literature and an AMIA Workshop |url=https://academic.oup.com/jamia/article-lookup/doi/10.1197/jamia.M2997 |journal=Journal of the American Medical Informatics Association |language=en |volume=16 |issue=3 |pages=291–299 |doi=10.1197/jamia.M2997 |issn=1067-5027 |pmc=PMC2732244 |pmid=19261935}}</ref> report that across industries (including healthcare) there is at least a 40% or greater failure rate for generic IT projects. These failures are largely attributed to overbudgeting, timeline overruns, under delivery of value, and termination of the project before completion. They also emphasize the three major reasons for project success: user involvement, proactive executive management support, and a clear requirements statement.<ref name=":3" /> Reviewing the CDC’s roadmap reveals an insufficient emphasis on—if not a complete miss of—these important human factors concepts, such as the perceptions of the public health professional workforce, their attitude, and their motivation for accepting and using new technology.<ref name=":2" /> | |||
Revision as of 23:55, 23 August 2021
| Full article title | Public health informatics, human factors, and the end-users |
|---|---|
| Journal | Health Services Research and Managerial Epidemiology |
| Author(s) | Matthews, Sarah D.; Proctor, Michael D. |
| Author affiliation(s) | University of Central Florida |
| Primary contact | Email: sarah dot matthews at knights dot ucf dot edu |
| Year published | 2021 |
| Volume and issue | 8 |
| Article # | 23333928211012226 |
| DOI | 10.1177/23333928211012226 |
| ISSN | 2333-3928 |
| Distribution license | Creative Commons Attribution-NonCommercial 4.0 International |
| Website | https://journals.sagepub.com/doi/10.1177/23333928211012226 |
| Download | https://journals.sagepub.com/doi/pdf/10.1177/23333928211012226 (PDF) |
 |
This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed. |
Abstract
There is an unspoken assumption in public health informatics that “if you build it, they will come.” In this commentary, we argue that building it is not enough. Without end-user focus on human factors issues that are identified and resolved prior to implementation, “they may come, but they won’t stay!” We argue that to engage public health professionals with new innovative technology, one must continually ask during the development process, “who are we building this product for, and do we have the right information to back up our theories on implementation and use?” With the myriad of public health informatics introduced amid the COVID-19 pandemic, there are now many choices. For those languishing, we note that this question may not have been sufficiently pursued, resulting in situations where “they may come, but they won’t stay!”
Keywords: public health informatics, public health professionals, Technology Acceptance Model, Health Belief Model, human factors research
Public health informatics evolution and COVID-19
Over two decades ago, Yasnoff et al.[1] defined the discipline of public health informatics (PHI) as the “systematic application of information and computer science and technology to public health practice, research, and learning.”[1] The prevailing impression at that time was that all stakeholders must be engaged in coordinated activities related to PHI, but the public health workforce were deemed to not have the training and experience to make decisions about IT.[2] If public health professionals were left out of the PHI decision making, is it any surprise that this practice resulted in some high risk level of technology failures, and in other cases slow adoption of the technology.[2] Besides bringing public health professionals into the decision making circle, what can be done to help PHI flourish?
In the last two decades, we have seen a myriad of innovative technologies applied to public health practice in areas such as disease surveillance, immunization registries, electronic health record (EHR) integration, vital statistics, etc. Public health organizations such as the Association of State and Territorial Health Officials (ASTHO), Public Health Informatics Institute (PHII), and Centers for Disease Control and Prevention (CDC) recognized that the decentralized United States public health system is enormous in scale and immense in diversity, making it difficult to implement innovative technology successfully.[3][4][5] Complicating successful implementations are informatics factors and organizational culture barriers that do not allow for evidence-based public health to be implemented in practice.[2][6]
To help public health leaders to understand these digital technologies and make informed decisions on technology integration, ASTHO, PHII, and the CDC have created several reports and frameworks.[7][8][9] These documents are filled with standards, discussion about security, confidentiality and privacy, system architectures and infrastructure, training, and workforce development. They are detailed about the technology and their implementations, with recommendations of such things as overhauling of computer systems, changes in operability, and upgrades to hardware and software. These guides and frameworks primarily define the workforce in the domain of technical skills. One example is the CDC’s roadmap for public health informatics and data modernization, which identifies the need for a future workforce with stronger skills in data science, analytics, modeling, and informatics.
Clearly, improved technical skills are a necessary condition, but we argue that alone is insufficient to the challenge at hand. Kaplan and Harris-Salamone[10] report that across industries (including healthcare) there is at least a 40% or greater failure rate for generic IT projects. These failures are largely attributed to overbudgeting, timeline overruns, under delivery of value, and termination of the project before completion. They also emphasize the three major reasons for project success: user involvement, proactive executive management support, and a clear requirements statement.[10] Reviewing the CDC’s roadmap reveals an insufficient emphasis on—if not a complete miss of—these important human factors concepts, such as the perceptions of the public health professional workforce, their attitude, and their motivation for accepting and using new technology.[7]
References
- ↑ 1.0 1.1 Yasnoff, William A.; OʼCarroll, Patrick W.; Koo, Denise; Linkins, Robert W.; Kilbourne, Edwin M. (2000). "Public Health Informatics: Improving and Transforming Public Health in the Information Age:" (in en). Journal of Public Health Management and Practice 6 (6): 67–75. doi:10.1097/00124784-200006060-00010. ISSN 1078-4659. http://journals.lww.com/00124784-200006060-00010.
- ↑ 2.0 2.1 2.2 Yasnoff, W. A.; Overhage, J. M.; Humphreys, B. L.; LaVenture, M. (1 November 2001). "A National Agenda for Public Health Informatics: Summarized Recommendations from the 2001 AMIA Spring Congress" (in en). Journal of the American Medical Informatics Association 8 (6): 535–545. doi:10.1136/jamia.2001.0080535. ISSN 1067-5027. PMC PMC130064. PMID 11687561. https://academic.oup.com/jamia/article-lookup/doi/10.1136/jamia.2001.0080535.
- ↑ Beck, Angela J.; Boulton, Matthew L.; Coronado, Fátima (1 November 2014). "Enumeration of the Governmental Public Health Workforce, 2014" (in en). American Journal of Preventive Medicine 47 (5): S306–S313. doi:10.1016/j.amepre.2014.07.018. PMC PMC6944190. PMID 25439250. https://linkinghub.elsevier.com/retrieve/pii/S0749379714003857.
- ↑ Hilliard, Tracy M.; Boulton, Matthew L. (1 May 2012). "Public Health Workforce Research in Review" (in en). American Journal of Preventive Medicine 42 (5): S17–S28. doi:10.1016/j.amepre.2012.01.031. https://linkinghub.elsevier.com/retrieve/pii/S074937971200092X.
- ↑ Tao, Donghua; Evashwick, Connie J.; Grivna, Michal; Harrison, Roger (19 February 2018). "Educating the Public Health Workforce: A Scoping Review". Frontiers in Public Health 6: 27. doi:10.3389/fpubh.2018.00027. ISSN 2296-2565. PMC PMC5826052. PMID 29515988. http://journal.frontiersin.org/article/10.3389/fpubh.2018.00027/full.
- ↑ Novick, Lloyd F. (1 September 2020). "JPHMP and The Guide to Community Preventive Services" (in en). Journal of Public Health Management and Practice 26 (5): 399–400. doi:10.1097/PHH.0000000000001217. ISSN 1078-4659. https://journals.lww.com/10.1097/PHH.0000000000001217.
- ↑ 7.0 7.1 Centers for Disease Control and Prevention (9 April 2021). "Data Modernization Initiative". Public Health Surveillance and Data. Centers for Disease Control and Prevention. https://www.cdc.gov/surveillance/surveillance-data-strategies/data-IT-transformation.html.
- ↑ ASTHO (July 2020). "Issue Guide: COVID-19 Case Investigation and Contact Tracing - Considerations for Using Digital Technologies" (PDF). ASTHO. https://astho.org/ASTHOReports/COVID-19-Case-Investigation-and-Contact-Tracing-Considerations-for-Using-Digital-Technologies/07-16-20/.
- ↑ Public Health Informatics Institute (June 2020). "Digital Tools to Support Contact Tracing: Tool Assessment Report" (PDF). Public Health Informatics Institute. https://phii.org/sites/default/files/DT4CT%20Assessment%20Report%206.29.20%20_FINAL-v2.pdf.
- ↑ 10.0 10.1 Kaplan, B.; Harris-Salamone, K. D. (1 May 2009). "Health IT Success and Failure: Recommendations from Literature and an AMIA Workshop" (in en). Journal of the American Medical Informatics Association 16 (3): 291–299. doi:10.1197/jamia.M2997. ISSN 1067-5027. PMC PMC2732244. PMID 19261935. https://academic.oup.com/jamia/article-lookup/doi/10.1197/jamia.M2997.
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. Some grammar and paragraph spacing was updated for improved readability. In some cases important information was missing from the references, and that information was added.
