Public health informatics - Revision history

Shawndouglas: Updated URLs for 2022

2022-01-06T21:58:12Z

Updated URLs for 2022

← Older revision		Revision as of 21:58, 6 January 2022
Line 30:		Line 30:

	===In the United States===		===In the United States===
	The [[Centers for Disease Control and Prevention]] (CDC) in Atlanta, Georgia has played an important role in public health and [[infectious disease informatics]]. The agency's Center for Surveillance, Epidemiology and Laboratory Services (CSELS; formerly OSELS<ref name="ACDMinsApril13">{{cite web \|url=https://www.cdc.gov/maso/facm/pdfs/ACDCDC/20130425_CDCACD.pdf \|format=PDF \|title=Advisory Committee to the Director: Record of the April 25, 2013 Meeting \|author=Advisory Committee to the Director \|publisher=Centers for Disease Control and Prevention \|pages=9–14 \|date=July 2013 \|accessdate=~~21 March 2020~~}}</ref><ref name="CDCOrgArch">{{cite web \|url=http://www.cdc.gov/maso/pdf/CDC_Official.pdf \|archiveurl=https://web.archive.org/web/20130718025323/http://www.cdc.gov/maso/pdf/CDC_Official.pdf \|format=PDF \|title=Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) \|publisher=Centers for Disease Control and Prevention \|date=27 July 2011 \|archivedate=18 July 2013 \|accessdate=17 June 2014}}</ref>) and its Division of Health Informatics and Surveillance (DHIS; formerly PHITPO and PHSIPO<ref name="ACDMinsApril13" /><ref name="CDCOrgArch" />) has focused on advancing the state of information science in these realms, applying digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations.<ref name="DHISAbout">{{cite web \|url=https://www.cdc.gov/csels/dhis/documents/dhis-fact-sheet-508.pdf \|format=PDF \|title=Division of Health Informatics and Surveillance \|author=Division of Health Informatics and Surveillance \|publisher=Centers for Disease Control and Prevention \|date=19 June 2018 \|accessdate=~~21 March 2020~~}}</ref> The CDC also created the National Electronic Disease Surveillance System (NEDSS)<ref name="DHISAbout" />, which includes a free comprehensive web and message-based reporting system called the NEDSS Base System (NBS), used for managing and transmitting reportable disease data.<ref name="NBSAbout">{{cite web \|url=https://~~wwwn~~.cdc.gov/nndss/nedss.html \|title=National Notifiable Diseases Surveillance System (NNDSS) \|author=Division of Health Informatics and Surveillance \|publisher=Centers for Disease Control and Prevention \|date=16 March 2017 \|accessdate=~~21 March 2020~~}}</ref>		The [[Centers for Disease Control and Prevention]] (CDC) in Atlanta, Georgia has played an important role in public health and [[infectious disease informatics]]. The agency's Center for Surveillance, Epidemiology and Laboratory Services (CSELS; formerly OSELS<ref name="ACDMinsApril13">{{cite web \|url=https://www.cdc.gov/maso/facm/pdfs/ACDCDC/20130425_CDCACD.pdf \|archiveurl=https://web.archive.org/web/20190722192037/https://www.cdc.gov/maso/facm/pdfs/ACDCDC/20130425_CDCACD.pdf \|format=PDF \|title=Advisory Committee to the Director: Record of the April 25, 2013 Meeting \|author=Advisory Committee to the Director \|publisher=Centers for Disease Control and Prevention \|pages=9–14 \|date=July 2013 \|archivedate=22 July 2019 \|accessdate=06 January 2022}}</ref><ref name="CDCOrgArch">{{cite web \|url=http://www.cdc.gov/maso/pdf/CDC_Official.pdf \|archiveurl=https://web.archive.org/web/20130718025323/http://www.cdc.gov/maso/pdf/CDC_Official.pdf \|format=PDF \|title=Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) \|publisher=Centers for Disease Control and Prevention \|date=27 July 2011 \|archivedate=18 July 2013 \|accessdate=17 June 2014}}</ref>) and its Division of Health Informatics and Surveillance (DHIS; formerly PHITPO and PHSIPO<ref name="ACDMinsApril13" /><ref name="CDCOrgArch" />) has focused on advancing the state of information science in these realms, applying digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations.<ref name="DHISAbout">{{cite web \|url=https://www.cdc.gov/csels/dhis/documents/dhis-fact-sheet-508.pdf \|archiveurl=https://web.archive.org/web/20210704090101/https://www.cdc.gov/csels/dhis/documents/dhis-fact-sheet-508.pdf \|format=PDF \|title=Division of Health Informatics and Surveillance \|author=Division of Health Informatics and Surveillance \|publisher=Centers for Disease Control and Prevention \|date=19 June 2018 \|archivedate=04 July 2021 \|accessdate=06 January 2022}}</ref> The CDC also created the National Electronic Disease Surveillance System (NEDSS)<ref name="DHISAbout" />, which includes a free comprehensive web and message-based reporting system called the NEDSS Base System (NBS), used for managing and transmitting reportable disease data.<ref name="NBSAbout">{{cite web \|url=https://www.cdc.gov/nndss/about/nedss.html \|title=National Notifiable Diseases Surveillance System (NNDSS) \|author=Division of Health Informatics and Surveillance \|publisher=Centers for Disease Control and Prevention \|date=16 March 2017 \|accessdate=06 January 2022}}</ref>

	Since 2002, the CDC has promoted the idea of the Public Health Information Network to facilitate the transmission of data from various partners in the health care industry and elsewhere (hospitals, clinical and environmental laboratories, doctors' practices, pharmacies) to local health agencies, then to state health agencies, and then to the CDC. At each stage the entity must be capable of receiving the data, storing it, aggregating it appropriately, and transmitting it to the next level.<ref name="PHIN02">{{cite web \|url=http://www.cdc.gov/phin/library/archive_2002/PHIN_Functions_Specifications_121802.pdf \|archiveurl=https://web.archive.org/web/20111023111340/http://www.cdc.gov/phin/library/archive_2002/PHIN_Functions_Specifications_121802.pdf \|format=PDF \|title=Public Health Information Network Functions and Specifications, Version 1.2 \|publisher=Centers for Disease Control and Prevention \|date=18 December 2002 \|archivedate=23 October 2011 \|accessdate=21 March 2020}}</ref> To promote interoperability between the NBS and other informatics systems, the CDC has also encouraged the adoption of several standard vocabularies and messaging formats from the health care world. The most prominent of these are the [[Health Level 7]] (HL7) standards for health care messaging, the LOINC system for encoding laboratory test and result information, and the Systematized Nomenclature of Medicine (SNOMED) vocabulary of health care concepts.<ref name="NBSAbout" />		Since 2002, the CDC has promoted the idea of the Public Health Information Network to facilitate the transmission of data from various partners in the health care industry and elsewhere (hospitals, clinical and environmental laboratories, doctors' practices, pharmacies) to local health agencies, then to state health agencies, and then to the CDC. At each stage the entity must be capable of receiving the data, storing it, aggregating it appropriately, and transmitting it to the next level.<ref name="PHIN02">{{cite web \|url=http://www.cdc.gov/phin/library/archive_2002/PHIN_Functions_Specifications_121802.pdf \|archiveurl=https://web.archive.org/web/20111023111340/http://www.cdc.gov/phin/library/archive_2002/PHIN_Functions_Specifications_121802.pdf \|format=PDF \|title=Public Health Information Network Functions and Specifications, Version 1.2 \|publisher=Centers for Disease Control and Prevention \|date=18 December 2002 \|archivedate=23 October 2011 \|accessdate=21 March 2020}}</ref> To promote interoperability between the NBS and other informatics systems, the CDC has also encouraged the adoption of several standard vocabularies and messaging formats from the health care world. The most prominent of these are the [[Health Level 7]] (HL7) standards for health care messaging, the LOINC system for encoding laboratory test and result information, and the Systematized Nomenclature of Medicine (SNOMED) vocabulary of health care concepts.<ref name="NBSAbout" />
Line 38:		Line 38:
	==Notes==		==Notes==

	Some elements of this article are reused from [~~http~~://en.wikipedia.org/wiki/Public_health_informatics the Wikipedia article].		Some elements of this article are reused from [https://en.wikipedia.org/wiki/Public_health_informatics the Wikipedia article].

	==References==		==References==

Shawndouglas: Minor updates for 2020

2020-03-21T20:42:48Z

Minor updates for 2020

← Older revision		Revision as of 20:42, 21 March 2020
Line 1:		Line 1:
	[[Image:Drug overdose death rates by state per 100,000 people 2008 US.png\|right\|600px\|thumbnail\|Collecting and utilizing vital statistics data is only one of many applications of public health informatics.]]		[[Image:Drug overdose death rates by state per 100,000 people 2008 US.png\|right\|600px\|thumbnail\|Collecting and utilizing vital statistics data is only one of many applications of public health informatics.]]
	'''Public health informatics''' has been defined as "the systematic application of [[information]] and computer science and technology to public health practice, research, and learning."<ref name="YasnoffPHI">{{cite journal ~~\|url=http://people.dbmi.columbia.edu/~rik7001/Yasnoff.pdf \|format=PDF \|journal=Journal of Public Health Management and Practice~~ \|title=Public Health Informatics: Improving and Transforming Public Health in the Information Age \|author=Yasnoff, ~~William~~ A.; O’Carroll, ~~Patrick~~ W.; Koo, ~~Denise; Linkins, Robert W~~.~~; Kilbourne, Edwin M~~. \|volume=6 \|issue=6 \|pages=67–75 \|year=2000 \|pmid=18019962 ~~\|accessdate=11 June 2014~~}}</ref><ref name="FriedePHI">{{cite journal ~~\|url=http://www.annualreviews.org/doi/abs/10.1146/annurev.pu.16.050195.001323 \|journal=Annual Review of Public Health~~ \|title=Public Health Informatics: How Information-Age Technology Can Strengthen Public Health \|author=Friede, ~~Andrew~~; Blum, ~~Henrik~~ L.; McDonald, ~~Mike~~ \|volume=16 \|pages=239–252 \|year=1995 \|doi=10.1146/annurev.pu.16.050195.001323 \|~~accessdate~~=~~11 June 2014~~}}</ref> Like other types of informatics, public health informatics is a multidisciplinary field, involving the studies of [[Informatics (academic field)\|informatics]], computer science, psychology, law, statistics, epidemiology, and microbiology.		'''Public health informatics''' has been defined as "the systematic application of [[information]] and computer science and technology to public health practice, research, and learning."<ref name="YasnoffPHI">{{cite journal \|title=Public Health Informatics: Improving and Transforming Public Health in the Information Age \|journal=Journal of Public Health Management and Practice \|author=Yasnoff, W.A.; O’Carroll, P.W.; Koo, D. et al. \|volume=6 \|issue=6 \|pages=67–75 \|year=2000 \|doi=10.1097/00124784-200006060-00010 \|pmid=18019962}}</ref><ref name="FriedePHI">{{cite journal \|title=Public Health Informatics: How Information-Age Technology Can Strengthen Public Health \|journal=Annual Review of Public Health \|author=Friede, A.; Blum, H.L.; McDonald, M. \|volume=16 \|pages=239–252 \|year=1995 \|doi=10.1146/annurev.pu.16.050195.001323 \|pmid=7639873}}</ref> Like other types of informatics, public health informatics is a multidisciplinary field, involving the studies of [[Informatics (academic field)\|informatics]], computer science, psychology, law, statistics, epidemiology, and microbiology.

	In 2000, researcher William A. Yasnoff and his colleagues identified four key aspects that differentiate public health informatics from [[Health informatics\|medical informatics]] and other informatics specialty areas. Public health informatics<ref name="YasnoffPHI" />:		In 2000, researcher William A. Yasnoff and his colleagues identified four key aspects that differentiate public health informatics from [[Health informatics\|medical informatics]] and other informatics specialty areas. Public health informatics<ref name="YasnoffPHI" />:
Line 10:		Line 10:

	==History==		==History==
	Before the advent of the ~~Internet~~, public health data, like other healthcare and business data, were collected on paper forms and stored centrally at the relevant public health agency. As computers became more commonplace, some data and information would be computerized, requiring a distinct data entry process, storage in various file formats, and analysis by mainframe computers using standard batch processing. With the coming of the ~~Internet~~ and cheaper large-scale storage technologies, public health agencies with sufficient resources began transitioning to web-accessible collections of public health data, and, more recently, to automated messaging of the same information.<ref name="OCarrollPHI">{{cite book \|url=~~http~~://books.google.com/books?id=ap6uCR0Ybo4C \|title=Public Health Informatics and Information Systems \|author=O'Carroll, ~~Patrick~~ W. \|publisher=Springer \|year=2003 \|pages=790 \|isbn=9780387954745 \|accessdate=~~16 June 2014~~}}</ref><ref name="LombardoDS">{{cite book \|url=~~http~~://books.google.com/books?id=-xI2Kl39ZzoC&printsec=frontcover \|chapter=Chapter 1: Disease Surveillance, a Public Health Priority \|title=Disease Surveillance: A Public Health Informatics Approach \|author=Lombardo, ~~Joseph~~ S.; Buckeridge, ~~David~~ L. \|publisher=John Wiley & Sons \|year=2012 \|pages=1–40 \|isbn=9781118569054 \|accessdate=~~16 June 2014~~}}</ref><ref name="LeePrincPrac">{{cite book \|url=~~http~~://books.google.com/books?id=FF78GCiUbwUC&pg=PA70 \|chapter=Chapter 5: Informatics and the Management of Surveillance Data \|title=Principles and Practice of Public Health Surveillance \|author=Krishnamurthy, ~~Ramesh~~ S.; St. Louis, ~~Michael~~ E. \|publisher=Oxford University Press \|year=2010 \|pages=65–87 \|isbn=9780195372922 \|accessdate=~~16 June 2014~~}}</ref>		Before the advent of the internet, public health data, like other healthcare and business data, were collected on paper forms and stored centrally at the relevant public health agency. As computers became more commonplace, some data and information would be computerized, requiring a distinct data entry process, storage in various file formats, and analysis by mainframe computers using standard batch processing. With the coming of the internet and cheaper large-scale storage technologies, public health agencies with sufficient resources began transitioning to web-accessible collections of public health data, and, more recently, to automated messaging of the same information.<ref name="OCarrollPHI">{{cite book \|url=https://books.google.com/books?id=ap6uCR0Ybo4C \|title=Public Health Informatics and Information Systems \|author=O'Carroll, P.W. \|publisher=Springer \|year=2003 \|pages=790 \|isbn=9780387954745 \|accessdate=21 March 2020}}</ref><ref name="LombardoDS">{{cite book \|url=https://books.google.com/books?id=-xI2Kl39ZzoC&printsec=frontcover \|chapter=Chapter 1: Disease Surveillance, a Public Health Priority \|title=Disease Surveillance: A Public Health Informatics Approach \|author=Lombardo, J.S.; Buckeridge, D.L. \|publisher=John Wiley & Sons \|year=2012 \|pages=1–40 \|isbn=9781118569054 \|accessdate=21 March 2020}}</ref><ref name="LeePrincPrac">{{cite book \|url=https://books.google.com/books?id=FF78GCiUbwUC&pg=PA70 \|chapter=Chapter 5: Informatics and the Management of Surveillance Data \|title=Principles and Practice of Public Health Surveillance \|author=Krishnamurthy, R.S.; St. Louis, M.E. \|publisher=Oxford University Press \|year=2010 \|pages=65–87 \|isbn=9780195372922 \|accessdate=21 March 2020}}</ref>

	==Application==		==Application==
Line 27:		Line 27:
	Due to the complexity and variability of public health data, like health care data generally, the issue of data modeling presents a particular challenge. Flat data sets for statistical analysis were the norm; however, today's requirements of interoperability and integrated sets of data across the public health enterprise require more sophistication. The relational database is increasingly the norm in public health informatics. Designers and implementers of the many sets of data required for various public health purposes must find a workable balance between very complex and abstract data models and simplistic, ''ad hoc'' models that untrained public health practitioners come up with and feel capable of working with.		Due to the complexity and variability of public health data, like health care data generally, the issue of data modeling presents a particular challenge. Flat data sets for statistical analysis were the norm; however, today's requirements of interoperability and integrated sets of data across the public health enterprise require more sophistication. The relational database is increasingly the norm in public health informatics. Designers and implementers of the many sets of data required for various public health purposes must find a workable balance between very complex and abstract data models and simplistic, ''ad hoc'' models that untrained public health practitioners come up with and feel capable of working with.

	Another challenge is found in the need to extract usable public health information from the mass of available heterogeneous data. The public health informaticist is thus required to become familiar with a variety of analysis tools, ranging from business intelligence tools to produce routine or ''ad hoc'' reports, to sophisticated statistical analysis tools and ~~geographical~~ information ~~systems~~ (GIS) to expose the geographical dimension of public health trends.		Another challenge is found in the need to extract usable public health information from the mass of available heterogeneous data. The public health informaticist is thus required to become familiar with a variety of analysis tools, ranging from business intelligence tools to produce routine or ''ad hoc'' reports, to sophisticated statistical analysis tools and [[geographic information system]]s (GIS) to expose the geographical dimension of public health trends.

	===In the United States===		===In the United States===
	The [[Centers for Disease Control and Prevention]] (CDC) in Atlanta, Georgia has played an important role in public health and [[infectious disease informatics]]. The agency's Center for Surveillance, Epidemiology and Laboratory Services (CSELS; formerly OSELS<ref name="ACDMinsApril13">{{cite web \|url=~~http~~://www.cdc.gov/~~about~~/~~pdf~~/~~advisory~~/~~4-25-13-acd-summary-v2~~.pdf \|format=PDF \|title=Advisory Committee to the Director: Record of the April 25, 2013 Meeting \|author=Advisory Committee to the Director \|publisher=Centers for Disease Control and Prevention \|pages=9–14 \|date=July 2013 \|accessdate=~~17 June 2014~~}}</ref><ref name="CDCOrgArch">{{cite web \|url=http://www.cdc.gov/maso/pdf/CDC_Official.pdf \|archiveurl=https://web.archive.org/web/20130718025323/http://www.cdc.gov/maso/pdf/CDC_Official.pdf \|format=PDF \|title=Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) \|publisher=Centers for Disease Control and Prevention \|date=27 July 2011 \|archivedate=18 July 2013 \|accessdate=17 June 2014}}</ref>) and its Division of Health Informatics and Surveillance (DHIS; formerly PHITPO and PHSIPO<ref name="ACDMinsApril13" /><ref name="CDCOrgArch" />) has focused on advancing the state of information science in these realms, applying digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations.<ref name="DHISAbout">{{cite web \|url=~~http~~://www.cdc.gov~~/ophss~~/csels/dhis/documents/~~DHIS~~-~~Overview~~-~~3132014~~.pdf \|format=PDF \|title=Division of Health Informatics and Surveillance \|author=Division of Health Informatics and Surveillance \|publisher=Centers for Disease Control and Prevention \|date=~~13 March 2014~~ \|accessdate=~~17 June 2014~~}}</ref> The CDC also created the National Electronic Disease Surveillance System (NEDSS)<ref name="DHISAbout" />, which includes a free comprehensive web and message-based reporting system called the NEDSS Base System (NBS), used for managing and transmitting reportable disease data.<ref name="NBSAbout">{{cite web \|url=~~http~~://wwwn.cdc.gov/nndss~~/script~~/nedss.~~aspx~~ \|title=~~NEDSS/NBS~~ \|author=Division of Health Informatics and Surveillance \|publisher=Centers for Disease Control and Prevention \|date=~~10 December 2013~~ \|accessdate=~~17 June 2014~~}}</ref>		The [[Centers for Disease Control and Prevention]] (CDC) in Atlanta, Georgia has played an important role in public health and [[infectious disease informatics]]. The agency's Center for Surveillance, Epidemiology and Laboratory Services (CSELS; formerly OSELS<ref name="ACDMinsApril13">{{cite web \|url=https://www.cdc.gov/maso/facm/pdfs/ACDCDC/20130425_CDCACD.pdf \|format=PDF \|title=Advisory Committee to the Director: Record of the April 25, 2013 Meeting \|author=Advisory Committee to the Director \|publisher=Centers for Disease Control and Prevention \|pages=9–14 \|date=July 2013 \|accessdate=21 March 2020}}</ref><ref name="CDCOrgArch">{{cite web \|url=http://www.cdc.gov/maso/pdf/CDC_Official.pdf \|archiveurl=https://web.archive.org/web/20130718025323/http://www.cdc.gov/maso/pdf/CDC_Official.pdf \|format=PDF \|title=Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) \|publisher=Centers for Disease Control and Prevention \|date=27 July 2011 \|archivedate=18 July 2013 \|accessdate=17 June 2014}}</ref>) and its Division of Health Informatics and Surveillance (DHIS; formerly PHITPO and PHSIPO<ref name="ACDMinsApril13" /><ref name="CDCOrgArch" />) has focused on advancing the state of information science in these realms, applying digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations.<ref name="DHISAbout">{{cite web \|url=https://www.cdc.gov/csels/dhis/documents/dhis-fact-sheet-508.pdf \|format=PDF \|title=Division of Health Informatics and Surveillance \|author=Division of Health Informatics and Surveillance \|publisher=Centers for Disease Control and Prevention \|date=19 June 2018 \|accessdate=21 March 2020}}</ref> The CDC also created the National Electronic Disease Surveillance System (NEDSS)<ref name="DHISAbout" />, which includes a free comprehensive web and message-based reporting system called the NEDSS Base System (NBS), used for managing and transmitting reportable disease data.<ref name="NBSAbout">{{cite web \|url=https://wwwn.cdc.gov/nndss/nedss.html \|title=National Notifiable Diseases Surveillance System (NNDSS) \|author=Division of Health Informatics and Surveillance \|publisher=Centers for Disease Control and Prevention \|date=16 March 2017 \|accessdate=21 March 2020}}</ref>

	Since 2002, the CDC has promoted the idea of the Public Health Information Network to facilitate the transmission of data from various partners in the health care industry and elsewhere (hospitals, clinical and environmental laboratories, doctors' practices, pharmacies) to local health agencies, then to state health agencies, and then to the CDC. At each stage the entity must be capable of receiving the data, storing it, aggregating it appropriately, and transmitting it to the next level.<ref name="PHIN02">{{cite web \|url=http://www.cdc.gov/phin/library/archive_2002/PHIN_Functions_Specifications_121802.pdf \|format=PDF \|title=Public Health Information Network Functions and Specifications, Version 1.2 \|publisher=Centers for Disease Control and Prevention \|date=18 December 2002 \|accessdate=~~17 June 2014~~}}</ref> To promote interoperability between the NBS and other informatics systems, the CDC has also encouraged the adoption of several standard vocabularies and messaging formats from the health care world. The most prominent of these are the [[Health Level 7]] (HL7) standards for health care messaging, the LOINC system for encoding laboratory test and result information, and the Systematized Nomenclature of Medicine (SNOMED) vocabulary of health care concepts.<ref name="NBSAbout" />		Since 2002, the CDC has promoted the idea of the Public Health Information Network to facilitate the transmission of data from various partners in the health care industry and elsewhere (hospitals, clinical and environmental laboratories, doctors' practices, pharmacies) to local health agencies, then to state health agencies, and then to the CDC. At each stage the entity must be capable of receiving the data, storing it, aggregating it appropriately, and transmitting it to the next level.<ref name="PHIN02">{{cite web \|url=http://www.cdc.gov/phin/library/archive_2002/PHIN_Functions_Specifications_121802.pdf \|archiveurl=https://web.archive.org/web/20111023111340/http://www.cdc.gov/phin/library/archive_2002/PHIN_Functions_Specifications_121802.pdf \|format=PDF \|title=Public Health Information Network Functions and Specifications, Version 1.2 \|publisher=Centers for Disease Control and Prevention \|date=18 December 2002 \|archivedate=23 October 2011 \|accessdate=21 March 2020}}</ref> To promote interoperability between the NBS and other informatics systems, the CDC has also encouraged the adoption of several standard vocabularies and messaging formats from the health care world. The most prominent of these are the [[Health Level 7]] (HL7) standards for health care messaging, the LOINC system for encoding laboratory test and result information, and the Systematized Nomenclature of Medicine (SNOMED) vocabulary of health care concepts.<ref name="NBSAbout" />

	A typical example of data transmissions to the CDC would be infectious disease data, which hospitals, labs, and doctors are legally required to report to local health agencies. The local health agencies must then report to their state public health department and the states must report in aggregate form to the CDC. Among other uses of this received data, the CDC publishes the ''Morbidity and Mortality Weekly Report'' (MMWR), "the agency’s primary vehicle for scientific publication of timely, reliable, authoritative, accurate, objective, and useful public health information and recommendations."<ref name="MMWRAbout">{{cite web \|url=~~http~~://www.cdc.gov/mmwr/about.html \|title=About the Morbidity and Mortality Weekly Report (MMWR) Series \|publisher=Centers for Disease Control and Prevention \|date=~~15 January 2010~~ \|accessdate=~~17 June 2014~~}}</ref>		A typical example of data transmissions to the CDC would be infectious disease data, which hospitals, labs, and doctors are legally required to report to local health agencies. The local health agencies must then report to their state public health department and the states must report in aggregate form to the CDC. Among other uses of this received data, the CDC publishes the ''Morbidity and Mortality Weekly Report'' (MMWR), "the agency’s primary vehicle for scientific publication of timely, reliable, authoritative, accurate, objective, and useful public health information and recommendations."<ref name="MMWRAbout">{{cite web \|url=https://www.cdc.gov/mmwr/about.html \|title=About the Morbidity and Mortality Weekly Report (MMWR) Series \|publisher=Centers for Disease Control and Prevention \|date=04 March 2020 \|accessdate=21 March 2020}}</ref>

	==Notes==		==Notes==
Line 41:		Line 41:

	==References==		==References==
	~~<references/>~~		{{Reflist\|3}}

	<!---Place all category tags here-->		<!---Place all category tags here-->
	[[Category:Informatics]]		[[Category:Informatics]]

Shawndouglas: Added image

2014-06-17T17:24:36Z

Added image

← Older revision		Revision as of 17:24, 17 June 2014
Line 1:		Line 1:
			[[Image:Drug overdose death rates by state per 100,000 people 2008 US.png\|right\|600px\|thumbnail\|Collecting and utilizing vital statistics data is only one of many applications of public health informatics.]]
	'''Public health informatics''' has been defined as "the systematic application of [[information]] and computer science and technology to public health practice, research, and learning."<ref name="YasnoffPHI">{{cite journal \|url=http://people.dbmi.columbia.edu/~rik7001/Yasnoff.pdf \|format=PDF \|journal=Journal of Public Health Management and Practice \|title=Public Health Informatics: Improving and Transforming Public Health in the Information Age \|author=Yasnoff, William A.; O’Carroll, Patrick W.; Koo, Denise; Linkins, Robert W.; Kilbourne, Edwin M. \|volume=6 \|issue=6 \|pages=67–75 \|year=2000 \|pmid=18019962 \|accessdate=11 June 2014}}</ref><ref name="FriedePHI">{{cite journal \|url=http://www.annualreviews.org/doi/abs/10.1146/annurev.pu.16.050195.001323 \|journal=Annual Review of Public Health \|title=Public Health Informatics: How Information-Age Technology Can Strengthen Public Health \|author=Friede, Andrew; Blum, Henrik L.; McDonald, Mike \|volume=16 \|pages=239–252 \|year=1995 \|doi=10.1146/annurev.pu.16.050195.001323 \|accessdate=11 June 2014}}</ref> Like other types of informatics, public health informatics is a multidisciplinary field, involving the studies of [[Informatics (academic field)\|informatics]], computer science, psychology, law, statistics, epidemiology, and microbiology.		'''Public health informatics''' has been defined as "the systematic application of [[information]] and computer science and technology to public health practice, research, and learning."<ref name="YasnoffPHI">{{cite journal \|url=http://people.dbmi.columbia.edu/~rik7001/Yasnoff.pdf \|format=PDF \|journal=Journal of Public Health Management and Practice \|title=Public Health Informatics: Improving and Transforming Public Health in the Information Age \|author=Yasnoff, William A.; O’Carroll, Patrick W.; Koo, Denise; Linkins, Robert W.; Kilbourne, Edwin M. \|volume=6 \|issue=6 \|pages=67–75 \|year=2000 \|pmid=18019962 \|accessdate=11 June 2014}}</ref><ref name="FriedePHI">{{cite journal \|url=http://www.annualreviews.org/doi/abs/10.1146/annurev.pu.16.050195.001323 \|journal=Annual Review of Public Health \|title=Public Health Informatics: How Information-Age Technology Can Strengthen Public Health \|author=Friede, Andrew; Blum, Henrik L.; McDonald, Mike \|volume=16 \|pages=239–252 \|year=1995 \|doi=10.1146/annurev.pu.16.050195.001323 \|accessdate=11 June 2014}}</ref> Like other types of informatics, public health informatics is a multidisciplinary field, involving the studies of [[Informatics (academic field)\|informatics]], computer science, psychology, law, statistics, epidemiology, and microbiology.

Shawndouglas: Added references.

2014-06-17T17:18:23Z

Added references.

← Older revision		Revision as of 17:18, 17 June 2014
Line 29:		Line 29:

	===In the United States===		===In the United States===
	The [[Centers for Disease Control and Prevention]] (CDC) in Atlanta, Georgia has played an important role in public health and [[infectious disease informatics]]. The agency's ~~Public~~ Health Informatics and ~~Technology Program Office~~ (PHITPO) has focused on advancing the state of information science in these realms, applying digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations. The CDC also created the National Electronic Disease Surveillance System (NEDSS), which includes a free comprehensive web and message-based reporting system called the NEDSS Base System (NBS), used for managing and transmitting reportable disease data.		The [[Centers for Disease Control and Prevention]] (CDC) in Atlanta, Georgia has played an important role in public health and [[infectious disease informatics]]. The agency's Center for Surveillance, Epidemiology and Laboratory Services (CSELS; formerly OSELS<ref name="ACDMinsApril13">{{cite web \|url=http://www.cdc.gov/about/pdf/advisory/4-25-13-acd-summary-v2.pdf \|format=PDF \|title=Advisory Committee to the Director: Record of the April 25, 2013 Meeting \|author=Advisory Committee to the Director \|publisher=Centers for Disease Control and Prevention \|pages=9–14 \|date=July 2013 \|accessdate=17 June 2014}}</ref><ref name="CDCOrgArch">{{cite web \|url=http://www.cdc.gov/maso/pdf/CDC_Official.pdf \|archiveurl=https://web.archive.org/web/20130718025323/http://www.cdc.gov/maso/pdf/CDC_Official.pdf \|format=PDF \|title=Department of Health and Human Services, Centers for Disease Control and Prevention (CDC) \|publisher=Centers for Disease Control and Prevention \|date=27 July 2011 \|archivedate=18 July 2013 \|accessdate=17 June 2014}}</ref>) and its Division of Health Informatics and Surveillance (DHIS; formerly PHITPO and PHSIPO<ref name="ACDMinsApril13" /><ref name="CDCOrgArch" />) has focused on advancing the state of information science in these realms, applying digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations.<ref name="DHISAbout">{{cite web \|url=http://www.cdc.gov/ophss/csels/dhis/documents/DHIS-Overview-3132014.pdf \|format=PDF \|title=Division of Health Informatics and Surveillance \|author=Division of Health Informatics and Surveillance \|publisher=Centers for Disease Control and Prevention \|date=13 March 2014 \|accessdate=17 June 2014}}</ref> The CDC also created the National Electronic Disease Surveillance System (NEDSS)<ref name="DHISAbout" />, which includes a free comprehensive web and message-based reporting system called the NEDSS Base System (NBS), used for managing and transmitting reportable disease data.<ref name="NBSAbout">{{cite web \|url=http://wwwn.cdc.gov/nndss/script/nedss.aspx \|title=NEDSS/NBS \|author=Division of Health Informatics and Surveillance \|publisher=Centers for Disease Control and Prevention \|date=10 December 2013 \|accessdate=17 June 2014}}</ref>

	Since ~~about 2005~~, the CDC has promoted the idea of the Public Health Information Network to facilitate the transmission of data from various partners in the health care industry and elsewhere (hospitals, clinical and environmental laboratories, doctors' practices, pharmacies) to local health agencies, then to state health agencies, and then to the CDC. At each stage the entity must be capable of receiving the data, storing it, aggregating it appropriately, and transmitting it to the next level. To promote interoperability between the NBS and other informatics systems, the CDC has also encouraged the adoption of several standard vocabularies and messaging formats from the health care world. The most prominent of these are the [[Health Level 7]] (HL7) standards for health care messaging, the LOINC system for encoding laboratory test and result information, and the Systematized Nomenclature of Medicine (SNOMED) vocabulary of health care concepts.		Since 2002, the CDC has promoted the idea of the Public Health Information Network to facilitate the transmission of data from various partners in the health care industry and elsewhere (hospitals, clinical and environmental laboratories, doctors' practices, pharmacies) to local health agencies, then to state health agencies, and then to the CDC. At each stage the entity must be capable of receiving the data, storing it, aggregating it appropriately, and transmitting it to the next level.<ref name="PHIN02">{{cite web \|url=http://www.cdc.gov/phin/library/archive_2002/PHIN_Functions_Specifications_121802.pdf \|format=PDF \|title=Public Health Information Network Functions and Specifications, Version 1.2 \|publisher=Centers for Disease Control and Prevention \|date=18 December 2002 \|accessdate=17 June 2014}}</ref> To promote interoperability between the NBS and other informatics systems, the CDC has also encouraged the adoption of several standard vocabularies and messaging formats from the health care world. The most prominent of these are the [[Health Level 7]] (HL7) standards for health care messaging, the LOINC system for encoding laboratory test and result information, and the Systematized Nomenclature of Medicine (SNOMED) vocabulary of health care concepts.<ref name="NBSAbout" />

	A typical example of data transmissions to the CDC would be infectious disease data, which hospitals, labs, and doctors are legally required to report to local health agencies. The local health agencies must then report to their state public health department and the states must report in aggregate form to the CDC. Among other uses of this received data, the CDC publishes the ''Morbidity and Mortality Weekly Report'' (MMWR), "the agency’s primary vehicle for scientific publication of timely, reliable, authoritative, accurate, objective, and useful public health information and recommendations."		A typical example of data transmissions to the CDC would be infectious disease data, which hospitals, labs, and doctors are legally required to report to local health agencies. The local health agencies must then report to their state public health department and the states must report in aggregate form to the CDC. Among other uses of this received data, the CDC publishes the ''Morbidity and Mortality Weekly Report'' (MMWR), "the agency’s primary vehicle for scientific publication of timely, reliable, authoritative, accurate, objective, and useful public health information and recommendations."<ref name="MMWRAbout">{{cite web \|url=http://www.cdc.gov/mmwr/about.html \|title=About the Morbidity and Mortality Weekly Report (MMWR) Series \|publisher=Centers for Disease Control and Prevention \|date=15 January 2010 \|accessdate=17 June 2014}}</ref>

	==Notes==		==Notes==

	Some ~~portions~~ of this article are reused from [http://en.wikipedia.org/wiki/Public_health_informatics the Wikipedia article].		Some elements of this article are reused from [http://en.wikipedia.org/wiki/Public_health_informatics the Wikipedia article].

	==References==		==References==

Shawndouglas: Added more history. Saving and adding more references.

2014-06-16T22:59:30Z

Added more history. Saving and adding more references.

← Older revision		Revision as of 22:59, 16 June 2014
Line 9:		Line 9:

	==History==		==History==
	Before the advent of the Internet, public health data, like other healthcare and business data, were collected on paper forms and stored centrally at the relevant public health agency. As computers became more commonplace, some data and information would be computerized, requiring a distinct data entry process, storage in various file formats, and analysis by mainframe computers using standard batch processing. With the coming of the Internet and cheaper large-scale storage technologies, public health agencies with sufficient resources began transitioning to web-accessible collections of public health data, and, more recently, to automated messaging of the same information.		Before the advent of the Internet, public health data, like other healthcare and business data, were collected on paper forms and stored centrally at the relevant public health agency. As computers became more commonplace, some data and information would be computerized, requiring a distinct data entry process, storage in various file formats, and analysis by mainframe computers using standard batch processing. With the coming of the Internet and cheaper large-scale storage technologies, public health agencies with sufficient resources began transitioning to web-accessible collections of public health data, and, more recently, to automated messaging of the same information.<ref name="OCarrollPHI">{{cite book \|url=http://books.google.com/books?id=ap6uCR0Ybo4C \|title=Public Health Informatics and Information Systems \|author=O'Carroll, Patrick W. \|publisher=Springer \|year=2003 \|pages=790 \|isbn=9780387954745 \|accessdate=16 June 2014}}</ref><ref name="LombardoDS">{{cite book \|url=http://books.google.com/books?id=-xI2Kl39ZzoC&printsec=frontcover \|chapter=Chapter 1: Disease Surveillance, a Public Health Priority \|title=Disease Surveillance: A Public Health Informatics Approach \|author=Lombardo, Joseph S.; Buckeridge, David L. \|publisher=John Wiley & Sons \|year=2012 \|pages=1–40 \|isbn=9781118569054 \|accessdate=16 June 2014}}</ref><ref name="LeePrincPrac">{{cite book \|url=http://books.google.com/books?id=FF78GCiUbwUC&pg=PA70 \|chapter=Chapter 5: Informatics and the Management of Surveillance Data \|title=Principles and Practice of Public Health Surveillance \|author=Krishnamurthy, Ramesh S.; St. Louis, Michael E. \|publisher=Oxford University Press \|year=2010 \|pages=65–87 \|isbn=9780195372922 \|accessdate=16 June 2014}}</ref>

	==Application==		==Application==
	In the United States and other parts of the world, public health informatics is practiced by individuals in public health agencies at the national, state, and larger local health jurisdiction levels. Additionally, research and training in public health informatics takes place at a variety of academic institutions. In the United States, the bulk of public health informatics activities takes place at the state and local level, in the state departments of health and the county or parish departments of health. In other parts of the world the bulk of activities may occur at a national level, with local jurisdictions reporting directly to an appropriate government or health-related entity. Activities may include:		In the United States and other parts of the world, public health informatics is practiced by individuals in public health agencies at the national, state, and larger local health jurisdiction levels. Additionally, research and training in public health informatics takes place at a variety of academic institutions. In the United States, the bulk of public health informatics activities takes place at the state and local level, in the state departments of health and the county or parish departments of health. In other parts of the world the bulk of activities may occur at a national level, with local jurisdictions reporting directly to an appropriate government or health-related entity. Activities may include<ref name="OCarrollPHI" /><ref name="LombardoDS" />:

	* collecting and storing vital statistics such as birth and death records.		* collecting and storing vital statistics such as birth and death records.
Line 21:		Line 21:
	* collecting hospital capacity information to allow for planning of responses in case of emergencies.		* collecting hospital capacity information to allow for planning of responses in case of emergencies.

	As part of the collection and application of public health data, several challenges still exist. Some entities may simply not be aware they need to report data to other entities. A lack of resources of either the reporter or collector may also hinder reporting and sharing of data. In some parts of the world, a lack of interoperability of data interchange formats (which can be at the purely syntactic or at the semantic level) may lead to under- or non-reported public health data. Finally, variations in reporting requirements across the states, territories, and localities pose challenges, which itself may lead to variability of incoming data to public health jurisdictions, requiring greater data quality standards.		As part of the collection and application of public health data, several challenges still exist. Some entities may simply not be aware they need to report data to other entities. A lack of resources of either the reporter or collector may also hinder reporting and sharing of data. In some parts of the world, a lack of interoperability of data interchange formats (which can be at the purely syntactic or at the semantic level) may lead to under- or non-reported public health data. Finally, variations in reporting requirements across the states, territories, and localities pose challenges, which itself may lead to variability of incoming data to public health jurisdictions, requiring greater data quality standards.<ref name="LeePrincPrac" />

	==Informatics==		==Informatics==

Shawndouglas: Updated content formatting. Need to go back and add references later.

2014-06-11T22:57:22Z

Updated content formatting. Need to go back and add references later.

Show changes

Shawndouglas: Updated intro.

2014-06-11T20:39:32Z

Updated intro.

← Older revision		Revision as of 20:39, 11 June 2014
Line 1:		Line 1:
	'''Public ~~Health Informatics~~''' has been defined as the systematic application of information and [[computer science]] and technology to public health practice, research, and learning. ~~It is one~~ of the ~~sub~~-~~domains~~ of ~~biomedical~~ informatics.		'''Public health informatics''' has been defined as "the systematic application of [[information]] and computer science and technology to public health practice, research, and learning."<ref name="YasnoffPHI">{{cite journal \|url=http://people.dbmi.columbia.edu/~rik7001/Yasnoff.pdf \|format=PDF \|journal=Journal of Public Health Management and Practice \|title=Public Health Informatics: Improving and Transforming Public Health in the Information Age \|author=Yasnoff, William A.; O’Carroll, Patrick W.; Koo, Denise; Linkins, Robert W.; Kilbourne, Edwin M. \|volume=6 \|issue=6 \|pages=67–75 \|year=2000 \|pmid=18019962 \|accessdate=11 June 2014}}</ref><ref name="FriedePHI">{{cite journal \|url=http://www.annualreviews.org/doi/abs/10.1146/annurev.pu.16.050195.001323 \|journal=Annual Review of Public Health \|title=Public Health Informatics: How Information-Age Technology Can Strengthen Public Health \|author=Friede, Andrew; Blum, Henrik L.; McDonald, Mike \|volume=16 \|pages=239–252 \|year=1995 \|doi=10.1146/annurev.pu.16.050195.001323 \|accessdate=11 June 2014}}</ref> Like other types of informatics, public health informatics is a multidisciplinary field, involving the studies of [[Informatics (academic field)\|informatics]], computer science, psychology, law, statistics, epidemiology, and microbiology.

			In 2000, researcher William A. Yasnoff and his colleagues identified four key aspects that differentiate public health informatics from [[Health informatics\|medical informatics]] and other informatics specialty areas. Public health informatics<ref name="YasnoffPHI" />:

			# focuses on "applications of information science and technology that promote the health of populations as opposed to the health of specific individuals."
			# focuses on "applications of information science and technology that prevent disease and injury by altering the conditions or the environment that put populations of individuals at risk."
			# "explore[s] the potential for prevention at all vulnerable points in the causal chains leading to disease, injury, or disability; applications should not be restricted to particular social, behavioral, or environmental contexts."
			# "reflect[s] the governmental context in which public health is practiced."


	==United States==		==United States==

Shawndouglas: Added attribution.

2014-04-24T18:54:18Z

Added attribution.

← Older revision		Revision as of 18:54, 24 April 2014
Line 38:		Line 38:

	* SAPPHIRE (Health care) or ''Situational Awareness and Preparedness for Public Health Incidences and Reasoning Engines'' is a semantics-based health information system capable of tracking and evaluating situations and occurrences that may affect public health.		* SAPPHIRE (Health care) or ''Situational Awareness and Preparedness for Public Health Incidences and Reasoning Engines'' is a semantics-based health information system capable of tracking and evaluating situations and occurrences that may affect public health.

			==Notes==

			Many portions of this article are reused from [http://en.wikipedia.org/wiki/Public_health_informatics the Wikipedia article].

	==References==		==References==

	<references/>		<references/>
	* Public Health Informatics and Information Systems by D.A. Ross, A.R. Hinman, K. Saarlas, and W.H. Foege (Hardcover - Oct 16, 2002) ISBN 0-387-95474-0		* Public Health Informatics and Information Systems by D.A. Ross, A.R. Hinman, K. Saarlas, and W.H. Foege (Hardcover - Oct 16, 2002) ISBN 0-387-95474-0

Shawndouglas: /* United States */ Internal links

2014-04-03T16:56:16Z

United States: Internal links

← Older revision		Revision as of 16:56, 3 April 2014
Line 7:		Line 7:
	At the [[Centers for Disease Control and Prevention]] (CDC) in Atlanta, Georgia, the [http://www.cdc.gov/osels/ph_informatics_technology/index.html Public Health Informatics and Technology Program Office (PHITPO)] focuses on advancing the state of information science and applies digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations. The three sub-units within PHITPO include Informatics Practice, Policy and Coordination; Informatics Solutions and Operations; and Informatics Research and Development.		At the [[Centers for Disease Control and Prevention]] (CDC) in Atlanta, Georgia, the [http://www.cdc.gov/osels/ph_informatics_technology/index.html Public Health Informatics and Technology Program Office (PHITPO)] focuses on advancing the state of information science and applies digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations. The three sub-units within PHITPO include Informatics Practice, Policy and Coordination; Informatics Solutions and Operations; and Informatics Research and Development.

	The bulk of the work of public health informatics in the United States, as with public health generally, takes place at the state and local level, in the state departments of health and the county or parish departments of health. At a state health department the activities may include: collection and storage of ''vital statistics'' (birth and death records); collection of reports of communicable disease cases from doctors, hospitals, and laboratories, used for infectious disease surveillance; display of infectious disease statistics and trends; collection of child immunization and lead screening information; daily collection and analysis of emergency room data to detect early evidence of biological threats; collection of hospital capacity information to allow for planning of responses in case of emergencies. Each of these activities presents its own information processing challenge.		The bulk of the work of public health informatics in the United States, as with public health generally, takes place at the state and local level, in the state departments of health and the county or parish departments of health. At a state health department the activities may include: collection and storage of ''vital statistics'' (birth and death records); collection of reports of communicable disease cases from doctors, [[Hospital\|hospitals]], and [[Laboratory\|laboratories]], used for infectious disease surveillance; display of infectious disease statistics and trends; collection of child immunization and lead screening information; daily collection and analysis of emergency room data to detect early evidence of biological threats; collection of hospital capacity information to allow for planning of responses in case of emergencies. Each of these activities presents its own information processing challenge.

	===Collection of public health data===		===Collection of public health data===

Shawndouglas: Internal link

2014-03-23T17:38:32Z

Internal link

← Older revision		Revision as of 17:38, 23 March 2014
Line 5:		Line 5:
	In the United States, public health informatics is practiced by individuals in public health agencies at the federal and state levels and in the larger local health jurisdictions. Additionally, research and training in public health informatics takes place at a variety of academic institutions.		In the United States, public health informatics is practiced by individuals in public health agencies at the federal and state levels and in the larger local health jurisdictions. Additionally, research and training in public health informatics takes place at a variety of academic institutions.

	At the ~~federal~~ Centers for Disease Control and Prevention in Atlanta, Georgia, the [http://www.cdc.gov/osels/ph_informatics_technology/index.html Public Health Informatics and Technology Program Office (PHITPO)] focuses on advancing the state of information science and applies digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations. The three sub-units within PHITPO include Informatics Practice, Policy and Coordination; Informatics Solutions and Operations; and Informatics Research and Development.		At the [[Centers for Disease Control and Prevention]] (CDC) in Atlanta, Georgia, the [http://www.cdc.gov/osels/ph_informatics_technology/index.html Public Health Informatics and Technology Program Office (PHITPO)] focuses on advancing the state of information science and applies digital information technologies to aid in the detection and management of diseases and syndromes in individuals and populations. The three sub-units within PHITPO include Informatics Practice, Policy and Coordination; Informatics Solutions and Operations; and Informatics Research and Development.

	The bulk of the work of public health informatics in the United States, as with public health generally, takes place at the state and local level, in the state departments of health and the county or parish departments of health. At a state health department the activities may include: collection and storage of ''vital statistics'' (birth and death records); collection of reports of communicable disease cases from doctors, hospitals, and laboratories, used for infectious disease surveillance; display of infectious disease statistics and trends; collection of child immunization and lead screening information; daily collection and analysis of emergency room data to detect early evidence of biological threats; collection of hospital capacity information to allow for planning of responses in case of emergencies. Each of these activities presents its own information processing challenge.		The bulk of the work of public health informatics in the United States, as with public health generally, takes place at the state and local level, in the state departments of health and the county or parish departments of health. At a state health department the activities may include: collection and storage of ''vital statistics'' (birth and death records); collection of reports of communicable disease cases from doctors, hospitals, and laboratories, used for infectious disease surveillance; display of infectious disease statistics and trends; collection of child immunization and lead screening information; daily collection and analysis of emergency room data to detect early evidence of biological threats; collection of hospital capacity information to allow for planning of responses in case of emergencies. Each of these activities presents its own information processing challenge.