tetano
Editor, Senior Moderator
PLoS One. 2013 Dec 26;8(12):e84077. doi: 10.1371/journal.pone.0084077.
Combining surveillance systems: effective merging of u.s. Veteran and military health data.
Pavlin JA1, Burkom HS2, Elbert Y2, Lucero-Obusan C3, Winston CA3, Cox KL4, Oda G3, Lombardo JS2, Holodniy M3.
Author information
Abstract
BACKGROUND:
The U.S. Department of Veterans Affairs (VA) and Department of Defense (DoD) had more than 18 million healthcare beneficiaries in 2011. Both Departments conduct individual surveillance for disease events and health threats.
METHODS:
We performed joint and separate analyses of VA and DoD outpatient visit data from October 2006 through September 2010 to demonstrate geographic and demographic coverage, timeliness of influenza epidemic awareness, and impact on spatial cluster detection achieved from a joint VA and DoD biosurveillance platform.
RESULTS:
Although VA coverage is greater, DoD visit volume is comparable or greater. Detection of outbreaks was better in DoD data for 58% and 75% of geographic areas surveyed for seasonal and pandemic influenza, respectively, and better in VA data for 34% and 15%. The VA system tended to alert earlier with a typical H3N2 seasonal influenza affecting older patients, and the DoD performed better during the H1N1 pandemic which affected younger patients more than normal influenza seasons. Retrospective analysis of known outbreaks demonstrated clustering evidence found in separate DoD and VA runs, which persisted with combined data sets.
CONCLUSION:
The analyses demonstrate two complementary surveillance systems with evident benefits for the national health picture. Relative timeliness of reporting could be improved in 92% of geographic areas with access to both systems, and more information provided in areas where only one type of facility exists. Combining DoD and VA data enhances geographic cluster detection capability without loss of sensitivity to events isolated in either population and has a manageable effect on customary alert rates.
PMID:
24386335
[PubMed - in process]
PMCID:
PMC3873400
Free PMC Article
http://www.ncbi.nlm.nih.gov/pubmed/24386335
Combining surveillance systems: effective merging of u.s. Veteran and military health data.
Pavlin JA1, Burkom HS2, Elbert Y2, Lucero-Obusan C3, Winston CA3, Cox KL4, Oda G3, Lombardo JS2, Holodniy M3.
Author information
Abstract
BACKGROUND:
The U.S. Department of Veterans Affairs (VA) and Department of Defense (DoD) had more than 18 million healthcare beneficiaries in 2011. Both Departments conduct individual surveillance for disease events and health threats.
METHODS:
We performed joint and separate analyses of VA and DoD outpatient visit data from October 2006 through September 2010 to demonstrate geographic and demographic coverage, timeliness of influenza epidemic awareness, and impact on spatial cluster detection achieved from a joint VA and DoD biosurveillance platform.
RESULTS:
Although VA coverage is greater, DoD visit volume is comparable or greater. Detection of outbreaks was better in DoD data for 58% and 75% of geographic areas surveyed for seasonal and pandemic influenza, respectively, and better in VA data for 34% and 15%. The VA system tended to alert earlier with a typical H3N2 seasonal influenza affecting older patients, and the DoD performed better during the H1N1 pandemic which affected younger patients more than normal influenza seasons. Retrospective analysis of known outbreaks demonstrated clustering evidence found in separate DoD and VA runs, which persisted with combined data sets.
CONCLUSION:
The analyses demonstrate two complementary surveillance systems with evident benefits for the national health picture. Relative timeliness of reporting could be improved in 92% of geographic areas with access to both systems, and more information provided in areas where only one type of facility exists. Combining DoD and VA data enhances geographic cluster detection capability without loss of sensitivity to events isolated in either population and has a manageable effect on customary alert rates.
PMID:
24386335
[PubMed - in process]
PMCID:
PMC3873400
Free PMC Article
http://www.ncbi.nlm.nih.gov/pubmed/24386335