OBJECTIVES: We examined whether automated electronic laboratory reporting of notifiable-diseases results in information being delivered to public health departments more completely and quickly than is the case with spontaneous, paper-based reporting. METHODS: We used data from a local public health department, hospital infection control departments, and a community-wide health information exchange to identify all potential cases of notifiable conditions that occurred in Marion County, Ind, during the first quarter of 2001. We compared traditional spontaneous reporting to the health department with automated electronic laboratory reporting through the health information exchange. RESULTS: After reports obtained using the 2 methods had been matched, there were 4785 unique reports for 53 different conditions during the study period. Chlamydia was the most common condition, followed by hepatitis B, hepatitis C, and gonorrhea. Automated electronic laboratory reporting identified 4.4 times as many cases as traditional spontaneous, paper-based methods and identified those cases 7.9 days earlier than spontaneous reporting. CONCLUSIONS: Automated electronic laboratory reporting improves the completeness and timeliness of disease surveillance, which will enhance public health awareness and reporting efficiency.
OBJECTIVES: We examined whether automated electronic laboratory reporting of notifiable-diseases results in information being delivered to public health departments more completely and quickly than is the case with spontaneous, paper-based reporting. METHODS: We used data from a local public health department, hospital infection control departments, and a community-wide health information exchange to identify all potential cases of notifiable conditions that occurred in Marion County, Ind, during the first quarter of 2001. We compared traditional spontaneous reporting to the health department with automated electronic laboratory reporting through the health information exchange. RESULTS: After reports obtained using the 2 methods had been matched, there were 4785 unique reports for 53 different conditions during the study period. Chlamydia was the most common condition, followed by hepatitis B, hepatitis C, and gonorrhea. Automated electronic laboratory reporting identified 4.4 times as many cases as traditional spontaneous, paper-based methods and identified those cases 7.9 days earlier than spontaneous reporting. CONCLUSIONS: Automated electronic laboratory reporting improves the completeness and timeliness of disease surveillance, which will enhance public health awareness and reporting efficiency.
Authors: Anil A Panackal; Nkuchia M M'ikanatha; Fu-Chiang Tsui; Joan McMahon; Michael M Wagner; Bruce W Dixon; Juan Zubieta; Maureen Phelan; Sara Mirza; Juliette Morgan; Daniel Jernigan; A William Pasculle; James T Rankin; Rana A Hajjeh; Lee H Harrison Journal: Emerg Infect Dis Date: 2002-07 Impact factor: 6.883
Authors: Daniel B Jernigan; Pratima L Raghunathan; Beth P Bell; Ross Brechner; Eddy A Bresnitz; Jay C Butler; Marty Cetron; Mitch Cohen; Timothy Doyle; Marc Fischer; Carolyn Greene; Kevin S Griffith; Jeannette Guarner; James L Hadler; James A Hayslett; Richard Meyer; Lyle R Petersen; Michael Phillips; Robert Pinner; Tanja Popovic; Conrad P Quinn; Jennita Reefhuis; Dori Reissman; Nancy Rosenstein; Anne Schuchat; Wun-Ju Shieh; Larry Siegal; David L Swerdlow; Fred C Tenover; Marc Traeger; John W Ward; Isaac Weisfuse; Steven Wiersma; Kevin Yeskey; Sherif Zaki; David A Ashford; Bradley A Perkins; Steve Ostroff; James Hughes; David Fleming; Jeffrey P Koplan; Julie L Gerberding Journal: Emerg Infect Dis Date: 2002-10 Impact factor: 6.883
Authors: Deepthi Rajeev; Catherine Staes; R Scott Evans; Andrea Price; Mary Hill; Susan Mottice; Ilene Risk; Robert Rolfs Journal: AMIA Annu Symp Proc Date: 2011-10-22
Authors: Patina Zarcone; Dale Nordenberg; Michelle Meigs; Ulrike Merrick; Daniel Jernigan; Steven H Hinrichs Journal: Public Health Rep Date: 2010 May-Jun Impact factor: 2.792
Authors: Ross Lazarus; Michael Klompas; Francis X Campion; Scott J N McNabb; Xuanlin Hou; James Daniel; Gillian Haney; Alfred DeMaria; Leslie Lenert; Richard Platt Journal: J Am Med Inform Assoc Date: 2008-10-24 Impact factor: 4.497
Authors: Erika Samoff; Mary T Fangman; Aaron T Fleischauer; Anna E Waller; Pia D M Macdonald Journal: Public Health Rep Date: 2013 Sep-Oct Impact factor: 2.792