Improving Cattle Market Syndromic Surveillance Through Electronic Data Capture

Leah Estberg, Randy Munger, Cynthia Zepeda, Judy Akkina, Susan Rollo, Andy Schwartz

Abstract


ObjectiveImplement a mobile technology platform to capture and transmitsyndromic cattle data collected at Texas market sales.IntroductionAn active syndromic surveillance system was designed to collectcattle health information from a sample of Texas cattle market sales.Texas Animal Health Commission livestock inspectors record the totalnumber of animals observed along with the total number displayingclinical signs of interest grouped into body system categories(e.g. respiratory, neurologic, etc.). Inspection reports are submitted tothe United States Department of Agriculture Veterinary Services (VS)Risk Identification Team for monitoring.MethodsThe pilot project started in 2012 with paper-based data collectionforms to both 1) gain trust from the inspector supervisors and 2)evaluate the value of the system with minimal early investment.The data collected at each sale on paper-based forms were later enteredinto spreadsheets at the office. These sale inspection reports were thensubmitted to the inspector’s supervisor for review prior to forwardingby email to VS. VS staff aggregated data from each spreadsheet in toa centralized database and conducted weekly monitoring.Recently, a new reporting system was developed at VS to enablecollection and transmission of the data on mobile devices runningan Android operating system capable of transmitting data to VS viaa Wi-Fi connection. The new system was deployed March 2016following in-person training, release of a user guide document, and amonth of user testing.ResultsBetween March 2014 and June 2016 a total of 1,330 sale inspectionreports from 16 markets were submitted by spreadsheet an average11 days following the sale (range: 1 day through 141 days followingthe sale). These reports were tracked for data quality issues thatrequired manual intervention. It was discovered that 64 (4.8%) ofthe reports required correction. The most common types of dataquality issues were market sale date not provided, market alias ID notprovided, report submitted more than once, and report not submittedas an Excel file but as an image, such as a pdf file.Between March and June 2016 a total of 160 sale inspection reportsfrom 16 markets were submitted using mobile devices an average7 days following the sale (range: same day through 47 days followingthe sale). All data submitted could be directly imported into thecentralized database and processed as needed for monitoring withoutany data correction required.Some challenges encountered with deploying the mobile technologysystem included addressing the VS Information Technology securityrequirements for establishing user accounts and implementing directdata upload into VS systems. Additionally, Wi-Fi connectivity can bedifficult in some remote areas.Some advantages to using the mobile technology included havingthe option to download and run the application on most mobile devicesrunning the Android operating system. There was an improvementin data reporting timeliness of 4 days on average, and the rangesubstantially narrowed. There was also time savings for inspectorswho no longer needed to transfer hard copy data to a spreadsheet,and for VS personnel who no longer needed to aggregate data fromindividual spreadsheets. Improvements in data quality included theability to directly report that sales were canceled or not attended;the ability to provide comments at various levels of detail related to thesale, the pen of animals observed, or specific signs observed; and therequirement to supply essential data elements such as sale date andmarket ID.ConclusionsThe conversion from a paper and spreadsheet-based sale inspectionreport to a mobile technology platform resulted in significant timesavings and data quality improvements that appeared to justify thesystem development and deployment costs and challenges. Thesebenefits support potential expansion of the system.

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DOI: https://doi.org/10.5210/ojphi.v9i1.7640



Online Journal of Public Health Informatics * ISSN 1947-2579 * http://ojphi.org