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Completeness and timeliness of notifiable disease reporting: a comparison of laboratory and provider reports submitted to a large county health department

Overview of attention for article published in BMC Medical Informatics and Decision Making, June 2017
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  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

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Title
Completeness and timeliness of notifiable disease reporting: a comparison of laboratory and provider reports submitted to a large county health department
Published in
BMC Medical Informatics and Decision Making, June 2017
DOI 10.1186/s12911-017-0491-8
Pubmed ID
Authors

Brian E. Dixon, Zuoyi Zhang, Patrick T. S. Lai, Uzay Kirbiyik, Jennifer Williams, Rebecca Hills, Debra Revere, P. Joseph Gibson, Shaun J. Grannis

Abstract

Most public health agencies expect reporting of diseases to be initiated by hospital, laboratory or clinic staff even though so-called passive approaches are known to be burdensome for reporters and produce incomplete as well as delayed reports, which can hinder assessment of disease and delay recognition of outbreaks. In this study, we analyze patterns of reporting as well as data completeness and timeliness for traditional, passive reporting of notifiable disease by two distinct sources of information: hospital and clinic staff versus clinical laboratory staff. Reports were submitted via fax machine as well as electronic health information exchange interfaces. Data were extracted from all submitted notifiable disease reports for seven representative diseases. Reporting rates are the proportion of known cases having a corresponding case report from a provider, a faxed laboratory report or an electronic laboratory report. Reporting rates were stratified by disease and compared using McNemar's test. For key data fields on the reports, completeness was calculated as the proportion of non-blank fields. Timeliness was measured as the difference between date of laboratory confirmed diagnosis and the date the report was received by the health department. Differences in completeness and timeliness by data source were evaluated using a generalized linear model with Pearson's goodness of fit statistic. We assessed 13,269 reports representing 9034 unique cases. Reporting rates varied by disease with overall rates of 19.1% for providers and 84.4% for laboratories (p < 0.001). All but three of 15 data fields in provider reports were more often complete than those fields within laboratory reports (p <0.001). Laboratory reports, whether faxed or electronically sent, were received, on average, 2.2 days after diagnosis versus a week for provider reports (p <0.001). Despite growth in the use of electronic methods to enhance notifiable disease reporting, there still exists much room for improvement.

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The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 62 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 16%
Student > Doctoral Student 6 10%
Professor > Associate Professor 5 8%
Other 4 6%
Student > Bachelor 3 5%
Other 11 18%
Unknown 23 37%
Readers by discipline Count As %
Nursing and Health Professions 13 21%
Medicine and Dentistry 11 18%
Engineering 4 6%
Social Sciences 2 3%
Biochemistry, Genetics and Molecular Biology 1 2%
Other 4 6%
Unknown 27 44%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 August 2021.
All research outputs
#6,480,423
of 22,982,639 outputs
Outputs from BMC Medical Informatics and Decision Making
#623
of 2,002 outputs
Outputs of similar age
#104,260
of 316,289 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#16
of 42 outputs
Altmetric has tracked 22,982,639 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 2,002 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 316,289 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 42 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 61% of its contemporaries.