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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
- Source :
- BMC Medical Informatics and Decision Making, Vol 17, Iss 1, Pp 1-8 (2017)
- Publication Year :
- 2017
- Publisher :
- BMC, 2017.
-
Abstract
- Abstract Background 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. Methods 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. Results 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
Details
- Language :
- English
- ISSN :
- 14726947
- Volume :
- 17
- Issue :
- 1
- Database :
- Directory of Open Access Journals
- Journal :
- BMC Medical Informatics and Decision Making
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.0e955c6118784a34a856f924539ee4a6
- Document Type :
- article
- Full Text :
- https://doi.org/10.1186/s12911-017-0491-8