Automatic Electronic Laboratory-Based Reporting of Notifiable Infectious Diseases

Panackal, Anil A.; M’ikanatha, Nkuchia M.; Tsui, Fu-Chiang; McMahon, Joan; Wagner, Michael M.; Dixon, Bruce; Zubieta, Juan Carlos; Phelan, Maureen; Mirza, Sara; Morgan, Juliette; Jernigan, Daniel B.; Pasculle, A. William; Rankin, J S; Hajjeh, Rana; Harrison, Lee H.

doi:10.3201/eid0807.010493

Cited by 101 publications

(70 citation statements)

References 6 publications

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“…However, since there should not be a longer delay between the onset date and the date of sample collection, one could conclude that the timeliness in the reporting has improved since then. Also studies from other countries have shown that meningococcal infection, measles and/or salmonellosis were reported most rapidly, while TB and other mycobacteria had the longest delays (8,9,11,14,15,18,19). The conclusion drawn from all these studies is that differences in the delays between diseases seem to be dependent on the level of urgency.…”

Section: Discussionmentioning

confidence: 95%

Timeliness of case reporting in the Swedish statutory surveillance of communicable diseases 1998–2002

Jansson

Arneborn

Skärlund

et al. 2004

Scandinavian Journal of Infectious Diseases

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To prepare for a new communicable disease act in Sweden, we performed an in-depth analysis of the performance of the present notification system (1998--2002). Four diseases were selected for analysis (meningococcal infection, salmonellosis, infection with penicillin-resistant pneumococci and tularaemia). Each step in the double notification flow (clinical and laboratory notifications) was studied and paper-based and electronic notifications compared. More than 15 possible single dates in the notification flows were analysed for 27,000 cases. The shortest notification flows (from date of sample collection to when the first notification was received at SMI--clinical or laboratory notification) were seen for meningococcal infections and salmonellosis (median 7 d) and the longest for tularaemia (11 d). Laboratory notifications were faster than clinical notifications, and electronic reporting 1.5-1.7 times faster than paper notifications. Further gains should be expected from the new electronic reporting system (SmiNet2), which will allow also clinical reporting electronically over the internet.

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Section: Discussionmentioning

confidence: 95%

Timeliness of case reporting in the Swedish statutory surveillance of communicable diseases 1998–2002

Jansson

Arneborn

Skärlund

et al. 2004

Scandinavian Journal of Infectious Diseases

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“…In the last 15 years, electronic reporting has been recommended often as an instrument to improve timeliness and efficiency of laboratory reports in several U.S. states, The Netherlands, Sweden, and Korea (3, 6,13,14,18,21,22,[25][26][27][28]. However, a number of authors recommended revising or abandoning the reporting of gastroenteritis or food poisoning because the timeliness of the report was variable and often too late for effective action (4 , 24).…”

Section: Discussionmentioning

confidence: 96%

Timeliness of Electronic Reporting and Acceptability of Public Health Follow-Up of Routine Nonparatyphoidal and Nontyphoidal Salmonella Infections, London and South East England, 2010 to 2011

Severi

Dabrera²,

Boxall³

et al. 2014

Journal of Food Protection

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Nonparatyphoidal and nontyphoidal Salmonella (NTS) infections are major causes of food poisoning in England. Diagnostic laboratories and clinicians have a statutory responsibility to report NTS infection cases to the Health Protection Agency via various means, with electronic reporting encouraged as the universal method. The Health Protection Agency (Public Health England since 1 April 2013) refers cases to environmental health departments for follow-up. Timeliness of reporting and adequacy of NTS infection case follow-up are key factors in the implementation of public health actions. Laboratories, health protection units, and environmental health departments in London and South East (SE) regions of England completed three surveys between December 2010 and April 2011, collecting data about the NTS infection case reporting methods and the time elapsed between symptom onset and public health actions. The median period between symptom onset and public health investigation was 25 days in London and 23 days in SE when electronic reporting was used and 12 days in London and 11 days in SE when other means of reporting were used. The most common follow-up method was a telephone questionnaire in London (53%) and a postal questionnaire in SE (52%). The telephone questionnaire had the highest response rate (98% in London; 96% in SE). Timeliness and efficiency of electronic NTS infection case reports can be improved by decreasing the electronic laboratory report period and using telephone-administered questionnaires to maximize the public health benefit when following up single cases of NTS infection.

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“…There has been substantial public health investment and basic research to extend traditional methods of case detection—notifiable disease reporting and sentinel physician systems—to include electronic surveillance that leverages routinely collected information such as laboratory test orders and results [1–2], chief complaints [3–6], sales of over-the-counter medications [7–8], and encounter notes [9–10]. Accompanying the search for better data, there has been substantial research on the problem of inferring the existence of cases, outbreaks, and outbreak characteristics such as disease incidence, transmission parameters, future course [11–13], and temporal [14–21], spatial [22–27], and spatiotemporal characteristics [28–29].…”

Section: Introductionmentioning

confidence: 99%

A study of the transferability of influenza case detection systems between two large healthcare systems

Wagner

Cooper

et al. 2017

PLoS ONE

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ObjectivesThis study evaluates the accuracy and transferability of Bayesian case detection systems (BCD) that use clinical notes from emergency department (ED) to detect influenza cases.MethodsA BCD uses natural language processing (NLP) to infer the presence or absence of clinical findings from ED notes, which are fed into a Bayesain network classifier (BN) to infer patients’ diagnoses. We developed BCDs at the University of Pittsburgh Medical Center (BCDUPMC) and Intermountain Healthcare in Utah (BCDIH). At each site, we manually built a rule-based NLP and trained a Bayesain network classifier from over 40,000 ED encounters between Jan. 2008 and May. 2010 using feature selection, machine learning, and expert debiasing approach. Transferability of a BCD in this study may be impacted by seven factors: development (source) institution, development parser, application (target) institution, application parser, NLP transfer, BN transfer, and classification task. We employed an ANOVA analysis to study their impacts on BCD performance.ResultsBoth BCDs discriminated well between influenza and non-influenza on local test cases (AUCs > 0.92). When tested for transferability using the other institution’s cases, BCDUPMC discriminations declined minimally (AUC decreased from 0.95 to 0.94, p<0.01), and BCDIH discriminations declined more (from 0.93 to 0.87, p<0.0001). We attributed the BCDIH decline to the lower recall of the IH parser on UPMC notes. The ANOVA analysis showed five significant factors: development parser, application institution, application parser, BN transfer, and classification task.ConclusionWe demonstrated high influenza case detection performance in two large healthcare systems in two geographically separated regions, providing evidentiary support for the use of automated case detection from routinely collected electronic clinical notes in national influenza surveillance. The transferability could be improved by training Bayesian network classifier locally and increasing the accuracy of the NLP parser.

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Automatic Electronic Laboratory-Based Reporting of Notifiable Infectious Diseases

Cited by 101 publications

References 6 publications

Timeliness of case reporting in the Swedish statutory surveillance of communicable diseases 1998–2002

Timeliness of case reporting in the Swedish statutory surveillance of communicable diseases 1998–2002

Timeliness of Electronic Reporting and Acceptability of Public Health Follow-Up of Routine Nonparatyphoidal and Nontyphoidal Salmonella Infections, London and South East England, 2010 to 2011

A study of the transferability of influenza case detection systems between two large healthcare systems

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