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Arch Pediatr Adolesc Med. 2011 Jan;165(1):61-7. doi: 10.1001/archpediatrics.2010.250.

Integrating spatial epidemiology into a decision model for evaluation of facial palsy in children.

Author information

1
Division of Emergency Medicine, Children's Hospital Boston, Boston, MA 02115, USA. andrew.fine@childrens.harvard.edu

Abstract

OBJECTIVE:

To develop a novel diagnostic algorithm for Lyme disease among children with facial palsy by integrating public health surveillance data with traditional clinical predictors.

DESIGN:

Retrospective cohort study.

SETTING:

Children's Hospital Boston emergency department, 1995-2007.

PATIENTS:

Two hundred sixty-four children (aged <20 years) with peripheral facial palsy who were evaluated for Lyme disease.

MAIN OUTCOME MEASURES:

Multivariate regression was used to identify independent clinical and epidemiologic predictors of Lyme disease facial palsy.

RESULTS:

Lyme diagnosis was positive in 65% of children from high-risk counties in Massachusetts during Lyme disease season compared with 5% of those without both geographic and seasonal risk factors. Among patients with both seasonal and geographic risk factors, 80% with 1 clinical risk factor (fever or headache) and 100% with 2 clinical factors had Lyme disease. Factors independently associated with Lyme disease facial palsy were development from June to November (odds ratio, 25.4; 95% confidence interval, 8.3-113.4), residence in a county where the most recent 3-year average Lyme disease incidence exceeded 4 cases per 100,000 (18.4; 6.5-68.5), fever (3.9; 1.5-11.0), and headache (2.7; 1.3-5.8). Clinical experts correctly treated 68 of 94 patients (72%) with Lyme disease facial palsy, but a tool incorporating geographic and seasonal risk identified all 94 cases.

CONCLUSIONS:

Most physicians intuitively integrate geographic information into Lyme disease management, but we demonstrate quantitatively how formal use of geographically based incidence in a clinical algorithm improves diagnostic accuracy. These findings demonstrate potential for improved outcomes from investments in health information technology that foster bidirectional communication between public health and clinical settings.

PMID:
21199982
PMCID:
PMC3644029
DOI:
10.1001/archpediatrics.2010.250
[Indexed for MEDLINE]
Free PMC Article

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