Ang, BCH; Chen, MIC; Goh, TLH; Ng, YY; Fan, SW; (2005) An assessment of electronically captured data in the patient care enhancement system (PACES) for syndromic surveillance. Annals of the Academy of Medicine, Singapore, 34 (9). pp. 539-534. ISSN 0304-4602 https://researchonline.lshtm.ac.uk/id/eprint/8671
Permanent Identifier
Use this permanent URL when citing or linking to this resource.
https://researchonline.lshtm.ac.uk/id/eprint/8671
Abstract
INTRODUCTION: A common approach to the surveillance of emerging infectious diseases and agents of bioterrorism is to analyse electronically captured data for disease syndromes. The Patient Care Enhancement System (PACES) is a form of electronic medical records presently in service in the Singapore Armed Forces (SAF). We assess the feasibility of PACES data for surveillance, describe time-trends, and identify methods of sub-analysis which could improve performance. MATERIALS AND METHODS: Medical consults from July 2000 to June 2003 were extracted. Diagnosis codes were mapped to 7 infectious disease syndromes according to the categorisation in the Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE): gastrointestinal (GI), fever (FEVER), respiratory, (RESP), coma (COMA), neurological (NEURO), dermatologic-haemorrhagic (DERMHEM) and dermatologic- infectious (DERM-INF). RESULTS: A total of 732,233 episodes of care were analysed. Weekly periodicity was observed, with decreased weekend consults; there were no obvious seasonal trends in any of the syndromes. RESP, FEVER and GI syndromes were common events. Sub-analyses, either by restricting to cases with a repeated consultation, or grouping the data by medical centres, could dramatically lower thresholds used to flag outbreaks. CONCLUSION: In spite of the level of background noise inherent in a system consisting mainly of primary care consults, sub-analysis by medical centre, or restriction to cases with repeated consults were able to yield sensitive thresholds for outbreak detection.
Item Type | Article |
---|---|
Keywords | Adolescent, Adult, Humans, Infection/*epidemiology, *Medical Records Systems, Computerized, Population Surveillance, Syndrome, Adolescent, Adult, Humans, Infection, epidemiology, Medical Records Systems, Computerized, Population Surveillance, Syndrome |
Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology (-2023) |
PubMed ID | 16284674 |
ISI | 233309800003 |