Electronic Medical Records (EMR)

Group A beta-hemolytic Streptococcus (GABHS) has caused outbreaks in recruit training environments, where it leads to significant morbidity and, on occasion, has been linked to deaths. Streptococcal surveillance has long been a part of military recruit public health activities. All Navy and Marine Corps training sites are required to track and record positive throat cultures and rapid tests on weekly basis. The Navy and Marine Corps have used bicillin prophylaxis as an effective control measure against GABHS outbreaks at recruit training sites. Though streptococcal control program policies vary by site, a minimum prophylaxis protocol is required and mass prophylax is indicated when local GABHS rates exceed a specific threshold. Before July 2007, prophylaxis upon initial entry was required between October and March, and when the local rate exceeded 10 cases per 1000 recruits. In July 2007, the Navy instituted a policy of mass prophylaxis upon initial entry throughout the year. Evaluation of GABHS cases before and after implementation of the new policy, including overall rates, identification of outbreaks, and inpatient results will help enhance the Navy’s ability to evaluate threshold levels, provide systematic/standardized monitoring across the three recruit sites, and inform prophylaxis and monitoring strategies.

Objective

To compare trends of group A beta-hemolytic Streptococcus among recruits before and after changes in prophylaxis implementation using electronic laboratory and medical encounter records.

A comprehensive electronic medical record (EMR) represents a rich source of information that can be harnessed for epidemic surveillance. At this time, however, we do not know how EMR-based data elements should be combined to improve the performance of surveillance systems. In a manual EMR review of over 15 000 outpatient encounters, we observed that two-thirds of the cases with an acute respiratory infection (ARI) were seen in the emergency room or other urgent care areas, but that these areas received only 15% of total outpatient visits. Because of this seemingly favorable signal-to-noise ratio, we hypothesized that an ARI surveillance system that focused on urgent visits would outperform one that monitored all outpatient visits.

A comprehensive electronic medical record (EMR) represents a rich source of information that can be harnessed for epidemic surveillance. At this time, however, we do not know how EMR-based data elements should be combined to improve the performance of surveillance systems. In a manual EMR review of over 15 000 outpatient encounters, we observed that two-thirds of the cases with an acute respiratory infection (ARI) were seen in the emergency room or other urgent care areas, but that these areas received only 15% of total outpatient visits.1 Because of this seemingly favorable signal-to-noise ratio, we hypothesized that an ARI surveillance system that focused on urgent visits would outperform one that monitored all outpatient visits.

Current influenza-like illness (ILI) monitoring in Idaho is based on syndromic surveillance using laboratory data, combined with periodic person-to-person reports collected by Idaho state workers. This system relies on voluntary reporting.

Electronic medical records offer a method of obtaining data in an automated fashion. The Computerized Patient Record System (CPRS) captures real-time visit information, vital signs, ICD-9, pharmacy, and lab data. The electronic medical record surveillance has been utilized for syndromic surveillance on a regional level. Funds supporting expansion of electronic medical records offer increased ability for use in biosurveillance. The addition of temporo-spatial modeling may improve identification of clusters of cases. This abstract reviews our efforts to develop a real-time system of identifying ILI in Idaho using Veterans Administration data and temporo-spatial techniques.

Objective

The objective of this study is to describe initial efforts to establish a real-time syndromic surveillance of ILI in Idaho, using data from the Veterans Administration electronic medical record (CPRS).

GI disease outbreaks can be focal (for example, restaurant associated), generalized (for example, seasonal rotavirus increases) or intermediate (for example, widely disseminated contaminated commercial products). Health departments (HDs) are commonly notified of focal outbreaks by passive reporting, whereas generalized outbreaks in non-institutional settings are seldom reported as clusters. Intermediate outbreaks are often detected via laboratory testing, which may be subjected to backlogs and delays. Healthcare systems routinely collect in EMRs clinical data related to GI disease, such as ambulatory care diagnoses, that could be exploited for surveillance. Multiple syndromic and laboratory data sources could potentially be used to prospectively detect generalized and intermediate GI disease outbreaks for situational awareness and possible epidemiological investigation.

Objective

To identify which syndromic and laboratory-based data streams from electronic medical records (EMRs) may be used to detect gastrointestinal (GI) disease outbreaks in a timely manner.

Microorganisms resistant to antibiotics (ABX) increase the mortality, morbidity and costs of infections. In the absence of a drug development pipeline that can keep pace with the emerging resistancemechanisms, these organisms are expected to threaten public health for years to come. Because exposure to ABX promotes the development of bacterial resistance, health care providers have long been urged to avoid using antibiotics to treat conditions that they are unlikely to improve, including many uncomplicated acute respiratory infections. We asked if interposing clinical decision support software at the time of electronic order entry could adjust ABX utilization toward consensus guidelines for these conditions.