Biomedical subjects

Michael M Wagner

Publications and source records attributed to Michael M Wagner.

30 records · Page 2Linked to original sources

PubMed2003

Telephone triage: a timely data source for surveillance of influenza-like diseases.

We evaluated telephone triage (TT) data for public health early warning systems. TT data is electronically available and contains coded elements that include the demographics and description of a caller's medical complaints. In the study, we obtained emergency room TT data and after hours TT data from a commercial TT software and service company. We compared the timeliness of the TT data with influenza surveillance data from the Centers for Disease Control using the cross correlation function. Emergency room TT calls are one to five weeks ahead of surveillance data collected by the CDC.

Disease Outbreaks↗

PubMed2003

Detection of pediatric respiratory and gastrointestinal outbreaks from free-text chief complaints.

We conducted a retrospective study to ascertain the potential of free-text chief complaints collected in pediatric emergency departments to serve as surveillance data for early detection of outbreaks. We determined that automatically coded chief complaint data provide a signal that reflects outbreaks in a population of children less than five years of age. Using the Exponentially Weighted Moving Average (EWMA) detection algorithm, we measured the timeliness, sensitivity, and specificity of free-text chief complaints for predicting outbreaks of pediatric respiratory and gastrointestinal illness. We found that time series of automatically coded free text-chief complaints in pediatric patients correlate well with hospital admissions and precede them by the mean of 10.3 days (95% CI -15.15, 35.5) for respiratory outbreaks and 29 days (95% CI 4.23, 53.7) for gastrointestinal outbreaks. We conclude that free-text chief complaints may play an important role as an early, sensitive and specific indicator of outbreaks of respiratory and gastrointestinal illness in children less than five years of age.

Child, Preschool↗

PubMed2003

A framework for infection control surveillance using association rules.

Surveillance of antibiotic resistance and nosocomial infections is one of the most important functions of a hospital infection control program. We employed the association rule method for automatically identifying new, unexpected, and potentially interesting patterns in hospital infection control. We hypothesized that mining for low-support, low-confidence rules would detect unexpected outbreaks caused by a small number of cases. To build a framework, we preprocessed the data and added new templates to eliminate uninteresting patterns. We applied our method to the culture data collected over 3 months from 10 hospitals in the UPMC Health System. We found that the new process and system are efficient and effective in identifying new, unexpected, and potentially interesting patterns in surveillance data. The clinical relevance and utility of this process await the results of prospective studies.

Algorithms↗

PubMed2003

Detection of outbreaks from time series data using wavelet transform.

In this paper, we developed a new approach to detection of disease outbreaks based on wavelet transform. It is capable of dealing with two problems found in real-world time series data, namely, negative singularity and long-term trends, which may degrade the performance of current approaches to outbreak detection. To test this approach, we introduced artificail disease outbreaks and negative singularities into a real world dataset and applied it and two other algorithms-autoregressive (AR) and Multi-resolution Wavelet Auto-regressive (MWAR) - to this dataset. We compared the performance of these algorithms in terms of sensitivity, specificity and timeliness. The results showed that our approach had similar sensitivity and specificity and slightly better timeliness compared to the other two algorithms. When we introduced negative singularities, its performance did not degrade as much as the other two algorithms' performance. We conclude that our approach to detection, when compared to traditional approaches, may not be as susceptible to degradation of performance caused by negative singularities.

Algorithms↗

PubMed2002

Automatic electronic laboratory-based reporting of notifiable infectious diseases at a large health system.

Electronic laboratory-based reporting, developed by the UPMC Health System, Pittsburgh, Pennsylvania, was evaluated to determine if it could be integrated into the conventional paper-based reporting system. We reviewed reports of 10 infectious diseases from 8 UPMC hospitals that reported to the Allegheny County Health Department in southwestern Pennsylvania during January 1-November 26, 2000. Electronic reports were received a median of 4 days earlier than conventional reports. The completeness of reporting was 74% (95% confidence interval [CI] 66% to 81%) for the electronic laboratory-based reporting and 65% (95% CI 57% to 73%) for the conventional paper-based reporting system (p>0.05). Most reports (88%) missed by electronic laboratory-based reporting were caused by using free text. Automatic reporting was more rapid and as complete as conventional reporting. Using standardized coding and minimizing free text usage will increase the completeness of electronic laboratory-based reporting.

Clinical Laboratory Information Systems↗

PubMed2002

Rapid deployment of an electronic disease surveillance system in the state of Utah for the 2002 Olympic Winter Games.

The key to minimizing the effects of an intentionally caused disease outbreak is early detection of the attack and rapid identification of the affected individuals. The Bush administration's leadership in advocating for biosurveillance systems capable of monitoring for bioterrorism attacks suggests that we should move quickly to establish a nationwide early warning biosurveillance system as a defense against this threat. The spirit of collaboration and unity inspired by the events of 9-11 and the 2002 Olympic Winter Games in Salt Lake City provided the opportunity to demonstrate how a prototypic biosurveillance system could be rapidly deployed. In seven weeks we were able to implement an automated, real-time disease outbreak detection system in the State of Utah and monitored 80,684 acute care visits occurring during a 28-day period spanning the Olympics. No trends of immediate public health concern were identified.

Bioterrorism↗

PubMed2002

Accuracy of three classifiers of acute gastrointestinal syndrome for syndromic surveillance.

ICD-9-coded emergency department (ED) diagnoses and free-text triage diagnoses are routinely collected data elements that have potential value for public health surveillance and early detection of epidemics. We constructed and measured performance of three classifiers for the detection of cases of acute gastrointestinal syndrome of public health significance: one used ICD-9-coded ED diagnosis as input data; the other two used free-text triage diagnosis. We measured the performance of these classifiers against the expert classification of cases based on review of ED reports. The sensitivity of the ICD-9-code classifier was 0.32, and the specificity was 0.99. The sensitivity of a naïve Bayes classifier using triage diagnoses was 0.63, the specificity was 0.94, and the area under the ROC curve was 0.82. A bigram Bayes classifier had sensitivity 0.38, specificity 0.94, and area under the ROC of 0.69. We conclude that a naive Bayes classifier of free-text triage diagnosis data provides more sensitive and earlier detection of cases of acute gastrointestinal syndrome than either a bigram Bayes classifier or an ICD-9 code classifier. The sensitivity achieved should be sufficient for syndromic surveillance system designed to detect moderate to large epidemics.

Acute Disease↗

PubMed2002

Data, network, and application: technical description of the Utah RODS Winter Olympic Biosurveillance System.

Given the post September 11th climate of possible bioterrorist attacks and the high profile 2002 Winter Olympics in the Salt Lake City, Utah, we challenged ourselves to deploy a computer-based real-time automated biosurveillance system for Utah, the Utah Real-time Outbreak and Disease Surveillance system (Utah RODS), in six weeks using our existing Real-time Outbreak and Disease Surveillance (RODS) architecture. During the Olympics, Utah RODS received real-time HL-7 admission messages from 10 emergency departments and 20 walk-in clinics. It collected free-text chief complaints, categorized them into one of seven prodromes classes using natural language processing, and provided a web interface for real-time display of time series graphs, geographic information system output, outbreak algorithm alerts, and details of the cases. The system detected two possible outbreaks that were dismissed as the natural result of increasing rates of Influenza. Utah RODS allowed us to further understand the complexities underlying the rapid deployment of a RODS-like system.

Algorithms↗

PubMedDate not supplied

How outbreaks of infectious disease are detected: a review of surveillance systems and outbreaks.

To learn how outbreaks of infectious disease are detected and to describe the entities and information systems that together function to identify outbreaks in the U.S., the authors drew on multiple sources of information to create a description of existing surveillance systems and how they interact to detect outbreaks. The results of this analysis were summarized in a system diagram. The authors reviewed a sample of recent outbreaks to determine how they were detected, with reference to the system diagram. The de facto U.S. system for detection of outbreaks consists of five components: the clinical health care system, local/state health agencies, federal agencies, academic/professional organizations, and collaborating governmental organizations. Primary data collection occurs at the level of clinical health care systems and local health agencies. The review of a convenience sample of outbreaks showed that all five components of the system participated in aggregating, analyzing, and sharing data. The authors conclude that the current U.S. approach to detection of disease outbreaks is complex and involves many organizations interacting in a loosely coupled manner. State and local health departments and the health care system are major components in the detection of outbreaks.

Communicable Disease Control↗

PubMedDate not supplied

The space race and biodefense: lessons from NASA about big science and the role of medical informatics.

The events that followed the launch of Sputnik on Oct 4, 1957, provide a metaphor for the events that are following the first bioterroristic case of pulmonary anthrax in the United States. This paper uses that metaphor to elucidate the nature of the task ahead and to suggest questions such as, Can the goals of the biodefense effort be formulated as concisely and concretely as the goal of the space program? Can we measure success in biodefense as we did for the space project? What are the existing resources that are the equivalents of propulsion systems and rocket engineers that can be applied to the problems of biodefense?

Anthrax↗

PubMedDate not supplied

Roundtable on bioterrorism detection: information system-based surveillance.

During the 2001 AMIA Annual Symposium, the Anesthesia, Critical Care, and Emergency Medicine Working Group hosted the Roundtable on Bioterrorism Detection. Sixty-four people attended the roundtable discussion, during which several researchers discussed public health surveillance systems designed to enhance early detection of bioterrorism events. These systems make secondary use of existing clinical, laboratory, paramedical, and pharmacy data or facilitate electronic case reporting by clinicians. This paper combines case reports of six existing systems with discussion of some common techniques and approaches. The purpose of the roundtable discussion was to foster communication among researchers and promote progress by 1) sharing information about systems, including origins, current capabilities, stages of deployment, and architectures; 2) sharing lessons learned during the development and implementation of systems; and 3) exploring cooperation projects, including the sharing of software and data. A mailing list server for these ongoing efforts may be found at http://bt.cirg.washington.edu.

Bioterrorism↗

PubMedDate not supplied

The informatics response in disaster, terrorism, and war.

The United States currently faces several new, concurrent large-scale health crises as a result of terrorist activity. In particular, three major health issues have risen sharply in urgency and public consciousness--bioterrorism, the threat of widespread delivery of agents of illness; mass disasters, local events that produce large numbers of casualties and overwhelm the usual capacity of health care delivery systems; and the delivery of optimal health care to remote military field sites. Each of these health issues carries large demands for the collection, analysis, coordination, and distribution of health information. The authors present overviews of these areas and discuss ongoing work efforts of experts in each.

Bioterrorism↗