Can long-term historical data from electronic medical records improve surveillance for epidemics of acute respiratory infections? A systematic evaluation.

Background: As the deployment of electronic medical records (EMR) expands, so is the availability of long-term datasets that could serve to enhance public health surveillance. We hypothesized that EMR-based surveillance systems that incorporate seasonality and other long-term trends would discover outbreaks of acute respiratory infections (ARI) sooner than systems that only consider the recent past.

Methods: We simulated surveillance systems aimed at discovering modeled influenza outbreaks injected into backgrounds of patients with ARI.

Decision support during electronic prescription to stem antibiotic overuse for acute respiratory infections: a long-term, quasi-experimental study.

Background: Interventions to support decision-making can reduce inappropriate antibiotic use for acute respiratory infections (ARI), but they may not be sustainable. The objective of the study is to evaluate the long-term effectiveness of a clinical decision-support system (CDSS) interposed at the time of electronic (e-) prescriptions for selected antibiotics.

Methods: This is a retrospective, observational intervention study, conducted within a large, statewide Veterans Affairs health system.

Restrictive versus liberal red blood cell transfusion strategy after hip surgery: a decision model analysis of healthcare costs.

Background: Red blood cell transfusion related to select surgical procedures accounts for approximately 2.8 million transfusions in the United States yearly and occurs commonly after hip fracture surgeries. Randomized controlled trials have demonstrated lack of clinical benefit with higher versus lower transfusion thresholds in postoperative hip fracture repair patients with cardiac disease or risk factors for cardiac disease.

Epidemic surveillance using an electronic medical record: an empiric approach to performance improvement.

Backgrounds: Electronic medical records (EMR) form a rich repository of information that could benefit public health. We asked how structured and free-text narrative EMR data should be combined to improve epidemic surveillance for acute respiratory infections (ARI).

Methods: Eight previously characterized ARI case detection algorithms (CDA) were applied to historical EMR entries to create authentic time series of daily ARI case counts (background).

Using the electronic medical record to identify community-acquired pneumonia: toward a replicable automated strategy.

Background: Timely information about disease severity can be central to the detection and management of outbreaks of acute respiratory infections (ARI), including influenza. We asked if two resources: 1) free text, and 2) structured data from an electronic medical record (EMR) could complement each other to identify patients with pneumonia, an ARI severity landmark.

Methods: A manual EMR review of 2747 outpatient ARI visits with associated chest imaging identified x-ray reports that could support the diagnosis of pneumonia (kappa score  = 0.

A sustainable strategy to prevent misuse of antibiotics for acute respiratory infections.

Backgrounds: Over 50% of antibiotics prescriptions are for outpatients with acute respiratory infections (ARI). Many of them are not needed and thus contribute both avoidable adverse events and pressures toward the development of bacterial resistance. Could a clinical decision support system (CDSS), interposed at the time of electronic prescription, adjust antibiotics utilization toward consensus treatment guidelines for ARI?

Methods: This is a retrospective comparison of pre- (2002) and post-intervention (2003-2006) periods at two comprehensive health care systems (intervention and control).

Analysis of False Positive Errors of an Acute Respiratory Infection Text Classifier due to Contextual Features.

Text classifiers have been used for biosurveillance tasks to identify patients with diseases or conditions of interest. When compared to a clinical reference standard of 280 cases of Acute Respiratory Infection (ARI), a text classifier consisting of simple rules and NegEx plus string matching for specific concepts of interest produced 569 (4%) false positive (FP) cases. Using instance level manual annotation we estimate the prevalence of contextual attributes and error types leading to FP cases.

Combining free text and structured electronic medical record entries to detect acute respiratory infections.

Background: The electronic medical record (EMR) contains a rich source of information that could be harnessed for epidemic surveillance. We asked if structured EMR data could be coupled with computerized processing of free-text clinical entries to enhance detection of acute respiratory infections (ARI).

Methodology: A manual review of EMR records related to 15,377 outpatient visits uncovered 280 reference cases of ARI.

Racial/ethnic and age disparities in chemotherapy selection for colorectal cancer.

Objectives: To test the hypotheses that African American patients and older patients with stage IV colorectal cancer were less likely to receive newer chemotherapy agents.

Study Design: Retrospective cohort design.

Methods: Among 5068 Surveillance, Epidemiology, and End Results-Medicare patients diagnosed as having stage IV colorectal cancer between 2000 and 2002, a total of 2466 received chemotherapy and were included in the analysis.

Outcomes of irinotecan-based chemotherapy regimens in elderly Medicare patients with metastatic colorectal cancer.

Background: Several population-based studies have confirmed the benefits of adjuvant chemotherapy with 5-fluorouracil/leucovorin for treatment of colorectal cancer. Few population-based studies have evaluated other chemotherapies that are now available for colorectal cancer management.

Objective: This study primarily sought to evaluate the survival benefit of first-line irinotecan use in a group of Medicare patients with stage IV (metastatic) colorectal cancer.

Optimizing A syndromic surveillance text classifier for influenza-like illness: Does document source matter?

Syndromic surveillance systems that incorporate electronic free-text data have primarily focused on extracting concepts of interest from chief complaint text, emergency department visit notes, and nurse triage notes. Due to availability and access, there has been limited work in the area of surveilling the full text of all electronic note documents compared with more specific document sources. This study provides an evaluation of the performance of a text classifier for detection of influenza-like illness (ILI) by document sources that are commonly used for biosurveillance by comparing them to routine visit notes, and a full electronic note corpus approach.

Adaptation of the NegEx algorithm to Veterans Affairs electronic text notes for detection of influenza-like illness (ILI).

We tested automated detection of influenza-like illness (ILI) from free-text clinician notes extracted from the VA electronic medical record using a simple negation algorithm coupled with string matching for relevant ILI symptoms mapped to UMLS concepts. Additionally, we documented negation problems encountered and adaptations made to the negation algorithm when applied to the full texts of a diverse array of VA note types and templates.

Using cost-effectiveness analysis to sharpen formulary decision-making: the example of tiotropium at the Veterans Affairs health care system.

Objective: To identify a cost-saving subset of criteria for the use of tiotropium at a Veterans Affairs Medical Center based on a cost-effectiveness analysis with ipratropium as the comparator.

Methods: Retrospective analysis of electronic medical records for the calendar year 2004 was conducted. The sample was drawn from a population at the Baltimore Veterans Affairs Medical Center that had a confirmed diagnosis of chronic obstructive pulmonary disease (COPD) and had filled prescriptions for ipratropium.

Application of Natural Language Processing to VA Electronic Health Records to Identify Phenotypic Characteristics for Clinical and Research Purposes.

Informatics tools to extract and analyze clinical information on patients have lagged behind data-mining developments in bioinformatics. While the analyses of an individual's partial or complete genotype is nearly a reality, the phenotypic characteristics that accompany the genotype are not well known and largely inaccessible in free-text patient health records. As the adoption of electronic medical records increases, there exists an urgent need to extract pertinent phenotypic information and make that available to clinicians and researchers.

Prescription of amiodarone through a computerized template that includes both decision support and executive functions improves the monitoring for toxicities.

The antiarrhythmic drug amiodarone causes severe side effects that warrant active monitoring. In a given patient, monitoring for amiodarone toxicities involves checking past results of five laboratory/imaging tests and reordering four of these tests every 6 to 12 month, a process that is both complex and time-consuming. We hypothesized that a software tool that automated the retrieval and ordering of these tests in a context-sensitive manner would improve the completeness of surveillance for drug toxicities.

Vancomycin-resistant enterococci: a road map on how to prevent the emergence and transmission of antimicrobial resistance.

Nosocomial acquisition of microorganisms resistant to multiple antibiotics represents a threat to patient safety. Here we review the mechanisms that have allowed highly resistant strains belonging to the Enterococcus genus to proliferate within our health-care institutions. These mechanisms indicate that decreasing the prevalence of resistant organisms requires active surveillance, adherence to vigorous isolation, hand hygiene and environmental decontamination measures, and effective antibiotic stewardship.