Elliot M. Fielstein

Combat veterans with posttraumatic stress disorder exhibit decreased habituation of the P1 midlatency auditory evoked potential

The current study used a paired stimulus paradigm to investigate the P1 midlatency auditory evoked potential in Vietnam combat veterans with posttraumatic stress disorder (PTSD) and three comparison groups: alcohol dependents, combat-exposed normals, and combat-unexposed normals. Compared to each comparison group, PTSD subjects exhibited significantly diminished habituation of the P1 potential. P1 potential habituation within the PTSD group, correlated significantly with intensity of PTSD reexperiencing symptoms, such as trauma-related nightmares and flashbacks. These findings are discussed as consistent with a sensory gating defect at the brainstem level in PTSD, and are further discussed in the context of other psychophysiological measures in PTSD and of P1 potential findings in psychiatric disorders other than PTSD.

Exploring the frontier of electronic health record surveillance: the case of postoperative complications.

Background:The aim of this study was to build electronic algorithms using a combination of structured data and natural language processing (NLP) of text notes for potential safety surveillance of 9 postoperative complications. Methods:Postoperative complications from 6 medical centers in the Southeastern United States were obtained from the Veterans Affairs Surgical Quality Improvement Program (VASQIP) registry. Development and test datasets were constructed using stratification by facility and date of procedure for patients with and without complications. Algorithms were developed from VASQIP outcome definitions using NLP-coded concepts, regular expressions, and structured data. The VASQIP nurse reviewer served as the reference standard for evaluating sensitivity and specificity. The algorithms were designed in the development and evaluated in the test dataset. Results:Sensitivity and specificity in the test set were 85% and 92% for acute renal failure, 80% and 93% for sepsis, 56% and 94% for deep vein thrombosis, 80% and 97% for pulmonary embolism, 88% and 89% for acute myocardial infarction, 88% and 92% for cardiac arrest, 80% and 90% for pneumonia, 95% and 80% for urinary tract infection, and 77% and 63% for wound infection, respectively. A third of the complications occurred outside of the hospital setting. Conclusions:Computer algorithms on data extracted from the electronic health record produced respectable sensitivity and specificity across a large sample of patients seen in 6 different medical centers. This study demonstrates the utility of combining NLP with structured data for mining the information contained within the electronic health record.

eQuality: Electronic Quality Assessment From Narrative Clinical Reports

OBJECTIVE To evaluate an electronic quality (eQuality) assessment tool for dictated disability examination records. METHODS We applied automated concept-based indexing techniques to automated quality screening of Department of Veterans Affairs spine disability examinations that had previously undergone gold standard quality review by human experts using established quality indicators. We developed automated quality screening rules and refined them iteratively on a training set of disability examination reports. We applied the resulting rules to a novel test set of spine disability examination reports. The initial data set was composed of all electronically available examination reports (N=125,576) finalized by the Veterans Health Administration between July and September 2001. RESULTS Sensitivity was 91% for the training set and 87% for the test set (P-.02). Specificity was 74% for the training set and 71% for the test set (P=.44). Human performance ranged from 4% to 6% higher (P<.001) than the eQuality tool in sensitivity and 13% to 16% higher in specificity (P<.001). In addition, the eQuality tool was equivalent or higher in sensitivity for 5 of 9 individual quality indicators. CONCLUSION The results demonstrate that a properly authored computer-based expert systems approach can perform quality measurement as well as human reviewers for many quality indicators. Although automation will likely always rely on expert guidance to be accurate and meaningful, eQuality is an important new method to assist clinicians in their efforts to practice safe and effective medicine.

Serial cerebrospinal fluid tryptophan and 5-hydroxy indoleacetic acid concentrations in healthy human subjects.

The role of the serotonergic system in the pathogenesis of behavioral disorders such as depression, alcoholism, obsessive-compulsive disorder, and violence is not completely understood. Measurement of the concentration of neurotransmitters and their metabolites in cerebrospinal fluid (CSF) is considered among the most valid, albeit indirect, methods of assessing central nervous system function in man. However, most studies in humans have measured lumbar CSF concentrations only at single time points, thus not taking into account rhythmic or episodic variations in levels of neurotransmitters, precursors, or metabolites. We have continuously sampled lumbar CSF via subarachnoid catheter in 12 healthy volunteers, aged 20-65 years. One ml (every 10 min) CSF samples were collected at a rate of 0.1ml/min for 24-hour (h), and the levels of tryptophan (TRP) and 5-hydroxy indoleacetic acid (5-HIAA) were measured. Variability across all 12 subjects was significantly greater (P < 0.0001) than the variability seen in repeated analysis of a reference CSF sample for both 5-HIAA (32.0% vs 7.9%) and TRP (25.4% vs 7.0%), confirming the presence of significant biological variability during the 24-hr period examined. This variability could not be explained solely by meal related effects. Cosinor analysis of the 24-hr TRP concentrations from all subjects revealed a significant diurnal pattern in CSF TRP levels, whereas the 5-HIAA data were less consistent. These studies indicate that long-term serial CSF sampling reveals diurnal and biological variability not evident in studies based on single CSF samples.

Detection of infectious symptoms from VA emergency department and primary care clinical documentation

OBJECTIVE The majority of clinical symptoms are stored as free text in the clinical record, and this information can inform clinical decision support and automated surveillance efforts if it can be accurately processed into computer interpretable data. METHODS We developed rule-based algorithms and evaluated a natural language processing (NLP) system for infectious symptom detection using clinical narratives. Training (60) and testing (444) documents were randomly selected from VA emergency department, urgent care, and primary care records. Each document was processed with NLP and independently manually reviewed by two clinicians with adjudication by referee. Infectious symptom detection rules were developed in the training set using keywords and SNOMED-CT concepts, and subsequently evaluated using the testing set. RESULTS Overall symptom detection performance was measured with a precision of 0.91, a recall of 0.84, and an F measure of 0.87. Overall symptom detection with assertion performance was measured with a precision of 0.67, a recall of 0.62, and an F measure of 0.64. Among those instances in which the automated system matched the reference set determination for symptom, the system correctly detected 84.7% of positive assertions, 75.1% of negative assertions, and 0.7% of uncertain assertions. CONCLUSION This work demonstrates how processed text could enable detection of non-specific symptom clusters for use in automated surveillance activities.

Are posttraumatic stress disorder mental health terms found in SNOMED‐CT medical terminology

The authors sought to evaluate how well the Systematized Nomenclature of Medicine-Clinical Terms (SNOMED-CT) controlled vocabulary represents terms commonly used clinically when documenting posttraumatic stress disorder (PTSD). A list was constructed based on the PTSD criteria in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV; American Psychiatric Association, 1994), symptom assessment instruments, and publications. Although two teams mapping the terms to SNOMED-CT differed in their approach, the consensus mapping accounted for 91% of the 153 PTSD terms. They found that the words used by clinicians in describing PTSD symptoms are represented in SNOMED-CT. These results can be used to codify mental health text reports for health information technology applications such as automated chart abstraction, algorithms for identifying documentation of symptoms representing PTSD in clinical notes, and clinical decision support.

Documentation quality and time costs: A randomized controlled trial of structured entry versus dictation

The Department of Veterans Affairs (VA) performs over 800,000 disability exams and distributes over &dollor;37 billion in disability benefits per year. VA developed and deployed a computer-based disability exam documentation system in order to improve exam report quality and timeliness. We conducted a randomized controlled trial comparing joint disability examinations supported by computerized templates to the examinations documented via dictation, to determine if the system met the intended goals or had unintended consequences. Consenting veterans were randomized to undergo exams documented using computerized templates or via dictation. We compared exam report quality, documentation time costs, encounter length, total time to fulfill an exam request with a finalized exam report, and veteran satisfaction. Computer-based templates resulted in disability exam reports that had higher quality scores (p. 0.042) and were returned to the requesting office faster than exam reports created via dictation (p. 0.02). Documentation time and veteran satisfaction were similar for both the documentation techniques. Encounter length was significantly longer for the template group. Computer-based templates impacted the VA disability evaluation system by improving report quality scores and production time and lengthening encounter times. Oversight bodies have called for mandated use of computer-based templates nationwide. We believe mandates regarding use of health information technology should be guided by data regarding its positive and negative impacts.