Biomedical subjects

Karen L Olson

Publications and source records attributed to Karen L Olson.

10 recordsLinked to original sources

PubMed2006

Privacy protection versus cluster detection in spatial epidemiology.

OBJECTIVES: Patient data that includes precise locations can reveal patients' identities, whereas data aggregated into administrative regions may preserve privacy and confidentiality. We investigated the effect of varying degrees of address precision (exact latitude and longitude vs the center points of zip code or census tracts) on detection of spatial clusters of cases. METHODS: We simulated disease outbreaks by adding supplementary spatially clustered emergency department visits to authentic hospital emergency department syndromic surveillance data. We identified clusters with a spatial scan statistic and evaluated detection rate and accuracy. RESULTS: More clusters were identified, and clusters were more accurately detected, when exact locations were used. That is, these clusters contained at least half of the simulated points and involved few additional emergency department visits. These results were especially apparent when the synthetic clustered points crossed administrative boundaries and fell into multiple zip code or census tracts. CONCLUSIONS: The spatial cluster detection algorithm performed better when addresses were analyzed as exact locations than when they were analyzed as center points of zip code or census tracts, particularly when the clustered points crossed administrative boundaries. Use of precise addresses offers improved performance, but this practice must be weighed against privacy concerns in the establishment of public health data exchange policies.

Algorithms↗

PubMed2006

Lumbar puncture ordering and results in the pediatric population: a promising data source for surveillance systems.

BACKGROUND: The Centers for Disease Control and Prevention is incorporating laboratory data into real-time surveillance systems. When normal patterns of laboratory test orders and results are modeled, aberrations can be detected. Because many test orders are available electronically well before results, atypical patterns of test ordering may signal outbreaks. OBJECTIVES: The authors sought to characterize baseline patterns in the ordering and early results of lumbar punctures, motivated by the possibility of using these data for real-time surveillance for early detection of meningitis or encephalitis outbreaks. METHODS: Retrospective cohorts of pediatric emergency department patients at a single hospital (1993-2003) and from the National Hospital and Ambulatory Medical Care Survey (1992-2000) were used for analysis. RESULTS: Test ordering exhibits seasonal patterns, with monthly peaks in January and August (p < 0.0001). For the hospital cohort, the rate of cerebrospinal fluid pleocytosis exhibits seasonal patterns (p < 0.0001), with a peak from August to October. This is strongly associated with the rate and pattern of clinical neurologic disease (p < 0.0001). A long-term secular decline in daily test ordering is evident, dropping from 5.3 to 2.9 in the hospital sample, and from 371.8 to 185.3 in the national sample (p < 0.001). The long-term rate of pleocytosis has declined (p < 0.0001), though the yield of testing for pleocytosis has improved (p = 0.0104). CONCLUSIONS: Laboratory test patterns correspond with those of clinical disease and are a promising source of surveillance data. Using such data for real-time monitoring requires specific adjustments for patient age, periodicities, and secular trends.

Adolescent↗

PubMed2006

Validation of syndromic surveillance for respiratory infections.

STUDY OBJECTIVE: A key public health question is whether syndromic surveillance data provide early warning of infectious outbreaks. One cause for skepticism is that biological correlates of the administrative and clinical data used in these systems have not been rigorously assessed. This study measures the value of respiratory data currently used in syndromic surveillance systems to detect respiratory infections by comparing it against criterion standard viral testing within a pediatric population. METHODS: We conducted a longitudinal study with prospective validation in the emergency department (ED) of a tertiary care children's hospital. Children aged 7 years or younger who presented with a respiratory syndrome or who were tested for respiratory syncytial virus (RSV), influenza virus, parainfluenza virus, adenovirus, or enterovirus between January 1993 and June 2004 were included. We assessed the predictive ability of the viral tests by fitting generalized linear models to respiratory syndrome counts. RESULTS: Of 582,635 patient visits, 89,432 (15.4%) were for respiratory syndromes, and of these, 7,206 (8.1%) patients were tested for the viruses of interest. RSV was significantly related to respiratory syndrome counts (adjusted rate ratio [RR] 1.33; 95% confidence interval [CI] 1.04 to 1.71). In multivariate models including all viruses tested, influenza virus was also a significant predictor of respiratory syndrome counts (RR 1.47; 95% CI 1.03 to 2.10). This model accounted for 81.6% of the observed variability in respiratory syndrome counts. CONCLUSION: Respiratory syndromic surveillance data strongly correlate with virologic test results in a pediatric population, providing evidence of the biologic validity of such surveillance systems. Real-time outbreak detection systems relying on syndromic data may be an important adjunct to the current set of public health systems for the detection and surveillance of respiratory infections.

Boston↗

PubMed2006

Making up is hard to do, especially for mothers with high levels of depressive symptoms and their infant sons.

BACKGROUND: The goal of this study was to evaluate the interactions of mothers with normative or high levels of depressive symptomatology on the Center for Epidemiologic Studies-Depression Scale (CES-D) and their 3-month-old infants. Although successful mutual regulation of affect is critical to children's socio-emotional development, little is known about the factors that influence dyadic processes such as synchrony, matching, mismatching, and bi-directionality during early infancy. Therefore, this study evaluated the effects of maternal depressive symptom status, infant gender, and interactional context on mother-infant affective expressiveness and the dyadic features of their interactions. METHODS: Participants were 133 mothers and their healthy full-term infants. Mothers were classified into three groups on the basis of their total score on the CES-D at 2 months of infant age: a high symptom group (CES-D score > or = 16), a mid symptom control group (CES-D score = 2-12), and a low symptom group (CES-D score = 0-1). Mothers and infants were then videotaped in the Face-to-Face Still-Face paradigm at 3 months of infant age. The mothers' and infants' affect during the interactions prior to (first play) and following the still-face (reunion play) were coded microanalytically using Izard's AFFEX system. RESULTS: Results indicated that male as compared to female infants were more vulnerable to high levels of maternal depressive symptoms and that high symptom mothers and their sons had more difficult interactions in the challenging reunion episode. CONCLUSIONS: The findings suggest that a cycle of mutual regulatory problems may become established between high symptom mothers and their sons, particularly in challenging social contexts. The long-term consequences of this early social interactive vulnerability in terms of later development need to be further investigated.

Adult↗

PubMed2005

A software tool for creating simulated outbreaks to benchmark surveillance systems.

BACKGROUND: Evaluating surveillance systems for the early detection of bioterrorism is particularly challenging when systems are designed to detect events for which there are few or no historical examples. One approach to benchmarking outbreak detection performance is to create semi-synthetic datasets containing authentic baseline patient data (noise) and injected artificial patient clusters, as signal. METHODS: We describe a software tool, the AEGIS Cluster Creation Tool (AEGIS-CCT), that enables users to create simulated clusters with controlled feature sets, varying the desired cluster radius, density, distance, relative location from a reference point, and temporal epidemiological growth pattern. AEGIS-CCT does not require the use of an external geographical information system program for cluster creation. The cluster creation tool is an open source program, implemented in Java and is freely available under the Lesser GNU Public License at its Sourceforge website. Cluster data are written to files or can be appended to existing files so that the resulting file will include both existing baseline and artificially added cases. Multiple cluster file creation is an automated process in which multiple cluster files are created by varying a single parameter within a user-specified range. To evaluate the output of this software tool, sets of test clusters were created and graphically rendered. RESULTS: Based on user-specified parameters describing the location, properties, and temporal pattern of simulated clusters, AEGIS-CCT created clusters accurately and uniformly. CONCLUSION: AEGIS-CCT enables the ready creation of datasets for benchmarking outbreak detection systems. It may be useful for automating the testing and validation of spatial and temporal cluster detection algorithms.

Algorithms↗

PubMed2005

Real time spatial cluster detection using interpoint distances among precise patient locations.

BACKGROUND: Public health departments in the United States are beginning to gain timely access to health data, often as soon as one day after a visit to a health care facility. Consequently, new approaches to outbreak surveillance are being developed. When cases cluster geographically, an analysis of their spatial distribution can facilitate outbreak detection. Our method focuses on detecting perturbations in the distribution of pair-wise distances among all patients in a geographical region. Barring outbreaks, this distribution can be quite stable over time. We sought to exemplify the method by measuring its cluster detection performance, and to determine factors affecting sensitivity to spatial clustering among patients presenting to hospital emergency departments with respiratory syndromes. METHODS: The approach was to (1) define a baseline spatial distribution of home addresses for a population of patients visiting an emergency department with respiratory syndromes using historical data; (2) develop a controlled feature set simulation by inserting simulated outbreak data with varied parameters into authentic background noise, thereby creating semisynthetic data; (3) compare the observed with the expected spatial distribution; (4) establish the relative value of different alarm strategies so as to maximize sensitivity for the detection of clustering; and (5) measure factors which have an impact on sensitivity. RESULTS: Overall sensitivity to detect spatial clustering was 62%. This contrasts with an overall alarm rate of less than 5% for the same number of extra visits when the extra visits were not characterized by geographic clustering. Clusters that produced the least number of alarms were those that were small in size (10 extra visits in a week, where visits per week ranged from 120 to 472), diffusely distributed over an area with a 3 km radius, and located close to the hospital (5 km) in a region most densely populated with patients to this hospital. Near perfect alarm rates were found for clusters that varied on the opposite extremes of these parameters (40 extra visits, within a 250 meter radius, 50 km from the hospital). CONCLUSION: Measuring perturbations in the interpoint distance distribution is a sensitive method for detecting spatial clustering. When cases are clustered geographically, there is clearly power to detect clustering when the spatial distribution is represented by the M statistic, even when clusters are small in size. By varying independent parameters of simulated outbreaks, we have demonstrated empirically the limits of detection of different types of outbreaks.

Ambulatory Care↗

PubMed2004

Similar and functionally typical kinematic reaching parameters in 7- and 15-month-old in utero cocaine-exposed and unexposed infants.

This study examined the effects of intrauterine cocaine exposure on the reaches of 19 exposed and 15 unexposed infants at 7 and 15 months using kinematic measures. Infants sat at a table and reached for a rattle, a toy doll, and a chair. Videotaped reaches were digitized using the Peak Performance system. Kinematic movement variables were extracted (e.g., reach duration, peak velocity, movement units, path length) and ratios computed (e.g., path length divided by number of movement units). Regardless of exposure status, reaches of older infants were faster, more direct, had fewer movement units, and covered more distance with the first movement unit. Exposed infants covered more distance per movement unit than unexposed infants, but there were no other significant differences. Reaches of exposed and unexposed infants were essentially similar. Importantly, reach parameters for these high-risk infants were similar to reach parameters for infants at lower social and biological risk.

Adult↗

PubMed2004

Use of emergency department chief complaint and diagnostic codes for identifying respiratory illness in a pediatric population.

OBJECTIVES: (1) To determine the value of emergency department chief complaint (CC) and International Classification of Disease diagnostic codes for identifying respiratory illness in a pediatric population and (2) to modify standard respiratory CC and diagnostic code sets to better identify respiratory illness in children. METHODS: We determined the sensitivity and specificity of CC and diagnostic codes by comparing code groups with a criterion standard. CC and diagnostic codes for 500 pediatric emergency department patients were retrospectively classified as respiratory or nonrespiratory. Respiratory diagnostic codes were further classified as upper or lower respiratory. The criterion standard was a blinded, reviewer-assigned illness category based on history, physical examination, test results, and treatment. We also modified our respiratory code sets to better identify respiratory illness in this population. RESULTS: Four hundred ninety-six charts met inclusion criteria. By the criterion standard, 87 (18%) patients had upper and 47 (10%) had lower respiratory illness. The specificity of CC and diagnostic codes groups was >0.97 [95% confidence interval (CI) 0.95-0.98]. The code group sensitivities were as follows: CC was 0.47 (95% CI 0.38-0.55), upper respiratory diagnostic was 0.56 (95% CI 0.45-0.67), lower respiratory diagnostic was 0.87 (95% CI 0.74-0.95), and combined CC and/or diagnostic was 0.72 (95% CI 0.63-0.79). Modifying the respiratory code sets to better identify respiratory illness increased sensitivity but decreased specificity. CONCLUSIONS: Diagnostic and CC codes have substantial value for emergency department syndromic surveillance. Adapting our respiratory code sets to a pediatric population forced a tradeoff between sensitivity and specificity.

Child↗

PubMed2003

Prevalence, stability, and socio-demographic correlates of depressive symptoms in Black mothers during the first 18 months postpartum.

OBJECTIVES: The goals of this longitudinal study were to evaluate 1) the prevalence and stability of high depressive symptom levels during the first 18 months postpartum in a sample of otherwise healthy Black mothers varying in socio-economic status and 2) the relation of sociodemographic variables and level of socio-demographic risk to maternal depressive symptom levels during this time period. METHODS: Participants were 163 Black adult mothers of healthy, full-term infants. The level of mothers' depressive symptomatology was assessed at 2, 3, 6, 12, and 18 months postpartum using the Center for Epidemiological Studies-Depression Scale (CES-D). Mothers provided socio-demographic information at each assessment. Univariate and bivariate analyses were used to analyze the data. RESULTS: The percentage of mothers with an elevated CES-D score (16 or higher) at single visits ranged from 13.5 to 14.7%, and 35.0% had at least one elevated CES-D score by 18 months postpartum. CES-D total scores were significantly correlated across each pair of visits (mean r = 0.57, all p's < 0.0001), and average CES-D scores did not change significantly over time. Single marital status, low-income status, and more negative maternal perceptions of the adequacy of income for meeting familial needs were significantly related to higher maternal CES-D scores at each assessment (all p's < 0.05). Level of socio-demographic risk, as assessed with a composite risk score derived from these variables, was significantly related to higher average CES-D scores (averaged across visits) (p < 0.0001) and to a greater frequency of elevated CES-D scores (16 or higher) during the first 18 months postpartum (p = 0.0002). CONCLUSIONS: The prevalence and stability of high levels of maternal depressive symptomatology during the first 18 months postpartum in this sample of Black women are consistent with those reported in prior studies of community samples of mothers unselected for race. Mothers with higher socio-demographic risk profiles had higher levels of maternal depressive symptoms at each assessment point.

Adolescent↗

PubMed2002

Stability and change in level of maternal depressive symptomatology during the first postpartum year.

BACKGROUND: This study evaluated stability and change in the level of maternal depressive symptomatology over the course of the first postpartum year in a community cohort of 106 first-time mothers of full-term, healthy infants. Effects of diagnosed depression and infant gender were also assessed. METHODS: At 2 months postpartum (intake), mothers were classified into one of two symptom groups on the basis of their total score on the Center for Epidemiological Studies-Depression Scale (CES-D): high (CES-D score > or = 16, 46%) or normative (CES-D score = 2-12, 54%). Mothers completed the CES-D again at 3, 6, and 12 months postpartum. At 12 months, maternal diagnostic status for major depression and related disorders was evaluated using the Diagnostic Interview Schedule-III-Revised. RESULTS: Mothers in the High symptom group at intake continued to have significantly higher CES-D scores at 3, 6, and 12 months than mothers in the Normative symptom group at intake, and a third in the High symptom group at intake had a subsequent CES-D score above the clinical cutoff (> or = 16). Maternal CES-D scores were significantly correlated across visits. In regressions controlling for diagnostic status and infant gender, mothers' CES-D score at the most recent prior assessment contributed significant unique variance to mothers' CES-D score at each subsequent assessment. CES-D scores were higher at 3 months if mothers had diagnosed depression and were parenting a son, and higher at 12 months if mothers had both diagnosed depression and a prior, high CES-D score. LIMITATIONS: Findings may not generalize to multipara or high-risk cohorts. CONCLUSIONS: First-time mothers with high levels of depressive symptomatology at 2 months postpartum (especially those with diagnosed depression) are at increased risk of continuing to experience high levels of depressive symptomatology throughout the first postpartum year. Implications for preventative intervention services are discussed.

Adult↗