PURPOSE: Physicians require information on the comparative benefits and harms of medications for optimal treatment decisions. However, this type of data is limited, especially for pediatric patients. OBJECTIVE: Our aim was to use observational data to measure and compare medication utilization patterns in a pediatric patient population. METHODS: Using pharmacy claims data from a large, national-scale insurance program in the USA, we identified all patients with a diagnosis of epilepsy treated with a first-generation antiepileptic drug (carbamazepine, ethosuximide, phenobarbital, phenytoin, or valproate) or a second-generation antiepileptic drug [carbamazepine extended release (XR), gabapentin, lamotrigine, levetiracetam, oxcarbazepine, tiagabine, topiramate, valproate XR, or zonisamide]. Treatment periods were defined on the basis of prescription fill dates and medication days supplied. Medication use was measured for individual antiepileptic drugs and for first-generation and second-generation drugs as groups. RESULTS: There were 2527 patients (54 %) who initiated therapy with first-generation antiepileptics and 2139 patients (46 %) who initiated therapy with second-generation antiepileptics. First- and second-generation drugs had the same 1-year retention rates [26 % (95 % confidence interval (CI) 24-28) and 26 % (95 % CI 25-28), respectively], and 26 % of patients (95 % CI 25-28) and 29 % of patients (95 % CI 27-31) who started on a first- or second-generation antiepileptic medication, respectively, resumed treatment with the initial drug after discontinuation. Overall, 73 % of patients (95 % CI 71-74) were treated with only one antiepileptic drug, with similar rates for patients started on first- and second-generation drugs [71 % (95 % CI 69-73) versus 74 % (95 % CI 72-76)]. CONCLUSION: Comparing drug utilization patterns in a pediatric population using observational data, we found similar rates of retention and therapeutic changes. These findings are consistent with the available comparative data and demonstrate an approach that could be extended to other drug classes and conditions in pediatric populations to examine drug effectiveness.

BACKGROUND: The allocation of research resources should favor conditions responsible for the greatest disease burden. This is particularly important in pediatric populations, which have been underrepresented in clinical research. Our aim was to measure the association between the focus of pediatric clinical trials and burden of disease and to identify neglected clinical domains. METHODS: We performed a cross-sectional study of clinical trials by using trial records in ClinicalTrials.gov. All trials started in 2006 or after and studying patient-level interventions in pediatric populations were included. Age-specific measures of disease burden were obtained for 21 separate conditions for high-, middle-, and low-income countries. We measured the correlation between number of pediatric clinical trials and disease burden for each condition. RESULTS: Neuropsychiatric conditions and infectious diseases were the most studied conditions globally in terms of number of trials (874 and 847 trials, respectively), while intentional injuries (5 trials) and maternal conditions (4 trials) were the least studied. Clinical trials were only moderately correlated with global disease burden (r = 0.58, P = .006). Correlations were also moderate within each of the country income levels, but lowest in low-income countries (r = .47, P = .03). Globally, the conditions most understudied relative to disease burden were injuries (-260 trials for unintentional injuries and -160 trials for intentional injuries), nutritional deficiencies (-175 trials), and respiratory infections (-171 trials). CONCLUSIONS: Pediatric clinical trial activity is only moderately associated with pediatric burden of disease, and least associated in low-income countries. The mismatch between clinical trials and disease burden identifies key clinical areas for focus and investment.

BACKGROUND: There is a natural assumption that quality and efficiency are optimized when providers consistently work together and share patients. Diversity in composition and recurrence of groups that provide face-to-face care to the same patients has not previously been studied. OBJECTIVE: Claims data enable identification of the constellation of providers caring for a single patient. To indirectly measure teamwork and provider collaboration, we measure recurrence of provider constellations and cohesion among providers. DESIGN: Retrospective analysis of commercial healthcare claims from a single insurer. PARTICIPANTS: Patients with claims for office visits and their outpatient providers. To maximize capture of provider panels, the cohort was drawn from the four regions with the highest plan coverage. Regional outpatient provider networks were constructed with providers as nodes and number of shared patients as links. MAIN MEASURES: Measures of cohesion and stability of provider constellations derived from the networks of providers to quantify patient sharing. RESULTS: For 10,325 providers and their 521,145 patients, there were 2,641,933 collaborative provider pairs sharing at least one patient. Fifty-four percent only shared a single patient, and 19 % shared two. Of 15,449,835 unique collaborative triads, 92 % shared one patient, 5 % shared two, and 0.2 % shared ten or more. Patient constellations had a median of four providers. Any precise constellation recurred rarely-89 % with exactly two providers shared just one patient and only 4 % shared over two; 97 % of constellations with exactly three providers shared just one patient. Four percent of constellations with 2+ providers were not at all cohesive, sharing only the hub patient. In the remaining constellations, a median of 93 % of provider pairs shared at least one additional patient beyond the hub patient. CONCLUSION: Stunning variability in the constellations of providers caring for patients may challenge underlying assumptions about the current state of teamwork in healthcare.

This study aimed to comprehensively describe prevalence and temporal dispensing patterns for medications prescribed to children and adolescents in the United States. Participants were 1.6 million children (49% female) under 18 years old enrolled in a nation-wide, employer-provided insurance plan. All medication claims from 1999-2006 were reviewed retrospectively. Drugs were assigned to 16 broad therapeutic categories. Effects of trend over time, seasonality, age and gender on overall and within category prevalence were examined. RESULTS: Mean monthly prevalence for dispensed medications was 23.5% (range 19.4-27.5), with highest rates in winter and lowest in July. The age group with the highest prevalence was one-year-old children. On average each month, 17.1% of all children were dispensed a single drug and 6.4% were dispensed two or more. Over time, prevalence for two or more drugs did not change, but the proportion of children dispensed a single drug decreased (slope -.02%, p= .001). Overall, boys had higher monthly rates than girls (average difference 0.9%, p= .002). However, differences by gender were greatest during middle childhood, especially for respiratory and central nervous system agents. Contraceptives accounted for a large proportion of dispensed medication to older teenage girls. Rates for the drugs with the highest prevalence in this study were moderately correlated (average Pearson r.66) with those from a previously published national survey. CONCLUSION: On average, nearly one quarter of a population of insured children in the United States was dispensed medication each month. This rate decreased somewhat over time, primarily because proportionally fewer children were dispensed a single medication. The rate for two or more drugs dispensed simultaneously remained steady.

BACKGROUND AND OBJECTIVE: Optimal treatment decisions in children require sufficient evidence on the safety and efficacy of pharmaceuticals in pediatric patients. However, there is concern that not enough trials are conducted in children and that pediatric trials differ from those performed in adults. Our objective was to measure the prevalence of pediatric studies among clinical drug trials and compare trial characteristics and quality indicators between pediatric and adult drug trials. METHODS: For conditions representing a high burden of pediatric disease, we identified all drug trials registered in ClinicalTrials.gov with start dates between 2006 and 2011 and tracked the resulting publications. We measured the proportion of pediatric trials and subjects for each condition and compared pediatric and adult trial characteristics and quality indicators. RESULTS: For the conditions selected, 59.9% of the disease burden was attributable to children, but only 12.0% (292/2440) of trials were pediatric (P .001). Among pediatric trials, 58.6% were conducted without industry funding compared with 35.0% of adult trials (P .001). Fewer pediatric compared with adult randomized trials examined safety outcomes (10.1% vs 16.9%, P = .008). Pediatric randomized trials were slightly more likely to be appropriately registered before study start (46.9% vs 39.3%, P = .04) and had a modestly higher probability of publication in the examined time frame (32.8% vs 23.2%, P = .04). CONCLUSIONS: There is substantial discrepancy between pediatric burden of disease and the amount of clinical trial research devoted to pediatric populations. This may be related in part to trial funding, with pediatric trials relying primarily on government and nonprofit organizations.

OBJECTIVE: To generate neurobehavioral norms for an unselected random sample of clinically healthy newborns by examining the newborns with use of the Neonatal Intensive Care Unit Network Neurobehavioral Scale (NNNS). STUDY DESIGN: We recruited 344 healthy mothers and newborns from a well-child nursery. The NNNS, a 128-item assessment of infant neurobehavior, was used to examine newborn performance. Associations between 11 NNNS summary scales and the stress/abstinence scale, as well as medical and demographic variables, were evaluated. Mean, SD, and 5th and 95th percentile values for the summary scores of the NNNS are presented. RESULTS: NNNS scores from the 10th to the 90th percentile represent a range of normative performance. Performance on different neurobehavioral domains was related to marital status, ethnicity, prenatal, intrapartum and neonatal risk factors, complications during labor/delivery, cesarean delivery, gestational age, the age of the newborn at testing, and infant sex. CONCLUSION: These data provide clinicians and researchers with normative data for evaluation of newborn neurobehavior. Even in a low-risk sample, medical and demographic factors below clinical cut-offs were related to newborn performance. Infants with scores outside the ranges for the 11 NNNS summary scores and the stress/abstinence scale may need further observation and, if necessary, early intervention.

BACKGROUND: Recent withdrawals of major drugs have highlighted the critical importance of drug safety surveillance in the postmarketing phase. Limitations of spontaneous report data have led drug safety professionals to pursue alternative postmarketing surveillance approaches based on healthcare administrative claims data. These data are typically analysed by comparing the adverse event rates associated with a drug of interest to those of a single comparable reference drug. OBJECTIVE: The aim of this study was to determine whether adverse event detection can be improved by incorporating information from multiple reference drugs. We developed a pharmacological network model that implemented this approach and evaluated its performance. METHODS: We studied whether adverse event detection can be improved by incorporating information from multiple reference drugs, and describe two approaches for doing so. The first, reported previously, combines a set of related drugs into a single reference cohort. The second is a novel pharmacoepidemiological network model, which integrates multiple pair-wise comparisons across an entire set of related drugs into a unified consensus safety score for each drug. We also implemented a single reference drug approach for comparison with both multi-drug approaches. All approaches were applied within a sequential analysis framework, incorporating new information as it became available and addressing the issue of multiple testing over time. We evaluated all these approaches using statin (HMG-CoA reductase inhibitors) safety data from a large healthcare insurer in the US covering April 2000 through March 2005. RESULTS: We found that both multiple reference drug approaches offer earlier detection (6-13 months) than the single reference drug approach, without triggering additional false positives. CONCLUSIONS: Such combined approaches have the potential to be used with existing healthcare databases to improve the surveillance of therapeutics in the postmarketing phase over single-comparator methods. The proposed network approach also provides an integrated visualization framework enabling decision makers to understand the key high-level safety relationships amongst a group of related drugs.

OBJECTIVE: To develop a novel diagnostic algorithm for Lyme disease among children with facial palsy by integrating public health surveillance data with traditional clinical predictors. DESIGN: Retrospective cohort study. SETTING: Children's Hospital Boston emergency department, 1995-2007. PATIENTS: Two hundred sixty-four children (aged 20 years) with peripheral facial palsy who were evaluated for Lyme disease. MAIN OUTCOME MEASURES: Multivariate regression was used to identify independent clinical and epidemiologic predictors of Lyme disease facial palsy. RESULTS: Lyme diagnosis was positive in 65% of children from high-risk counties in Massachusetts during Lyme disease season compared with 5% of those without both geographic and seasonal risk factors. Among patients with both seasonal and geographic risk factors, 80% with 1 clinical risk factor (fever or headache) and 100% with 2 clinical factors had Lyme disease. Factors independently associated with Lyme disease facial palsy were development from June to November (odds ratio, 25.4; 95% confidence interval, 8.3-113.4), residence in a county where the most recent 3-year average Lyme disease incidence exceeded 4 cases per 100,000 (18.4; 6.5-68.5), fever (3.9; 1.5-11.0), and headache (2.7; 1.3-5.8). Clinical experts correctly treated 68 of 94 patients (72%) with Lyme disease facial palsy, but a tool incorporating geographic and seasonal risk identified all 94 cases. CONCLUSIONS: Most physicians intuitively integrate geographic information into Lyme disease management, but we demonstrate quantitatively how formal use of geographically based incidence in a clinical algorithm improves diagnostic accuracy. These findings demonstrate potential for improved outcomes from investments in health information technology that foster bidirectional communication between public health and clinical settings.

BACKGROUND: Fragmentation of medical information places patients at risk for medical errors, adverse events, duplication of tests, and increased costs. We sought to quantify, at the population level, the burden of fragmentation in the acute care setting across the state of Massachusetts by measuring the rates at which individuals seek care across multiple sites. METHODS: A retrospective observational study of all adult patients with at least 2 visits or hospitalizations to the emergency departments, inpatient units, and observation units in Massachusetts from October 1, 2002, to September 30, 2007. RESULTS: The 3,692,178 adult patients who visited an acute care site during our study period accounted for 12,758,498 acute care visits. A total of 1,130,124 adult patients (31%) visited 2 or more hospitals during the study period, accounting for 56.5% of all acute care visits, while a subgroup of 43,794 patients (1%) visited 5 or more hospitals, contributing to almost one-tenth of all acute visits. Patients who visited multiple sites were younger (P .001), more likely to be male (P .001), more likely to have a primary psychiatric diagnosis (P .001), and more frequently hospitalized (P .001) and incurred higher charges than patients who used only a single site of care (P .001). CONCLUSIONS: A large number of patients seek care at multiple acute care sites. These findings provide one basis for assessing the value of an integrated electronic health information system for clinicians caring for patients across sites of care and therefore the return on investment in health information technology.

OBJECTIVE: Standardized surveillance syndromes do not exist but would facilitate sharing data among surveillance systems and comparing the accuracy of existing systems. The objective of this study was to create reference syndrome definitions from a consensus of investigators who currently have or are building syndromic surveillance systems. DESIGN: Clinical condition-syndrome pairs were catalogued for 10 surveillance systems across the United States and the representatives of these systems were brought together for a workshop to discuss consensus syndrome definitions. RESULTS: Consensus syndrome definitions were generated for the four syndromes monitored by the majority of the 10 participating surveillance systems: Respiratory, gastrointestinal, constitutional, and influenza-like illness (ILI). An important element in coming to consensus quickly was the development of a sensitive and specific definition for respiratory and gastrointestinal syndromes. After the workshop, the definitions were refined and supplemented with keywords and regular expressions, the keywords were mapped to standard vocabularies, and a web ontology language (OWL) ontology was created. LIMITATIONS: The consensus definitions have not yet been validated through implementation. CONCLUSION: The consensus definitions provide an explicit description of the current state-of-the-art syndromes used in automated surveillance, which can subsequently be systematically evaluated against real data to improve the definitions. The method for creating consensus definitions could be applied to other domains that have diverse existing definitions.