Alon Geva

Network Analysis of Team Structure in the Neonatal Intensive Care Unit

OBJECTIVE: The goal was to examine nursing team structure and its relationship with family satisfaction. METHODS: We used electronic health records to create patient-based, 1-mode networks of nursing handoffs. In these networks, nurses were represented as nodes and handoffs as edges. For each patient, we calculated network statistics including team size and diameter, network centrality index, proportion of newcomers to care teams according to day of hospitalization, and a novel measure of the average number of shifts between repeat caregivers, which was meant to quantify nursing continuity. We assessed parental satisfaction by using a standardized survey. RESULTS: Team size increased with increasing length of stay. At 2 weeks of age, 50% of shifts were staffed by a newcomer nurse who had not previously cared for the index patient. The patterns of newcomers to teams did not differ according to birth weight. When the population was dichotomized according to median mean repeat caregiver interval value, increased reports of problems with nursing care were seen with less-consistent staffing by familiar nurses. This relationship persisted after controlling for factors including birth weight, length of stay, and team size. CONCLUSIONS: Family perceptions of nursing care quality are more strongly associated with team structure and the sequence of nursing participation than with team size. Objective measures of health care team structure and function can be examined by applying network analytic techniques to information contained in electronic health records.

Spread of Methicillin-Resistant Staphylococcus aureus in a Large Tertiary NICU: Network Analysis

OBJECTIVE: Methicillin-resistant Staphylococcus aureus (MRSA) colonization in NICUs increases the risk of nosocomial infection. Network analysis provides tools to examine the interactions among patients and staff members that put patients at risk of colonization. METHODS: Data from MRSA surveillance cultures were combined with patient room locations, nursing assignments, and sibship information to create patient- and unit-based networks. Multivariate models were constructed to quantify the risk of incident MRSA colonization as a function of exposure to MRSA-colonized infants in these networks. RESULTS: A MRSA-negative infant in the NICU simultaneously with a MRSA-positive infant had higher odds of becoming colonized when the colonized infant was a sibling, compared with an unrelated patient (odds ratio: 8.8 [95% confidence interval [CI]: 5.3–14.8]). Although knowing that a patient was MRSA-positive and was placed on contact precautions reduced the overall odds of another patient becoming colonized by 35% (95% CI: 20%–47%), having a nurse in common with that patient still increased the odds of colonization by 43% (95% CI: 14%–80%). Normalized group degree centrality, a unitwide network measure of connectedness between colonized and uncolonized patients, was a significant predictor of incident MRSA cases (odds ratio: 18.1 [95% CI: 3.6–90.0]). CONCLUSIONS: Despite current infection-control strategies, patients remain at significant risk of MRSA colonization from MRSA-positive siblings and from other patients with whom they share nursing care. Strategies that minimize the frequency of staff members caring for both colonized and uncolonized infants may be beneficial in reducing the spread of MRSA colonization.

Dexamethasone and Tonsillectomy Bleeding A Meta-Analysis

Objective. To use meta-analytic techniques to examine the effect of dexamethasone on the risk of postoperative bleeding following tonsillectomy. Data Sources. PubMed and Embase databases accessed on April 23, 2009, and April 28, 2009. Review Methods. Using principles of meta-analysis, inclusion and exclusion criteria were developed to identify all randomized controlled trials of patients undergoing tonsillectomy in which perioperative intravenous dexamethasone was administered in at least 1 treatment arm and bleeding complications were reported. Electronic databases were searched to identify candidate articles. Two authors independently abstracted data from each article. Discrepancies were resolved by consensus. A fixed-effects model was used to pool relative risks among studies using the Mantel-Haenszel method. Studies were assessed for publication bias using a funnel plot of studies’ effect size vs standard error of the effect size as well as Begg test and Egger test. A P value <.05 was considered significant. Results. The primary search identified 85 potential studies. Fourteen met inclusion criteria and were selected for meta-analysis. No significant heterogeneity was found among studies (I2< 0.1%; 95% confidence interval [CI], 0%-55%; P = .68). The pooled relative risk (RR) of postoperative bleeding did not differ significantly between patients receiving dexamethasone and controls (RR, 1.02; 95% CI, 0.65-1.61; P = .92). When studies were stratified by age, primary vs secondary hemorrhage, and follow-up duration, no further significant differences in bleeding rate were identified. No evidence of publication bias was found using Begg (P = .70) or Egger (P = .73) tests. Conclusion. The results of this meta-analysis indicate that perioperative dexamethasone does not confer an increased risk of postoperative bleeding in patients undergoing tonsillectomy.

CoolSim: Using Industrial Modeling Techniques to Examine the Impact of Selective Head Cooling in a Model of Perinatal Regionalization

OBJECTIVE. A selective head-cooling device for the treatment of moderate to severe hypoxic-ischemic encephalopathy has been approved by the Food and Drug Administration for use in the United States. To reflect the complexity of health care delivery at the systems level, we used the industrial modeling technique of discrete event simulation to analyze the impact of various deployment strategies for selective head cooling and its partner technology, amplitude-integrated electroencephalography. METHODS. We modeled the course through the perinatal system of all births in Massachusetts over a 1-year period. Cohort and care characteristics were drawn from existing databases. Results of a recently published trial were used to estimate the effects of selective head cooling. One thousand cohort replications were conducted to assess uncertainty. Several policy alternatives were examined, including no use of selective head cooling and scenarios that altered the number and placement of selective head-cooling and amplitude-integrated electroencephalography units throughout the state. Patient-level outcome and cost data were assessed. RESULTS. For all scenarios tested, the use of amplitude-integrated electroencephalography/selective head cooling resulted in better outcomes at lower cost. However, substantial differences in transfer rates, failure-to-cool rates, and total costs were seen across scenarios. Optimal decision-making regarding the number and placement of devices led to a 16% improvement in cost savings and a 10-fold decrease in failure-to-cool rates, compared with other deployment scenarios. These results were insensitive to significant changes in model inputs. CONCLUSIONS. On the basis of currently available data, the package of amplitude-integrated electroencephalography and selective head cooling seems to be an economically desirable intervention. Quantifiable techniques to assess system-wide technology performance provide a powerful approach to informing decisions regarding the structure and function of health care systems.

Long-term outcomes and risk factors for aortic regurgitation after discrete subvalvular aortic stenosis resection in children

Objectives To characterise long-term outcomes after discrete subaortic stenosis (DSS) resection and to identify risk factors for reoperation and aortic regurgitation (AR) requiring repair or replacement. Methods All patients who underwent DSS resection between 1984 and 2009 at our institution with at least 36 months’ follow-up were included. Demographic, surgical and echocardiographic data were reviewed. Outcomes were reoperation for recurrent DSS, surgery for AR, death and morbidities, including heart transplant, endocarditis and complete heart block. Results Median length of postoperative follow-up was 10.9 years (3–27.2 years). Reoperation occurred in 32 patients (21%) and plateaued 10 years after initial resection. Survival at 10 years and 20 years was 98.6% and 86.3%, respectively. Aortic valve (AoV) repair or replacement for predominant AR occurred in 31 patients (20%) during or after DSS resection. By multivariable analysis, prior aortic stenosis (AS) intervention (HR 22.4, p<0.001) was strongly associated with AoV repair or replacement. Risk factors for reoperation by multivariable analysis included younger age at resection (HR 1.24, p=0.003), preoperative gradient ≥60 mm Hg (HR 2.23, p=0.04), peeling of membrane off AoV or mitral valve (HR 2.52, p=0.01), distance of membrane to AoV <7.0 mm (HR 4.03, p=0.03) and AS (HR 2.58, p=0.01). Conclusions In this cohort, the incidence of reoperations after initial DSS resection plateaued after 10 years. Despite a significant rate of reoperation, overall survival was good. Concomitant congenital AS and its associated interventions significantly increased the risk of AR requiring surgical intervention.

Chronic disseminated intravascular coagulation and childhood-onset skin necrosis resulting from homozygosity for a protein C Gla domain mutation, Arg15Trp.

A toddler of Haitian descent presented with an 18-month history of chronic consumption coagulopathy, followed by catastrophic skin necrosis. Protein C deficiency (1% to 3% of control) was noted by functional assay; chromogenic assay and antigen levels were 30% of control. Plasma infusion abrogated the disseminated intravascular coagulation-like state. The authors identified a homozygous mutation, C1432T, resulting in a missense, Arg15Trp, in the gamma-carboxyglutamate domain of the protein. Chronic consumption coagulopathy without purpura fulminans or venous thrombosis is a rare presentation of defective protein C pathway. The result of this mutation is a mixed type I (low antigen) and type II (low function) phenotype.

A Quantitative Analysis of Optimal Treatment Capacity for Perinatal Asphyxia

Objective. In centers electing to offer therapeutic hypothermia for treating hypoxic-ischemic encephalopathy (HIE), determining the optimal number of cooling devices is not straightforward. The authors used computer-based modeling to determine the level of service as a function of local HIE caseload and number of cooling devices available. Methods. The authors used discrete event simulation to create a model that varied the number of HIE cases and number of cooling devices available. Outcomes of interest were percentage of HIE-affected infants not cooled, number of infants not cooled, and percentage of time that all cooling devices were in use. Results. With 1 cooling device, even the smallest perinatal center did not achieve a cooling rate of 99% of eligible infants. In contrast, 2 devices ensured 99% service in centers treating as many as 20 infants annually. In centers averaging no more than 1 HIE infant monthly, the addition of a third cooling device did not result in a substantial reduction in the number of infants who would not be cooled. Conclusion. Centers electing to offer therapeutic hypothermia with only a single cooling device are at significant risk of being unable to provide treatment to eligible infants, whereas 2 devices appear to suffice for most institutions treating as many as 20 annual HIE cases. Three devices would rarely be needed given current caseloads seen at individual institutions. The quantitative nature of this analysis allows decision makers to determine the number of devices necessary to ensure adequate availability of therapeutic hypothermia given the HIE caseload of a particular institution.

Learning a Comorbidity-Driven Taxonomy of Pediatric Pulmonary Hypertension

Rationale: Pediatric pulmonary hypertension (PH) is a heterogeneous condition with varying natural history and therapeutic response. Precise classification of PH subtypes is, therefore, crucial for individualizing care. However, gaps remain in our understanding of the spectrum of PH in children. Objective: We seek to study the manifestations of PH in children and to assess the feasibility of applying a network-based approach to discern disease subtypes from comorbidity data recorded in longitudinal data sets. Methods and Results: A retrospective cohort study comprising 6 943 263 children (<18 years of age) enrolled in a commercial health insurance plan in the United States, between January 2010 and May 2013. A total of 1583 (0.02%) children met the criteria for PH. We identified comorbidities significantly associated with PH compared with the general population of children without PH. A Bayesian comorbidity network was constructed to model the interdependencies of these comorbidities, and network-clustering analysis was applied to derive disease subtypes comprising subgraphs of highly connected comorbid conditions. A total of 186 comorbidities were found to be significantly associated with PH. Network analysis of comorbidity patterns captured most of the major PH subtypes with known pathological basis defined by the World Health Organization and Panama classifications. The analysis further identified many subtypes documented in only a few case studies, including rare subtypes associated with several well-described genetic syndromes. Conclusions: Application of network science to model comorbidity patterns recorded in longitudinal data sets can facilitate the discovery of disease subtypes. Our analysis relearned established subtypes, thus validating the approach, and identified rare subtypes that are difficult to discern through clinical observations, providing impetus for deeper investigation of the disease subtypes that will enrich current disease classifications.

A Computable Phenotype Improves Cohort Ascertainment in a Pediatric Pulmonary Hypertension Registry

Objectives To compare registry and electronic health record (EHR) data mining approaches for cohort ascertainment in patients with pediatric pulmonary hypertension (PH) in an effort to overcome some of the limitations of registry enrollment alone in identifying patients with particular disease phenotypes. Study design This study was a single‐center retrospective analysis of EHR and registry data at Boston Childrens Hospital. The local Informatics for Integrating Biology and the Bedside (i2b2) data warehouse was queried for billing codes, prescriptions, and narrative data related to pediatric PH. Computable phenotype algorithms were developed by fitting penalized logistic regression models to a physician‐annotated training set. Algorithms were applied to a candidate patient cohort, and performance was evaluated using a separate set of 136 records and 179 registry patients. We compared clinical and demographic characteristics of patients identified by computable phenotype and the registry. Results The computable phenotype had an area under the receiver operating characteristics curve of 90% (95% CI, 85%‐95%), a positive predictive value of 85% (95% CI, 77%‐93%), and identified 413 patients (an additional 231%) with pediatric PH who were not enrolled in the registry. Patients identified by the computable phenotype were clinically distinct from registry patients, with a greater prevalence of diagnoses related to perinatal distress and left heart disease. Conclusions Mining of EHRs using computable phenotypes identified a large cohort of patients not recruited using a classic registry. Fusion of EHR and registry data can improve cohort ascertainment for the study of rare diseases. Trial registration ClinicalTrials.gov: NCT02249923.

Provider Connectedness to Other Providers Reduces Risk of Readmission After Hospitalization for Heart Failure

Provider interactions other than explicit care coordination, which is challenging to measure, may influence practice and outcomes. We performed a network analysis using claims data from a commercial payor. Networks were identified based on provider pairs billing outpatient care for the same patient. We compared network variables among patients who had and did not have a 30-day readmission after hospitalization for heart failure. After adjusting for comorbidities, high median provider connectedness—normalized degree, which for each provider is the number of connections to other providers normalized to the number of providers in the region—was the network variable associated with reduced odds of readmission after heart failure hospitalization (odds ratio = 0.55; 95% confidence interval [0.35, 0.86]). We conclude that heart failure patients with high provider connectedness are less likely to require readmission. The structure and importance of provider relationships using claims data merits further study.