Acute Cardiovascular Events Associated With Influenza in Hospitalized Adults : A Cross-sectional Study.

BACKGROUND: Influenza may contribute to the burden of acute cardiovascular events during annual influenza epidemics. OBJECTIVE: To examine acute cardiovascular events and determine risk factors for acute heart failure (aHF) and acute ischemic heart disease (aIHD) in adults with a hospitalization associated with laboratory-confirmed influenza. DESIGN: Cross-sectional study. SETTING: U.S. Influenza Hospitalization Surveillance Network during the 2010-to-2011 through 2017-to-2018 influenza seasons. PARTICIPANTS: Adults hospitalized with laboratory-confirmed influenza and identified through influenza testing ordered by a practitioner. MEASUREMENTS: Acute cardiovascular events were ascertained using discharge codes from the International Classification of Diseases (ICD), Ninth Revision, Clinical Modification, and ICD, 10th Revision. Age, sex, race/ethnicity, tobacco use, chronic conditions, influenza vaccination, influenza antiviral medication, and influenza type or subtype were included as exposures in logistic regression models, and marginal adjusted risk ratios and 95% CIs were estimated to describe factors associated with aHF or aIHD. RESULTS: Among 89 999 adults with laboratory-confirmed influenza, 80 261 had complete medical record abstractions and available ICD codes (median age, 69 years [interquartile range, 54 to 81 years]) and 11.7% had an acute cardiovascular event. The most common such events (non-mutually exclusive) were aHF (6.2%) and aIHD (5.7%). Older age, tobacco use, underlying cardiovascular disease, diabetes, and renal disease were significantly associated with higher risk for aHF and aIHD in adults hospitalized with laboratory-confirmed influenza. LIMITATION: Underdetection of cases was likely because influenza testing was based on practitioner orders. Acute cardiovascular events were identified by ICD discharge codes and may be subject to misclassification bias. CONCLUSION: In this population-based study of adults hospitalized with influenza, almost 12% of patients had an acute cardiovascular event. Clinicians should ensure high rates of influenza vaccination, especially in those with underlying chronic conditions, to protect against acute cardiovascular events associated with influenza. PRIMARY FUNDING SOURCE: Centers for Disease Control and Prevention.

Characteristics and Maternal and Birth Outcomes of Hospitalized Pregnant Women with Laboratory-Confirmed COVID-19 - COVID-NET, 13 States, March 1-August 22, 2020.

Pregnant women might be at increased risk for severe coronavirus disease 2019 (COVID-19) (1,2). The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) (3) collects data on hospitalized pregnant women with laboratory-confirmed SARS-CoV-2, the virus that causes COVID-19; to date, such data have been limited. During March 1-August 22, 2020, approximately one in four hospitalized women aged 15-49 years with COVID-19 was pregnant. Among 598 hospitalized pregnant women with COVID-19, 54.5% were asymptomatic at admission. Among 272 pregnant women with COVID-19 who were symptomatic at hospital admission, 16.2% were admitted to an intensive care unit (ICU), and 8.5% required invasive mechanical ventilation. During COVID-19-associated hospitalizations, 448 of 458 (97.8%) completed pregnancies resulted in a live birth and 10 (2.2%) resulted in a pregnancy loss. Testing policies based on the presence of symptoms might miss COVID-19 infections during pregnancy. Surveillance of pregnant women with COVID-19, including those with asymptomatic infections, is important to understand the short- and long-term consequences of COVID-19 for mothers and newborns. Identifying COVID-19 in women during birth hospitalizations is important to guide preventive measures to protect pregnant women, parents, newborns, other patients, and hospital personnel. Pregnant women and health care providers should be made aware of the potential risks for severe COVID-19 illness, adverse pregnancy outcomes, and ways to prevent infection.

Effects of Influenza Vaccination in the United States During the 2017-2018 Influenza Season.

BACKGROUND: The severity of the 2017-2018 influenza season in the United States was high, with influenza A(H3N2) viruses predominating. Here, we report influenza vaccine effectiveness (VE) and estimate the number of vaccine-prevented influenza-associated illnesses, medical visits, hospitalizations, and deaths for the 2017-2018 influenza season. METHODS: We used national age-specific estimates of 2017-2018 influenza vaccine coverage and disease burden. We estimated VE against medically attended reverse-transcription polymerase chain reaction-confirmed influenza virus infection in the ambulatory setting using a test-negative design. We used a compartmental model to estimate numbers of influenza-associated outcomes prevented by vaccination. RESULTS: The VE against outpatient, medically attended, laboratory-confirmed influenza was 38% (95% confidence interval [CI], 31%-43%), including 22% (95% CI, 12%-31%) against influenza A(H3N2), 62% (95% CI, 50%-71%) against influenza A(H1N1)pdm09, and 50% (95% CI, 41%-57%) against influenza B. We estimated that influenza vaccination prevented 7.1 million (95% CrI, 5.4 million-9.3 million) illnesses, 3.7 million (95% CrI, 2.8 million-4.9 million) medical visits, 109 000 (95% CrI, 39 000-231 000) hospitalizations, and 8000 (95% credible interval [CrI], 1100-21 000) deaths. Vaccination prevented 10% of expected hospitalizations overall and 41% among young children (6 months-4 years). CONCLUSIONS: Despite 38% VE, influenza vaccination reduced a substantial burden of influenza-associated illness, medical visits, hospitalizations, and deaths in the United States during the 2017-2018 season. Our results demonstrate the benefit of current influenza vaccination and the need for improved vaccines.

Estimating the Incidence of Influenza at the State Level - Utah, 2016-17 and 2017-18 Influenza Seasons.

The 2017-18 U.S. influenza season was notable for its high severity, with approximately 45 million illnesses and 810,000 influenza-associated hospitalizations throughout the United States (1). The purpose of the investigation reported here was to create a state-level estimate of the number of persons in Utah who became ill with influenza disease during this severe national seasonal influenza epidemic and to create a sustainable system for making timely updates in future influenza seasons. Knowing the extent of influenza-associated illness can help public health officials, policymakers, and clinicians tailor influenza messaging, planning, and responses for seasonal influenza epidemics or during pandemics. Using national methods and existing influenza surveillance and testing data, the influenza burden (number of influenza illnesses, medical visits for influenza, and influenza-associated hospitalizations) in Utah during the 2016-17 and 2017-18 influenza seasons was estimated. During the 2016-17 season, an estimated 265,000 symptomatic illnesses affecting 9% of Utah residents occurred, resulting in 125,000 medically attended illnesses and 2,700 hospitalizations. During the 2017-18 season, an estimated 338,000 symptomatic illnesses affecting 11% of Utah residents occurred, resulting in 160,000 medically attended illnesses and 3,900 hospitalizations. Other state or county health departments could adapt similar methods in their jurisdictions to estimate the burden of influenza locally and support prompt public health activities.

Racial/ethnic differences in healthcare use among patients with uncontrolled and controlled diabetes.

OBJECTIVES: To examine racial/ethnic differences in healthcare use among patients classified as having controlled and uncontrolled diabetes. DESIGN: Data from the Carolinas HealthCare System electronic data warehouse were used. Glycemic control was defined as glycosylated hemoglobin (HbA1c) < 8% (64 mmol/mol) in 2012 (n = 9996). Patients with HbA1c ≥ 8% (64 mmol/mol) in 2012 were classified as uncontrolled (n = 2576). Race and ethnicity were jointly classified as non-Hispanic Black, non-Hispanic White or Other. Separate mixed effects negative binomial models estimated the independent effect of race/ethnicity on the number of emergency department (ED) visits, hospitalizations and physician office visits in 2013, in each patient group, adjusting for significant confounding variables. RESULTS: Rates of diabetes-related ED visits were two to three times higher for non-Hispanic Blacks compared to non-Hispanic Whites (uncontrolled rate ratio [RR]: 3.41 95% CI: 1.41-8.22; controlled RR: 2.95; 95% CI: 1.78-4.91). Similar differences were observed for all-cause ED visits (uncontrolled RR: 1.83, 95% CI: 1.50-2.24; controlled RR: 2.45, 95% CI: 2.17-2.77). Non-Hispanic Blacks with controlled and uncontrolled diabetes also had lower rates of all-cause physician office visits when compared to non-Hispanic Whites (uncontrolled RR: 0.84, 95% CI: 0.77-0.91; controlled RR: 0.81, 95% CI: 0.78-0.84). CONCLUSION: Notable racial/ethnic disparities exist in the use of emergency services and physician offices for diabetes care. Strategies such as patient education and care delivery changes that address healthcare access issues in racial/ethnic minorities should be considered to offer better diabetes management and address diabetes disparities.

Not a magic pill: a qualitative exploration of provider perspectives on antibiotic prescribing in the outpatient setting.

BACKGROUND: Inappropriate prescribing of antibiotics poses an urgent public health threat. Limited research has examined factors associated with antibiotic prescribing practices in outpatient settings. The goals of this study were to explore elements influencing provider decisions to prescribe antibiotics, identify provider recommendations for interventions to reduce inappropriate antibiotic use, and inform the clinical management of patients in the outpatient environment for infections that do not require antibiotics. METHODS: This was a qualitative study using semi-structured interviews with key informants. Seventeen outpatient providers (10 medical doctors and 7 advanced care practitioners) within a large healthcare system in Charlotte, North Carolina, participated. Interviews were audio recorded, transcribed, and analyzed for themes. RESULTS: Primary barriers to reducing inappropriate antibiotic prescribing included patient education and expectations, system-level factors, and time constraints. Providers indicated they would be interested in having system-wide, evidence-based guidelines to inform their prescribing decisions and that they would also be receptive to efforts to improve their awareness of their own prescribing practices. Results further suggested that providers experience a high demand for antibiotic prescriptions; consequently, patient education around appropriate use would be beneficial. CONCLUSIONS: Findings suggest that antibiotic prescribing in the outpatient setting is influenced by many pressures, including patient demand and patient satisfaction. Training on appropriate antibiotic prescribing, guideline-based decision support, feedback on prescribing practices, and patient education are recommended interventions to improve levels of appropriate prescribing.

Human Rabies - Wyoming and Utah, 2015.

In September 2015, a Wyoming woman was admitted to a local hospital with a 5-day history of progressive weakness, ataxia, dysarthria, and dysphagia. Because of respiratory failure, she was transferred to a referral hospital in Utah, where she developed progressive encephalitis. On day 8 of hospitalization, the patient's family told clinicians they recalled that, 1 month before admission, the woman had found a bat on her neck upon waking, but had not sought medical care. The patient's husband subsequently had contacted county invasive species authorities about the incident, but he was not advised to seek health care for evaluation of his wife's risk for rabies. On October 2, CDC confirmed the patient was infected with a rabies virus variant that was enzootic to the silver-haired bat (Lasionycteris noctivagans). The patient died on October 3. Public understanding of rabies risk from bat contact needs to be improved; cooperation among public health and other agencies can aid in referring persons with possible bat exposure for assessment of rabies risk.

Prevalence of Metabolic Syndrome in a Large Integrated Health Care System in North Carolina.

BACKGROUND: Metabolic syndrome (MetS) is a cluster of conditions--including abdominal obesity, dyslipidemia, hypertension, and hyperglycemia--that are associated with a significantly increased risk of developing diabetes and cardiovascular diseases. No information currently exists regarding the prevalence of MetS in North Carolina. This study determined the prevalence of MetS among adults receiving care in a large integrated health care system in North Carolina. METHODS: This study used data from the Carolinas HealthCare System's electronic medical record system and included adults receiving care during 2014. The association between patient demographic characteristics and MetS was determined using multivariable logistic regression. RESULTS: The prevalence of MetS was approximately 22.5%. Individuals aged 18-29 years were less likely to have MetS compared with those aged 80 years and older (odds ratio [OR], 0.61; 95% confidence interval [CI], 0.56-0.67). Groups that were more likely to have MetS included women (OR, 1.07; 95% CI, 1.05-1.10), Hispanics (OR, 1.14; 95% CI, 1.05-1.23), individuals with Medicare (OR, 1.38; 95% CI, 1.33-1.42), and those with Medicaid (OR, 1.68; 95% CI, 1.58-1.78) compared with men, whites, and those with commercial insurance, respectively. LIMITATIONS: We excluded individuals with missing data for any of the conditions that define MetS, which may underestimate the actual prevalence of this condition. CONCLUSIONS: The considerable prevalence of MetS in our North Carolina sample suggests that interventions are needed to achieve the state's population health goals.

Genetic signatures in choline and 1-carbon metabolism are associated with the severity of hepatic steatosis.

Choline metabolism is important for very low-density lipoprotein secretion, making this nutritional pathway an important contributor to hepatic lipid balance. The purpose of this study was to assess whether the cumulative effects of multiple single nucleotide polymorphisms (SNPs) across genes of choline/1-carbon metabolism and functionally related pathways increase susceptibility to developing hepatic steatosis. In biopsy-characterized cases of nonalcoholic fatty liver disease and controls, we assessed 260 SNPs across 21 genes in choline/1-carbon metabolism. When SNPs were examined individually, using logistic regression, we only identified a single SNP (PNPLA3 rs738409) that was significantly associated with severity of hepatic steatosis after adjusting for confounders and multiple comparisons (P=0.02). However, when groupings of SNPs in similar metabolic pathways were defined using unsupervised hierarchical clustering, we identified groups of subjects with shared SNP signatures that were significantly correlated with steatosis burden (P=0.0002). The lowest and highest steatosis clusters could also be differentiated by ethnicity. However, unique SNP patterns defined steatosis burden irrespective of ethnicity. Our results suggest that analysis of SNP patterns in genes of choline/1-carbon metabolism may be useful for prediction of severity of steatosis in specific subsets of people, and the metabolic inefficiencies caused by these SNPs should be examined further.

A multimodal intervention to decrease inappropriate outpatient antibiotic prescribing for upper respiratory tract infections in a large integrated healthcare system.

OBJECTIVE: To evaluate the effectiveness of Carolinas Healthcare Outpatient Antimicrobial Stewardship Empowerment Network (CHOSEN), a multicomponent outpatient stewardship program to reduce inappropriate antibiotic prescribing for upper respiratory infections by 20% over 2 years. DESIGN: Before-and-after interrupted time series of antibiotics prescribed between 2 periods: April 2016-October 2017 and May 2018-March 2020. SETTING: The study included 162 primary-care practices within a large healthcare system in the greater Charlotte, North Carolina region. PARTICIPANTS: Adult and pediatric patients with encounters for upper respiratory infections for which an antibiotic is inappropriate. METHODS: Patient and provider educational materials, along with a web-based provider prescribing dashboard aimed at reducing inappropriate antibiotic prescribing were developed and distributed. Monthly antibiotic prescribing rates were calculated as the number of eligible encounters with an antibiotic prescribed divided by the total number of eligible encounters. A segmented regression analysis compared monthly antibiotic prescribing rates before versus after CHOSEN implementation, while also accounting for practice type and seasonal trends in prescribing. RESULTS: Overall, 286,580 antibiotics were prescribed during 704,248 preintervention encounters and 277,177 during 832,200 intervention encounters. Significant reductions in inappropriate prescribing rates were observed in all outpatient specialties: family medicine (relative difference before and after the intervention, -20.4%), internal medicine (-19.5%), pediatric medicine (-17.2%), and urgent care (-16.6%). CONCLUSIONS: A robust multimodal intervention that combined a provider prescribing dashboard with a targeted education campaign demonstrated significant decreases in inappropriate outpatient antibiotic prescribing for upper respiratory tract infections in a large integrated ambulatory network.

Association between composition of the human gastrointestinal microbiome and development of fatty liver with choline deficiency.

BACKGROUND & AIMS: Nonalcoholic fatty liver disease affects up to 30% of the US population, but the mechanisms underlying this condition are incompletely understood. We investigated how diet standardization and choline deficiency influence the composition of the microbial community in the human gastrointestinal tract and the development of fatty liver under conditions of choline deficiency. METHODS: We performed a 2-month inpatient study of 15 female subjects who were placed on well-controlled diets in which choline levels were manipulated. We used 454-FLX pyrosequencing of 16S ribosomal RNA bacterial genes to characterize microbiota in stool samples collected over the course of the study. RESULTS: The compositions of the gastrointestinal microbial communities changed with choline levels of diets; each individual's microbiome remained distinct for the duration of the experiment, even though all subjects were fed identical diets. Variations between subjects in levels of Gammaproteobacteria and Erysipelotrichi were directly associated with changes in liver fat in each subject during choline depletion. Levels of these bacteria, change in amount of liver fat, and a single nucleotide polymorphism that affects choline were combined into a model that accurately predicted the degree to which subjects developed fatty liver on a choline-deficient diet. CONCLUSIONS: Host factors and gastrointestinal bacteria each respond to dietary choline deficiency, although the gut microbiota remains distinct in each individual. We identified bacterial biomarkers of fatty liver that result from choline deficiency, adding to the accumulating evidence that gastrointestinal microbes have a role in metabolic disorders.

The Association Between Metabolic Syndrome and Non-Alcoholic Fatty Liver Disease Diagnosis Varies by Race.

Objectives: This study investigated how the association between metabolic syndrome (MetS) and nonalcoholic fatty liver disease (NAFLD) diagnosis varies between non-Hispanic African American and white patients. Methods: A retrospective cohort study was performed using electronic medical records from an integrated health care system (2010-2018). Adults with records for all MetS measurements (body mass index, lipids, blood pressure, and blood glucose) in 2011, who did not have a NAFLD diagnosis before their last MetS measurement, were included. Results: The study cohort consisted of 139,336 patients (age 56.1 ± 15.2 years, 57.9% female, 79.4% non-Hispanic white). The rate of NAFLD diagnosis was higher in MetS patients compared with non-MetS patients [adjusted hazards ratio (AHR) = 1.99, 95% CI = 1.91-2.09] with a significant interaction by race (AHR = 2.05, 95% CI = 1.95-2.15 in non-Hispanic whites vs. AHR = 1.76, 95% CI = 1.58-1.96 non-Hispanic African Americans, P = 0.017). Secondary analyses revealed that the relative NAFLD diagnosis rate was higher in non-Hispanic whites with MetS compared with non-Hispanic African Americans with MetS among females and patients 18-39 years of age and 40-59 years, but not among males and those ≥60 years of age. Conclusions: Non-Hispanic white patients with MetS, particularly females and those <60 years of age, may be at increased risk of NAFLD compared with non-Hispanic African American MetS patients and may benefit from extra attention regarding NAFLD screening.

Realizing a learning health system through process, rigor and culture change.

While many healthcare organizations strive to achieve the patient care benefits of being a learning health system (LHS), myriad challenges stand in the way of successful implementation. The reality of creating a true LHS requires top-to-bottom commitment to culture change with the necessary vision, leadership, and investment. The Center for Outcomes Research and Evaluation (CORE) is a multidisciplinary research unit embedded within a large, vertically integrated healthcare system in the southeastern United States. We used a two-pronged approach to: a) methodically recruit a team of experts, while generating early wins that demonstrated real success; and b) build relationships and buy-in across organizational leadership. Building out a team with diverse expertise created the ability to deploy pragmatic, data-driven research designs that fit seamlessly into real-world care delivery, resulting in agile study execution that aligns with health system timelines. Case study examples from hospital readmissions and antibiotic stewardship illustrate how our LHS operationalizes practice-informed research and research-informed practice. Lessons from this experience can serve as a blueprint for other healthcare systems or networks seeking to expand the promise of the LHS framework to improve health for patients and communities.

Census tract socioeconomic indicators and COVID-19-associated hospitalization rates-COVID-NET surveillance areas in 14 states, March 1-April 30, 2020.

OBJECTIVES: Some studies suggested more COVID-19-associated hospitalizations among racial and ethnic minorities. To inform public health practice, the COVID-19-associated Hospitalization Surveillance Network (COVID-NET) quantified associations between race/ethnicity, census tract socioeconomic indicators, and COVID-19-associated hospitalization rates. METHODS: Using data from COVID-NET population-based surveillance reported during March 1-April 30, 2020 along with socioeconomic and denominator data from the US Census Bureau, we calculated COVID-19-associated hospitalization rates by racial/ethnic and census tract-level socioeconomic strata. RESULTS: Among 16,000 COVID-19-associated hospitalizations, 34.8% occurred among non-Hispanic White (White) persons, 36.3% among non-Hispanic Black (Black) persons, and 18.2% among Hispanic or Latino (Hispanic) persons. Age-adjusted COVID-19-associated hospitalization rate were 151.6 (95% Confidence Interval (CI): 147.1-156.1) in census tracts with >15.2%-83.2% of persons living below the federal poverty level (high-poverty census tracts) and 75.5 (95% CI: 72.9-78.1) in census tracts with 0%-4.9% of persons living below the federal poverty level (low-poverty census tracts). Among White, Black, and Hispanic persons living in high-poverty census tracts, age-adjusted hospitalization rates were 120.3 (95% CI: 112.3-128.2), 252.2 (95% CI: 241.4-263.0), and 341.1 (95% CI: 317.3-365.0), respectively, compared with 58.2 (95% CI: 55.4-61.1), 304.0 (95%: 282.4-325.6), and 540.3 (95% CI: 477.0-603.6), respectively, in low-poverty census tracts. CONCLUSIONS: Overall, COVID-19-associated hospitalization rates were highest in high-poverty census tracts, but rates among Black and Hispanic persons were high regardless of poverty level. Public health practitioners must ensure mitigation measures and vaccination campaigns address needs of racial/ethnic minority groups and people living in high-poverty census tracts.

Modeling COVID-19 Latent Prevalence to Assess a Public Health Intervention at a State and Regional Scale: Retrospective Cohort Study.

BACKGROUND: Emergence of the coronavirus disease (COVID-19) caught the world off guard and unprepared, initiating a global pandemic. In the absence of evidence, individual communities had to take timely action to reduce the rate of disease spread and avoid overburdening their health care systems. Although a few predictive models have been published to guide these decisions, most have not taken into account spatial differences and have included assumptions that do not match the local realities. Access to reliable information that is adapted to local context is critical for policy makers to make informed decisions during a rapidly evolving pandemic. OBJECTIVE: The goal of this study was to develop an adapted susceptible-infected-removed (SIR) model to predict the trajectory of the COVID-19 pandemic in North Carolina and the Charlotte Metropolitan Region, and to incorporate the effect of a public health intervention to reduce disease spread while accounting for unique regional features and imperfect detection. METHODS: Three SIR models were fit to infection prevalence data from North Carolina and the greater Charlotte Region and then rigorously compared. One of these models (SIR-int) accounted for a stay-at-home intervention and imperfect detection of COVID-19 cases. We computed longitudinal total estimates of the susceptible, infected, and removed compartments of both populations, along with other pandemic characteristics such as the basic reproduction number. RESULTS: Prior to March 26, disease spread was rapid at the pandemic onset with the Charlotte Region doubling time of 2.56 days (95% CI 2.11-3.25) and in North Carolina 2.94 days (95% CI 2.33-4.00). Subsequently, disease spread significantly slowed with doubling times increased in the Charlotte Region to 4.70 days (95% CI 3.77-6.22) and in North Carolina to 4.01 days (95% CI 3.43-4.83). Reflecting spatial differences, this deceleration favored the greater Charlotte Region compared to North Carolina as a whole. A comparison of the efficacy of intervention, defined as 1 - the hazard ratio of infection, gave 0.25 for North Carolina and 0.43 for the Charlotte Region. In addition, early in the pandemic, the initial basic SIR model had good fit to the data; however, as the pandemic and local conditions evolved, the SIR-int model emerged as the model with better fit. CONCLUSIONS: Using local data and continuous attention to model adaptation, our findings have enabled policy makers, public health officials, and health systems to proactively plan capacity and evaluate the impact of a public health intervention. Our SIR-int model for estimated latent prevalence was reasonably flexible, highly accurate, and demonstrated efficacy of a stay-at-home order at both the state and regional level. Our results highlight the importance of incorporating local context into pandemic forecast modeling, as well as the need to remain vigilant and informed by the data as we enter into a critical period of the outbreak.

Spatial and temporal clustering of patients hospitalized with laboratory-confirmed influenza in the United States.

BACKGROUND: Timing of influenza spread across the United States is dependent on factors including local and national travel patterns and climate. Local epidemic intensity may be influenced by social, economic and demographic patterns. Data are needed to better explain how local socioeconomic factors influence both the timing and intensity of influenza seasons to result in national patterns. METHODS: To determine the spatial and temporal impacts of socioeconomics on influenza hospitalization burden and timing, we used population-based laboratory-confirmed influenza hospitalization surveillance data from the CDC-sponsored Influenza Hospitalization Surveillance Network (FluSurv-NET) at up to 14 sites from the 2009/2010 through 2013/2014 seasons (n = 35,493 hospitalizations). We used a spatial scan statistic and spatiotemporal wavelet analysis, to compare temporal patterns of influenza spread between counties and across the country. RESULTS: There were 56 spatial clusters identified in the unadjusted scan statistic analysis using data from the 2010/2011 through the 2013/2014 seasons, with relative risks (RRs) ranging from 0.09 to 4.20. After adjustment for socioeconomic factors, there were five clusters identified with RRs ranging from 0.21 to 1.20. In the wavelet analysis, most sites were in phase synchrony with one another for most years, except for the H1N1 pandemic year (2009-2010), wherein most sites had differential epidemic timing from the referent site in Georgia. CONCLUSIONS: Socioeconomic factors strongly impact local influenza hospitalization burden. Influenza phase synchrony varies by year and by socioeconomics, but is less influenced by socioeconomics than is disease burden.

A patient and family reporting system for perceived ambulatory note mistakes: experience at 3 U.S. healthcare centers.

OBJECTIVE: The study sought to test a patient and family online reporting system for perceived ambulatory visit note inaccuracies. MATERIALS AND METHODS: We implemented a patient and family electronic reporting system at 3 U.S. healthcare centers: a northeast urban academic adult medical center (AD), a northeast urban academic pediatric medical center (PED), and a southeast nonprofit hospital network (NET). Patients and families reported potential documentation inaccuracies after reading primary care and subspecialty visit notes. Results were characterized using descriptive statistics and coded for clinical relevance. RESULTS: We received 1440 patient and family reports (780 AD, 402 PED, and 258 NET), and 27% of the reports identified a potential inaccuracy (25% AD, 35% PED, 28% NET). Among these, patients and families indicated that the potential inaccuracy was important or very important in 58% of reports (55% AD, 55% PED, 71% NET). The most common types of potential inaccuracies included description of symptoms (21%), past medical problems (21%), medications (18%), and important information that was missing (15%). Most patient- and family-reported inaccuracies resulted in a change to care or to the medical record (55% AD, 67% PED, data not available at NET). DISCUSSION: About one-quarter of patients and families using an online reporting system identified potential documentation inaccuracies in visit notes and more than half were considered important by patients and clinicians, underscoring the potential role of patients and families as ambulatory safety partners. CONCLUSIONS: Partnering with patients and families to obtain reports on inaccuracies in visit notes may contribute to safer care. Mechanisms to encourage greater use of patient and family reporting systems are needed.

Whole Genome Sequencing detects Inter-Facility Transmission of Carbapenem-resistant Klebsiella pneumoniae.

OBJECTIVES: To identify transmission patterns of Carbapenem-resistant Klebsiella pneumoniae infection during an outbreak at a large, tertiary care hospital and to detect whether the outbreak organisms spread to other facilities in the integrated healthcare network. METHODS: We analyzed 71 K. pneumoniae whole genome sequences collected from clinical specimens before, during and after the outbreak and reviewed corresponding patient medical records. Sequence and patient data were used to model probable transmissions and assess factors associated with the outbreak. RESULTS: We identified close genetic relationships among carbapenem-resistant K. pneumoniae isolates sampled during the study period. Transmission tree analysis combined with patient records uncovered extended periods of silent colonization in many study patients and transmission routes that were likely the result of asymptomatic patients transitioning between facilities. CONCLUSIONS: Detecting how and where Carbapenem-resistant K. pneumoniae infections spread is challenging in an environment of rising prevalence, asymptomatic carriage and mobility of patients. Whole genome sequencing improved the precision of investigating inter-facility transmissions. Our results emphasize that containment of Carbapenem-resistant K. pneumoniae infections requires coordinated efforts between healthcare networks and settings of care that acknowledge and mitigate transmission risk conferred by undetected carriage and by patient transfers between facilities.

Correlation analysis of HOX, ErbB and IGFBP family gene expression in ovarian cancer.

Utilizing microarray gene expression data in cancer research possesses the ability to identify deregulated cellular pathways involved in malignant development. This study investigated the relationships of three gene families, HOX, ErbB and IGFBP, with regard to the development of ovarian cancer. These families were of interest because of similar chromosomal locations and their deregulated expression in ovarian cancer. Higher level statistics were used to differentially analyze microarray data in 65 ovarian samples to assess correlation and relationships among the gene families of interest. Fifteen genes in the three families were found to be significantly deregulated. Thirty-eight significant correlations were found within and between the genes of interest. Our data indicates that the significantly modeled relationships between HOX, ErbB and IGFBP gene pairs could provide insight into the underlying biological mechanisms in ovarian cancer.