Ming Yang

Harvard Medical School, Boston, Massachusetts, United States

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Publications (8)31.15 Total impact

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    ABSTRACT: Although influenza has been associated with asthma exacerbations, it is not clear the extent to which this association affects healthcare use in the United States (U.S.). The first goal of this project was to determine whether, and to what extent, the incidence of asthma hospitalizations is associated with seasonal variation in influenza. Second, we used influenza trends (2000-2008) to help predict asthma admissions during the 2009 H1N1 influenza pandemic. We identified all hospitalizations between 1998 and 2008 in the Nationwide Inpatient Sample from the Healthcare Cost and Utilization Project during which a primary diagnosis of asthma was recorded. Separately, we identified all hospitalizations during which a diagnosis of influenza was recorded. We performed time series regression analyses to investigate the association of monthly asthma admissions with influenza incidence. Finally, we applied these time series regression models using 1998-2008 data, to forecast monthly asthma admissions during the 2009 influenza pandemic. Based on time series regression models, a strong, significant association exists between concurrent influenza activity and incidence of asthma hospitalizations (p-value<0.0001). Use of influenza data to predict asthma admissions during the 2009 H1N1 pandemic improved the mean squared prediction error by 60.2%. Influenza activity in the population is significantly associated with asthma hospitalizations in the U.S., and this association can be exploited to more accurately forecast asthma admissions. Our results suggest that improvements in influenza surveillance, prevention, and treatment may decrease hospitalizations of asthma patients.
    Respirology 08/2013; · 2.78 Impact Factor
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    ABSTRACT: Abstract Although influenza has been associated with chronic obstructive pulmonary disease (COPD) exacerbations, it is not clear the extent to which this association affects healthcare use in the United States. The first goal of this project was to determine to what extent the incidence of COPD hospitalizations is associated with seasonal influenza. Second, as a natural experiment, we used influenza activity to help predict COPD admissions during the 2009 H1N1 influenza pandemic. To do this, we identified all hospitalizations between 1998 and 2010 in the Nationwide Inpatient Sample from the Healthcare Cost and Utilization Project (HCUP) during which a primary diagnosis of COPD was recorded. Separately, we identified all hospitalizations during which a diagnosis of influenza was recorded. We formulated time series regression models to investigate the association of monthly COPD admissions with influenza incidence. Finally, we applied these models, fit using 1998-2008 data, to forecast monthly COPD admissions during the 2009 pandemic. Based on time series regression models, a strong, significant association exists between concurrent influenza activity and incidence of COPD hospitalizations (p-value < 0.0001). The association is especially strong among older patients requiring mechanical ventilation. Use of influenza data to predict COPD admissions during the 2009 H1N1 pandemic reduced the mean-squared prediction error by 29.9%. We conclude that influenza activity is significantly associated with COPD hospitalizations in the United States and influenza activity can be exploited to more accurately forecast COPD admissions. Our results suggest that improvements in influenza surveillance, prevention, and treatment may decrease hospitalizations of patients diagnosed with COPD.
    COPD Journal of Chronic Obstructive Pulmonary Disease 07/2013; · 2.73 Impact Factor
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    ABSTRACT: Diagnostic and treatment approaches for sarcoidosis have changed dramatically over the past decade. Yet, the most recent reports of trends in hospitalizations of sarcoidosis patients are over ten years old. The objectives of this study were to determine the incidence of sarcoidosis among hospitalized patients and to analyze recent trends and seasonality of hospitalizations in sarcoidosis patients. We performed a retrospective cohort study of the Nationwide Inpatient Sample from 1998 through 2008. We identified all hospitalizations with a primary or secondary diagnosis of sarcoidosis (ICD-9-CM code 135). Incidence was modeled as a seasonal time series about a linear trend. Time series analysis of the monthly number of hospitalizations revealed a distinct positive linear trend. Over the study period, the number of hospitalized patients with sarcoidosis increased from 37,516 to 70,947 cases. Trends were most pronounced in patients older than 55 years (p < 0.0001), African Americans (p < 0.0001), females (p = 0.0289), and non-Medicaid populations (p < 0.0001). Hospitalizations are seasonal with highest incidence in January through March. Hospitalizations among sarcoidosis patients have almost doubled during the past decade, with disproportionate rate increases in African Americans, women, and older patients. The rate also increases among patients with insurance other than Medicaid. This study indicates the need for heightened surveillance of sarcoidosis patients given the unknown consequences of evolving treatment approaches. Our results point to a need for research investigating risk factors for hospitalization, including medications, co-morbidities, demographics, and socioeconomic status.
    BMC Pulmonary Medicine 05/2012; 12:19. · 2.76 Impact Factor
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    ABSTRACT: We show that respiratory fluoroquinolone use is extremely seasonal and that fluoroquinolone use is strongly associated with influenza. In our time series model, instantaneous influenza activity was a significant predictor of use (P < .0001). Also, we estimated that reducing influenza activity by 20% would reduce prescriptions by 8%.
    Infection Control and Hospital Epidemiology 07/2011; 32(7):706-9. · 4.02 Impact Factor
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    ABSTRACT: Sales for a drug may be correlated with the prevalence of a condition treated by the drug. We found that state data revealed a strong spatial association and national data a strong temporal association between Clostridium difficile and oral vancomycin prescription sales, suggesting a new "signal" for detecting disease activity.
    Infection Control and Hospital Epidemiology 07/2011; 32(7):723-6. · 4.02 Impact Factor
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    ABSTRACT: International travel and a global expansion of dengue fever have the potential to increase the incidence of dengue in the United States. We conducted a retrospective cohort analysis of trends in dengue among hospitalized patients by using the National Inpatient Sample (2000-2007); the number of cases more than tripled (p<0.0001).
    Emerging Infectious Diseases 05/2011; 17(5):914-6. · 6.79 Impact Factor
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    ABSTRACT: With use of the Nationwide Inpatient Sample, we conducted a study to determine whether rates of Clostridium difficile infection for delivery-associated hospitalizations are increasing. From 1998 to 2006, the number and incidence of C. difficile infection among peripartum women increased significantly. These increases were comparable to those observed in the general hospitalized population.
    Infection Control and Hospital Epidemiology 03/2010; 31(5):532-4. · 4.02 Impact Factor
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    ABSTRACT: To characterize the temporal progression of the monthly incidence of Clostridium difficile infections (CDIs) and to determine whether the incidence of CDI is related to the incidence of seasonal influenza. A retrospective study of patients in the Nationwide Inpatient Sample during the period from 1998 through 2005. We identified all hospitalizations with a primary or secondary diagnosis of CDI with use of International Classification of Diseases, 9th Revision, Clinical Modification codes, and we did the same for influenza. The incidence of CDI was modeled as an autoregression about a linear trend. To investigate the association of CDI with influenza, we compared national and regional CDI and influenza series data and calculated cross-correlation functions with data that had been prewhitened (filtered to remove temporal patterns common to both series). To estimate the burden of seasonal CDI, we developed a proportional measure of seasonal CDI. Time-series analysis of the monthly number of CDI cases reveals a distinct positive linear trend and a clear pattern of seasonal variation (R2 = 0.98). The cross-correlation functions indicate that influenza activity precedes CDI activity on both a national and regional basis. The average burden of seasonal (ie, winter) CDI is 23%. The epidemiologic characteristics of CDI follow a pattern that is seasonal and associated with influenza, which is likely due to antimicrobial use during influenza seasons. Approximately 23% of average monthly CDI during the peak 3 winter months could be eliminated if CDI remained at summer levels.
    Infection Control and Hospital Epidemiology 02/2010; 31(4):382-7. · 4.02 Impact Factor