1,143 results on '"Lee, Bruce Y."'
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2. Food and Nutrition Insecurity: Experiences That Differ for Some and Independently Predict Diet-Related Disease, Los Angeles County, 2022
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Livings, Michelle Sarah, Bruine de Bruin, Wändi, Wasim, Natasha, Wilson, John P, Lee, Bruce Y, and de la Haye, Kayla
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- 2024
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3. Benefits of Meeting the Healthy People 2030 Youth Sports Participation Target
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Martinez, Marie F., Weatherwax, Colleen, Piercy, Katrina, Whitley, Meredith A., Bartsch, Sarah M., Heneghan, Jessie, Fox, Martin, Bowers, Matthew T., Chin, Kevin L., Velmurugan, Kavya, Dibbs, Alexis, Smith, Alan L., Pfeiffer, Karin A., Farrey, Tom, Tsintsifas, Alexandra, Scannell, Sheryl A., and Lee, Bruce Y.
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- 2024
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4. How the Timing of Annual COVID-19 Vaccination of Nursing Home Residents and Staff Affects Its Value
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Bartsch, Sarah M., Weatherwax, Colleen, Wasserman, Michael R., Chin, Kevin L., Martinez, Marie F., Velmurugan, Kavya, Singh, Raveena D., John, Danielle C., Heneghan, Jessie L., Gussin, Gabrielle M., Scannell, Sheryl A., Tsintsifas, Alexandra C., O'Shea, Kelly J., Dibbs, Alexis M., Leff, Bruce, Huang, Susan S., and Lee, Bruce Y.
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- 2024
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5. Qualitative systems mapping in promoting physical activity and cardiorespiratory fitness: Perspectives and recommendations
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Pronk, Nicolaas P. and Lee, Bruce Y.
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- 2024
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6. The potential epidemiologic, clinical, and economic value of a universal coronavirus vaccine: a modelling study
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Bartsch, Sarah M., O'Shea, Kelly J., John, Danielle C., Strych, Ulrich, Bottazzi, Maria Elena, Martinez, Marie F., Ciciriello, Allan, Chin, Kevin L., Weatherwax, Colleen, Velmurugan, Kavya, Heneghan, Jessie, Scannell, Sheryl A., Hotez, Peter J., and Lee, Bruce Y.
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- 2024
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7. Modeling Interventions to Reduce the Spread of Multidrug-Resistant Organisms Between Health Care Facilities in a Region
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Bartsch, Sarah M, Wong, Kim F, Mueller, Leslie E, Gussin, Gabrielle M, McKinnell, James A, Tjoa, Thomas, Wedlock, Patrick T, He, Jiayi, Chang, Justin, Gohil, Shruti K, Miller, Loren G, Huang, Susan S, and Lee, Bruce Y
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Health Services and Systems ,Biomedical and Clinical Sciences ,Clinical Sciences ,Health Sciences ,Antimicrobial Resistance ,Emerging Infectious Diseases ,Health Services ,Clinical Research ,Prevention ,Bacterial Infections ,California ,Disease Transmission ,Infectious ,Drug Resistance ,Multiple ,Bacterial ,Humans ,Practice Guidelines as Topic ,Skilled Nursing Facilities ,Biomedical and clinical sciences ,Health sciences - Abstract
ImportanceMultidrug-resistant organisms (MDROs) can spread across health care facilities in a region. Because of limited resources, certain interventions can be implemented in only some facilities; thus, decision-makers need to evaluate which interventions may be best to implement.ObjectiveTo identify a group of target facilities and assess which MDRO intervention would be best to implement in the Shared Healthcare Intervention to Eliminate Life-threatening Dissemination of MDROs in Orange County, a large regional public health collaborative in Orange County, California.Design, setting, and participantsAn agent-based model of health care facilities was developed in 2016 to simulate the spread of methicillin-resistant Staphylococcus aureus (MRSA) and carbapenem-resistant Enterobacteriaceae (CRE) for 10 years starting in 2010 and to simulate the use of various MDRO interventions for 3 years starting in 2017. All health care facilities (23 hospitals, 5 long-term acute care hospitals, and 74 nursing homes) serving adult inpatients in Orange County, California, were included, and 42 target facilities were identified via network analyses.ExposuresIncreasing contact precaution effectiveness, increasing interfacility communication about patients' MDRO status, and performing decolonization using antiseptic bathing soap and a nasal product in a specific group of target facilities.Main outcomes and measuresMRSA and CRE prevalence and number of new carriers (ie, transmission events).ResultsCompared with continuing infection control measures used in Orange County as of 2017, increasing contact precaution effectiveness from 40% to 64% in 42 target facilities yielded relative reductions of 0.8% (range, 0.5%-1.1%) in MRSA prevalence and 2.4% (range, 0.8%-4.6%) in CRE prevalence in health care facilities countywide after 3 years, averting 761 new MRSA transmission events (95% CI, 756-765 events) and 166 new CRE transmission events (95% CI, 158-174 events). Increasing interfacility communication of patients' MDRO status to 80% in these target facilities produced no changes in the prevalence or transmission of MRDOs. Implementing decolonization procedures (clearance probability: 39% in hospitals, 27% in long-term acute care facilities, and 3% in nursing homes) yielded a relative reduction of 23.7% (range, 23.5%-23.9%) in MRSA prevalence, averting 3515 new transmission events (95% CI, 3509-3521 events). Increasing the effectiveness of antiseptic bathing soap to 48% yielded a relative reduction of 39.9% (range, 38.5%-41.5%) in CRE prevalence, averting 1435 new transmission events (95% CI, 1427-1442 events).Conclusions and relevanceThe findings of this study highlight the ways in which modeling can inform design of regional interventions and suggested that decolonization would be the best strategy for the Shared Healthcare Intervention to Eliminate Life-threatening Dissemination of MDROs in Orange County.
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- 2021
8. Neglected tropical disease vaccines: hookworm, leishmaniasis, and schistosomiasis
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Hotez, Peter J., Bottazzi, Maria Elena, Kaye, Paul M., Lee, Bruce Y., and Puchner, Karl Philipp
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- 2023
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9. Food Insecurity Is Under-reported in Surveys That Ask About the Past Year
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Livings, Michelle S., Bruine de Bruin, Wändi, Wilson, John P., Lee, Bruce Y., Xu, Mengya, Frazzini, Alison, Chandra, Swati, Weber, Kate, Babboni, Marianna, and de la Haye, Kayla
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- 2023
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10. Response to: “Quantifying the effect of vaccination on transmission in modelling studies”
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Bartsch, Sarah M., primary, O'Shea, Kelly J., additional, Strych, Ulrich, additional, Bottazzi, Maria Elena, additional, and Lee, Bruce Y., additional
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- 2024
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11. A Systems Map of the Challenges of Climate Communication
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Heneghan, Jessie, primary, John, Danielle C., additional, Bartsch, Sarah M., additional, Piltch-Loeb, Rachael, additional, Gilbert, Christine, additional, Kass, Dan, additional, Chin, Kevin L., additional, Dibbs, Alexis, additional, Shah, Tej D., additional, O’Shea, Kelly J., additional, Scannell, Sheryl A., additional, Martinez, Marie F., additional, and Lee, Bruce Y., additional
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- 2024
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12. The Need to Focus More on Climate Change Communication and Incorporate More Systems Approaches
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Lee, Bruce Y., primary, Pavilonis, Brian, additional, John, Danielle C., additional, Heneghan, Jessie, additional, Bartsch, Sarah M., additional, and Kavouras, Ilias, additional
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- 2024
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13. When increasing vegetable production may worsen food availability gaps: A simulation model in India
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Spiker, Marie L., Welling, Joel, Hertenstein, Daniel, Mishra, Suvankar, Mishra, Krishna, Hurley, Kristen M., Neff, Roni A., Fanzo, Jess, and Lee, Bruce Y.
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- 2023
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14. Knowing More of the Iceberg: How Detecting a Greater Proportion of Carbapenem-Resistant Enterobacteriaceae (CRE) Carriers Impacts Transmission
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Bartsch, Sarah M, Wong, Kim F, Stokes-Cawley, Owen J, McKinnell, James A, Cao, Chenghua, Gussin, Gabrielle M, Mueller, Leslie E, Kim, Diane S, Miller, Loren G, Huang, Susan S, and Lee, Bruce Y
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Prevention ,Carbapenem-Resistant Enterobacteriaceae ,Carrier State ,Contact Tracing ,Enterobacteriaceae Infections ,Hospitals ,Humans ,Infection Control ,Nursing Homes ,Prevalence ,CRE ,burden ,unknown carriers ,iceberg ,detection ,Biological Sciences ,Medical and Health Sciences ,Microbiology - Abstract
BackgroundClinical testing detects a fraction of carbapenem-resistant Enterobacteriaceae (CRE) carriers. Detecting a greater proportion could lead to increased use of infection prevention and control measures but requires resources. Therefore, it is important to understand the impact of detecting increasing proportions of CRE carriers.MethodsWe used our Regional Healthcare Ecosystem Analyst-generated agent-based model of adult inpatient healthcare facilities in Orange County, California, to explore the impact that detecting greater proportions of carriers has on the spread of CRE.ResultsDetecting and placing 1 in 9 carriers on contact precautions increased the prevalence of CRE from 0% to 8.0% countywide over 10 years. Increasing the proportion of detected carriers from 1 in 9 up to 1 in 5 yielded linear reductions in transmission; at proportions >1 in 5, reductions were greater than linear. Transmission reductions did not occur for 1, 4, or 5 years, varying by facility type. With a contact precautions effectiveness of ≤70%, the detection level yielding nonlinear reductions remained unchanged; with an effectiveness of >80%, detecting only 1 in 5 carriers garnered large reductions in the number of new CRE carriers. Trends held when CRE was already present in the region.ConclusionAlthough detection of all carriers provided the most benefits for preventing new CRE carriers, if this is not feasible, it may be worthwhile to aim for detecting >1 in 5 carriers.
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- 2020
15. Knowing More of the Iceberg: How Detecting a Greater Proportion of Carbapenem-Resistant Enterobacteriaceae Carriers Influences Transmission.
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Bartsch, Sarah M, Wong, Kim F, Stokes-Cawley, Owen J, McKinnell, James A, Cao, Chenghua, Gussin, Gabrielle M, Mueller, Leslie E, Kim, Diane S, Miller, Loren G, Huang, Susan S, and Lee, Bruce Y
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CRE ,burden ,detection ,iceberg ,unknown carriers ,Microbiology ,Biological Sciences ,Medical and Health Sciences - Abstract
BackgroundClinical testing detects a fraction of carbapenem-resistant Enterobacteriaceae (CRE) carriers. Detecting a greater proportion could lead to increased use of infection prevention and control measures but requires resources. Therefore, it is important to understand the impact of detecting increasing proportions of CRE carriers.MethodsWe used our Regional Healthcare Ecosystem Analyst-generated agent-based model of adult inpatient healthcare facilities in Orange County, California, to explore the impact that detecting greater proportions of carriers has on the spread of CRE.ResultsDetecting and placing 1 in 9 carriers on contact precautions increased the prevalence of CRE from 0% to 8.0% countywide over 10 years. Increasing the proportion of detected carriers from 1 in 9 up to 1 in 5 yielded linear reductions in transmission; at proportions >1 in 5, reductions were greater than linear. Transmission reductions did not occur for 1, 4, or 5 years, varying by facility type. With a contact precautions effectiveness of ≤70%, the detection level yielding nonlinear reductions remained unchanged; with an effectiveness of >80%, detecting only 1 in 5 carriers garnered large reductions in the number of new CRE carriers. Trends held when CRE was already present in the region.ConclusionAlthough detection of all carriers provided the most benefits for preventing new CRE carriers, if this is not feasible, it may be worthwhile to aim for detecting >1 in 5 carriers.
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- 2020
16. The SHIELD Orange County Project: Multidrug-resistant Organism Prevalence in 21 Nursing Homes and Long-term Acute Care Facilities in Southern California.
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McKinnell, James A, Singh, Raveena D, Miller, Loren G, Kleinman, Ken, Gussin, Gabrielle, He, Jiayi, Saavedra, Raheeb, Dutciuc, Tabitha D, Estevez, Marlene, Chang, Justin, Heim, Lauren, Yamaguchi, Stacey, Custodio, Harold, Gohil, Shruti K, Park, Steven, Tam, Steven, Robinson, Philip A, Tjoa, Thomas, Nguyen, Jenny, Evans, Kaye D, Bittencourt, Cassiana E, Lee, Bruce Y, Mueller, Leslie E, Bartsch, Sarah M, Jernigan, John A, Slayton, Rachel B, Stone, Nimalie D, Zahn, Matthew, Mor, Vincent, McConeghy, Kevin, Baier, Rosa R, Janssen, Lynn, O'Donnell, Kathleen, Weinstein, Robert A, Hayden, Mary K, Coady, Micaela H, Bhattarai, Megha, Peterson, Ellena M, and Huang, Susan S
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Humans ,Enterobacteriaceae Infections ,Staphylococcal Infections ,Chlorhexidine ,Long-Term Care ,Prevalence ,Public Health ,Drug Resistance ,Multiple ,Bacterial ,Nursing Homes ,California ,Methicillin-Resistant Staphylococcus aureus ,Vancomycin-Resistant Enterococci ,Carbapenem-Resistant Enterobacteriaceae ,CRE ,MRSA ,chlorhexidine ,decolonization ,long term care ,public health ,Emerging Infectious Diseases ,Antimicrobial Resistance ,Vaccine Related ,Aging ,Biodefense ,Prevention ,Clinical Research ,Health Services ,Biological Sciences ,Medical and Health Sciences ,Microbiology - Abstract
BackgroundMultidrug-resistant organisms (MDROs) spread between hospitals, nursing homes (NHs), and long-term acute care facilities (LTACs) via patient transfers. The Shared Healthcare Intervention to Eliminate Life-threatening Dissemination of MDROs in Orange County is a regional public health collaborative involving decolonization at 38 healthcare facilities selected based on their high degree of patient sharing. We report baseline MDRO prevalence in 21 NHs/LTACs.MethodsA random sample of 50 adults for 21 NHs/LTACs (18 NHs, 3 LTACs) were screened for methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant Enterococcus spp. (VRE), extended-spectrum β-lactamase-producing organisms (ESBL), and carbapenem-resistant Enterobacteriaceae (CRE) using nares, skin (axilla/groin), and peri-rectal swabs. Facility and resident characteristics associated with MDRO carriage were assessed using multivariable models clustering by person and facility.ResultsPrevalence of MDROs was 65% in NHs and 80% in LTACs. The most common MDROs in NHs were MRSA (42%) and ESBL (34%); in LTACs they were VRE (55%) and ESBL (38%). CRE prevalence was higher in facilities that manage ventilated LTAC patients and NH residents (8% vs
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- 2019
17. Health and Economic Value of Eliminating Socioeconomic Disparities in US Youth Physical Activity
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Powell-Wiley, Tiffany M., primary, Martinez, Marie F., additional, Heneghan, Jessie, additional, Weatherwax, Colleen, additional, Osei Baah, Foster, additional, Velmurugan, Kavya, additional, Chin, Kevin L., additional, Ayers, Colby, additional, Cintron, Manuel A., additional, Ortiz-Whittingham, Lola R., additional, Sandler, Dana, additional, Sharda, Sonal, additional, Whitley, Meredith, additional, Bartsch, Sarah M., additional, O’Shea, Kelly J., additional, Tsintsifas, Alexandra, additional, Dibbs, Alexis, additional, Scannell, Sheryl A., additional, and Lee, Bruce Y., additional
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- 2024
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18. Tracking the spread of carbapenem-resistant Enterobacteriaceae (CRE) through clinical cultures alone underestimates the spread of CRE even more than anticipated
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Lee, Bruce Y, Bartsch, Sarah M, Wong, Kim F, Kim, Diane S, Cao, Chenghua, Mueller, Leslie E, Gussin, Gabrielle M, McKinnell, James A, Miller, Loren G, and Huang, Susan S
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Anti-Bacterial Agents ,California ,Carbapenem-Resistant Enterobacteriaceae ,Carbapenems ,Enterobacteriaceae Infections ,Health Facilities ,Humans ,Medical and Health Sciences ,Epidemiology - Published
- 2019
19. Maintaining face mask use before and after achieving different COVID-19 vaccination coverage levels: a modelling study
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Bartsch, Sarah M, O'Shea, Kelly J, Chin, Kevin L, Strych, Ulrich, Ferguson, Marie C, Bottazzi, Maria Elena, Wedlock, Patrick T, Cox, Sarah N, Siegmund, Sheryl S, Hotez, Peter J, and Lee, Bruce Y
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- 2022
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20. The impact of reducing the frequency of night feeding on infant BMI
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O’Shea, Kelly J., Ferguson, Marie C., Esposito, Layla, Hammer, Lawrence D., Avelis, Cameron, Hertenstein, Daniel, Gonzales, Mario Solano, Bartsch, Sarah M., Wedlock, Patrick T., Siegmund, Sheryl S., and Lee, Bruce Y.
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- 2022
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21. What Is the Economic Benefit of Annual COVID-19 Vaccination From the Adult Individual Perspective?
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Bartsch, Sarah M, O'Shea, Kelly J, Weatherwax, Colleen, Strych, Ulrich, Velmurugan, Kavya, John, Danielle C, Bottazzi, Maria Elena, Hussein, Mustafa, Martinez, Marie F, Chin, Kevin L, Ciciriello, Allan, Heneghan, Jessie, Dibbs, Alexis, Scannell, Sheryl A, Hotez, Peter J, and Lee, Bruce Y
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SARS-CoV-2 ,COVID-19 ,SARS-CoV-2 Omicron variant ,VACCINE effectiveness ,MONETARY incentives - Abstract
Background With coronavirus disease 2019 (COVID-19) vaccination no longer mandated by many businesses/organizations, it is now up to individuals to decide whether to get any new boosters/updated vaccines going forward. Methods We developed a Markov model representing the potential clinical/economic outcomes from an individual perspective in the United States of getting versus not getting an annual COVID-19 vaccine. Results For an 18–49 year old, getting vaccinated at its current price ($60) can save the individual on average $ 30–$603 if the individual is uninsured and $4–$437 if the individual has private insurance, as long as the starting vaccine efficacy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is ≥50% and the weekly risk of getting infected is ≥0.2%, corresponding to an individual interacting with 9 other people in a day under Winter 2023–2024 Omicron SARS-CoV-2 variant conditions with an average infection prevalence of 10%. For a 50–64 year old, these cost-savings increase to $111–$1278 and $119–$1706 for someone without and with insurance, respectively. The risk threshold increases to ≥0.4% (interacting with 19 people/day), when the individual has 13.4% preexisting protection against infection (eg, vaccinated 9 months earlier). Conclusions There is both clinical and economic incentive for the individual to continue to get vaccinated against COVID-19 each year. [ABSTRACT FROM AUTHOR]
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- 2024
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22. The Economic Value of the Centers for Disease Control and Prevention Carbapenem-Resistant Enterobacteriaceae Toolkit
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Bartsch, Sarah M, Huang, Susan S, McKinnell, James A, Wong, Kim F, Mueller, Leslie E, Miller, Loren G, and Lee, Bruce Y
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Health Services and Systems ,Health Sciences ,Clinical Research ,Cost Effectiveness Research ,Prevention ,Health Services ,Good Health and Well Being ,California ,Carbapenem-Resistant Enterobacteriaceae ,Carbapenems ,Centers for Disease Control and Prevention ,U.S. ,Computer Simulation ,Cost of Illness ,Cost-Benefit Analysis ,Cross Infection ,Enterobacteriaceae Infections ,Health Expenditures ,Hospitals ,Humans ,Infection Control ,United States ,Medical and Health Sciences ,Epidemiology ,Biomedical and clinical sciences ,Health sciences - Abstract
OBJECTIVEWhile previous work showed that the Centers for Disease Control and Prevention toolkit for carbapenem-resistant Enterobacteriaceae (CRE) can reduce spread regionally, these interventions are costly, and decisions makers want to know whether and when economic benefits occur.DESIGNEconomic analysisSETTINGOrange County, CaliforniaMETHODSUsing our Regional Healthcare Ecosystem Analyst (RHEA)-generated agent-based model of all inpatient healthcare facilities, we simulated the implementation of the CRE toolkit (active screening of interfacility transfers) in different ways and estimated their economic impacts under various circumstances.RESULTSCompared to routine control measures, screening generated cost savings by year 1 when hospitals implemented screening after identifying ≤20 CRE cases (saving $2,000-$9,000) and by year 7 if all hospitals implemented in a regional coordinated manner after 1 hospital identified a CRE case (hospital perspective). Cost savings was achieved only if hospitals independently screened after identifying 10 cases (year 1, third-party payer perspective). Cost savings was achieved by year 1 if hospitals independently screened after identifying 1 CRE case and by year 3 if all hospitals coordinated and screened after 1 hospital identified 1 case (societal perspective). After a few years, all strategies cost less and have positive health effects compared to routine control measures; most strategies generate a positive cost-benefit each year.CONCLUSIONSActive screening of interfacility transfers garnered cost savings in year 1 of implementation when hospitals acted independently and by year 3 if all hospitals collectively implemented the toolkit in a coordinated manner. Despite taking longer to manifest, coordinated regional control resulted in greater savings over time.Infect Control Hosp Epidemiol 2018;39:516-524.
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- 2018
23. The CDC SHIELD Orange County Project – Baseline Multi Drug-Resistant Organism (MDRO) Prevalence in a Southern California Region
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Singh, Raveena D, Jernigan, John A, Slayton, Rachel B, Stone, Nimalie D, McKinnell, James A, Miller, Loren G, Kleinman, Ken, Heim, Lauren, Dutciuc, Tabitha D, Estevez, Marlene, Gussin, Gabrielle, Chang, Justin, Peterson, Ellena M, Evans, Kaye D, Lee, Bruce Y, Mueller, Leslie E, Bartsch, Sarah M, Zahn, Matthew, Janssen, Lynn, Weinstein, Robert A, Hayden, Mary K, Gohil, Shruti K, Park, Steven, Tam, Steven, Saavedra, Raheeb, Yamaguchi, Stacey, Custodio, Harold, Nguyen, Jenny, Tjoa, Thomas, He, Jiayi, O’Donnell, Kathleen, Coady, Micaela H, Platt, Richard, and Huang, Susan S
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Clinical Research ,Health Services ,Emerging Infectious Diseases ,Good Health and Well Being - Abstract
Abstract Background MDROs can spread between hospitals, nursing homes (NH), and long-term acute care facilities (LTACs) via shared patients. SHIELD OC is a regional decolonization collaborative involving 38 of 104 countywide adult facilities identified by their high degree of direct and indirect patient sharing with one another. We report baseline MDRO prevalence in these facilities. Methods Adult patients in 38 facilities (17 hospitals, 18 NHs, 3 LTACs) underwent point-prevalence screening between September 2016–April 2017 for MRSA, VRE, ESBL, and CRE using nares, skin (axilla/groin), and peri-rectal swabs. In NHs and LTACs, residents were randomly selected until 50 sets of swabs were obtained. Swabbing in hospitals involved all patients in contact precautions. An additional set of swabs were also performed for all LTAC admissions from November 2016–February 2017. Results The overall prevalence of any MDRO among patients was 64% (44%–88%) in NHs, 80% (range 72%–86%) in LTACs, and 64% (54–84%) in hospitals (contact precaution patients) (Table 1). Only 25%, 64%, and 81% of patients were already known to harbor an MDRO in NHs, LTACs, and hospitals, respectively. Known MDRO patients also harbored another MDRO 49%, 63%, and 34% of the time for NHs, LTACs, and hospitals, respectively. In LTACs, MDRO point prevalence was 38% higher than the usual admission prevalence (65% higher for MRSA, 34% higher for VRE, 95% higher for ESBL, and 50% higher for CRE). Conclusion MDRO carriage in highly inter-connected NHs and LTACs was widespread, rivaling that found in hospitalized patients on contact precautions. MRSA, VRE, and ESBL carriage far outnumbered CRE carriage. A history of MDRO was insensitive for identifying MDRO carriers, and many patients carried multiple MDROs. The extensive MDRO burden and transmission in long-term care settings suggests that regional MDRO prevention efforts must include MDRO control in long-term care facilities. Disclosures R. D. Singh, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. A. McKinnell, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. G. Miller, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; K. Kleinman, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. Heim, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. D. Dutciuc, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. Estevez, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; G. Gussin, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L’Oreal: Consultant, Consulting fee; J. Chang, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; E. M. Peterson, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; B. Y. Lee, GSK: Consultant, Consulting fee; R. A. Weinstein, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; OpGen Company: Study support, Provided services at no charge; M. K. Hayden, Sage Products: Receipt of contributed product, Sage is contributing product to healthcare facilities participating in a regional collaborative on which I am a co-investigator. Neither I nor my hospital receive product.; Clorox: Receipt of contributed product, Research support; CDC: Grant Investigator and Receipt of contributed product, Research grant; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; OpGen Company: Study support, Provided services at no charge for studies; S. K. Gohil, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. Park, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. Tam, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. Saavedra, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. Yamaguchi, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; H. Custodio, Xttrium Laboratories: Study coordination, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Study coordination, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Study coordination, Conducting studies in healthcare facilities that are receiving contributed product; J. Nguyen, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. Tjoa, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. He, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. H. Coady, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. Platt, Sage Products: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; Clorox: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; S. S. Huang, Sage Products: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Clorox: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; 3M: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Molnlycke: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product
- Published
- 2017
24. Cost-effectiveness of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) testing and isolation strategies in nursing homes
- Author
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Bartsch, Sarah M., primary, Weatherwax, Colleen, additional, Martinez, Marie F., additional, Chin, Kevin L., additional, Wasserman, Michael R., additional, Singh, Raveena D., additional, Heneghan, Jessie L., additional, Gussin, Gabrielle M., additional, Scannell, Sheryl A., additional, White, Cameron, additional, Leff, Bruce, additional, Huang, Susan S., additional, and Lee, Bruce Y., additional
- Published
- 2024
- Full Text
- View/download PDF
25. Impact of Delays between Clinical and Laboratory Standards Institute and Food and Drug Administration Revisions of Interpretive Criteria for Carbapenem-Resistant Enterobacteriaceae.
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Bartsch, Sarah M, Huang, Susan S, Wong, Kim F, Slayton, Rachel B, McKinnell, James A, Sahm, Daniel F, Kazmierczak, Krystyna, Mueller, Leslie E, Jernigan, John A, and Lee, Bruce Y
- Subjects
Humans ,Enterobacteriaceae ,Enterobacteriaceae Infections ,Carbapenems ,Anti-Bacterial Agents ,Microbial Sensitivity Tests ,Carrier State ,Infection Control ,beta-Lactam Resistance ,Time ,United States Government Agencies ,United States ,Disease Transmission ,Infectious ,Clinical Laboratory Services ,Disease Transmission ,Infectious ,Microbiology ,Biological Sciences ,Agricultural and Veterinary Sciences ,Medical and Health Sciences - Abstract
Delays often occur between CLSI and FDA revisions of antimicrobial interpretive criteria. Using our Regional Healthcare Ecosystem Analyst (RHEA) simulation model, we found that the 32-month delay in changing carbapenem-resistant Enterobacteriaceae (CRE) breakpoints might have resulted in 1,821 additional carriers in Orange County, CA, an outcome that could have been avoided by identifying CRE and initiating contact precautions. Policy makers should aim to minimize the delay in the adoption of new breakpoints for antimicrobials against emerging pathogens when containment of spread is paramount; delays of
- Published
- 2016
26. Process Evaluation and Lessons Learned from Engaging Local Policymakers in the B'More Healthy Communities for Kids Trial
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Nam, Cyd S., Ross, Alexandra, Ruggiero, Cara, Ferguson, Marie, Mui, Yeeli, Lee, Bruce Y., and Gittelsohn, Joel
- Abstract
Partnerships linking researchers to the policymaking process can be effective in increasing communication and supporting health policy. However, these policy partnerships rarely conduct process evaluation. The Policy Working Group (Policy WG) was the policy-level intervention of the multilevel B'More Healthy Communities for Kids (BHCK) trial. The group sought to align interests of local policymakers, inform local food and nutrition policy, introduce policymakers to a new simulation modeling, and sustain intervention levels of BHCK. We conducted an evaluation on the Policy WG between July 2013 and May 2016. We evaluated process indicators for reach, dose-delivered, and fidelity and developed a SWOT (strengths, weaknesses, opportunities, and threats) analysis. The policy intervention was implemented with high reach and dose-delivered. Fidelity measures improved from moderate to nearly high over time. The number of health-related issues on policymakers' agenda increased from 50% in the first 2 years to 150% of the high standard in Year 3. SWOT analysis integrated a stakeholder feedback survey to consider areas of strength, weakness, opportunity, and threats. Although the fidelity of the modeling was low at 37% of the high standard, stakeholders indicated that the simulation modeling should be a primary purpose for policy intervention. Results demonstrate that process evaluation and SWOT analysis is useful for tracking the progress of policy interventions in multilevel trials and can be used to monitor the progress of building partnerships with policymakers.
- Published
- 2019
- Full Text
- View/download PDF
27. Beyond the Intensive Care Unit (ICU): Countywide Impact of Universal ICU Staphylococcus aureus Decolonization
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Lee, Bruce Y, Bartsch, Sarah M, Wong, Kim F, McKinnell, James A, Cui, Eric, Cao, Chenghua, Kim, Diane S, Miller, Loren G, and Huang, Susan S
- Subjects
Health Services ,Clinical Research ,Antimicrobial Resistance ,Emerging Infectious Diseases ,Prevention ,Infectious Diseases ,Infection ,Good Health and Well Being ,Adult ,Anti-Infective Agents ,Beds ,California ,Chlorhexidine ,Computer Simulation ,Cross Infection ,Disinfection ,Humans ,Infection Control ,Intensive Care Units ,Methicillin-Resistant Staphylococcus aureus ,Mupirocin ,Staphylococcal Infections ,decolonization ,hospitals ,intensive care unit ,MRSA ,MSSA ,nursing homes ,Mathematical Sciences ,Medical and Health Sciences ,Epidemiology - Abstract
A recent trial showed that universal decolonization in adult intensive care units (ICUs) resulted in greater reductions in all bloodstream infections and clinical isolates of methicillin-resistant Staphylococcus aureus (MRSA) than either targeted decolonization or screening and isolation. Since regional health-care facilities are highly interconnected through patient-sharing, focusing on individual ICUs may miss the broader impact of decolonization. Using our Regional Healthcare Ecosystem Analyst simulation model of all health-care facilities in Orange County, California, we evaluated the impact of chlorhexidine baths and mupirocin on all ICU admissions when universal decolonization was implemented for 25%, 50%, 75%, and 100% of ICU beds countywide (compared with screening and contact precautions). Direct benefits were substantial in ICUs implementing decolonization (a median 60% relative reduction in MRSA prevalence). When 100% of countywide ICU beds were decolonized, there were spillover effects in general wards, long-term acute-care facilities, and nursing homes resulting in median 8.0%, 3.0%, and 1.9% relative MRSA reductions at 1 year, respectively. MRSA prevalence decreased by a relative 3.2% countywide, with similar effects for methicillin-susceptible S. aureus. We showed that a large proportion of decolonization's benefits are missed when accounting only for ICU impact. Approximately 70% of the countywide cases of MRSA carriage averted after 1 year of universal ICU decolonization were outside the ICU.
- Published
- 2016
28. The Potential Trajectory of Carbapenem-Resistant Enterobacteriaceae, an Emerging Threat to Health-Care Facilities, and the Impact of the Centers for Disease Control and Prevention Toolkit
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Lee, Bruce Y, Bartsch, Sarah M, Wong, Kim F, McKinnell, James A, Slayton, Rachel B, Miller, Loren G, Cao, Chenghua, Kim, Diane S, Kallen, Alexander J, Jernigan, John A, and Huang, Susan S
- Subjects
Prevention ,Antimicrobial Resistance ,Clinical Research ,Infectious Diseases ,Emerging Infectious Diseases ,Infection ,Good Health and Well Being ,California ,Carbapenems ,Centers for Disease Control and Prevention ,U.S. ,Computer Simulation ,Cross Infection ,Drug Resistance ,Bacterial ,Enterobacteriaceae ,Enterobacteriaceae Infections ,Forecasting ,Health Facilities ,Hospitalization ,Humans ,Infection Control ,Models ,Theoretical ,Population Surveillance ,Prevalence ,United States ,carbapenem-resistant Enterobacteriaceae ,control measures ,coordinated responses ,regional spread ,surveillance ,Mathematical Sciences ,Medical and Health Sciences ,Epidemiology - Abstract
Carbapenem-resistant Enterobacteriaceae (CRE), a group of pathogens resistant to most antibiotics and associated with high mortality, are a rising emerging public health threat. Current approaches to infection control and prevention have not been adequate to prevent spread. An important but unproven approach is to have hospitals in a region coordinate surveillance and infection control measures. Using our Regional Healthcare Ecosystem Analyst (RHEA) simulation model and detailed Orange County, California, patient-level data on adult inpatient hospital and nursing home admissions (2011-2012), we simulated the spread of CRE throughout Orange County health-care facilities under 3 scenarios: no specific control measures, facility-level infection control efforts (uncoordinated control measures), and a coordinated regional effort. Aggressive uncoordinated and coordinated approaches were highly similar, averting 2,976 and 2,789 CRE transmission events, respectively (72.2% and 77.0% of transmission events), by year 5. With moderate control measures, coordinated regional control resulted in 21.3% more averted cases (n = 408) than did uncoordinated control at year 5. Our model suggests that without increased infection control approaches, CRE would become endemic in nearly all Orange County health-care facilities within 10 years. While implementing the interventions in the Centers for Disease Control and Prevention's CRE toolkit would not completely stop the spread of CRE, it would cut its spread substantially, by half.
- Published
- 2016
29. Can following formula-feeding recommendations still result in infants who are overweight or have obesity?
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Ferguson, Marie C., O’Shea, Kelly J., Hammer, Lawrence D., Hertenstein, Daniel L., Syed, Rafay M., Nyathi, Sindiso, Gonzales, Mario Solano, Domino, Molly, S. Siegmund, Sheryl, Randall, Samuel, Wedlock, Patrick, Adam, Atif, and Lee, Bruce Y.
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- 2020
- Full Text
- View/download PDF
30. Health state utilities associated with post-surgical Staphylococcus aureus infections
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Matza, Louis S., Kim, Katherine J., Yu, Holly, Belden, Katherine A., Chen, Antonia F., Kurd, Mark, Lee, Bruce Y., and Webb, Jason
- Published
- 2019
31. Process Evaluation and Lessons Learned From Engaging Local Policymakers in the B’More Healthy Communities for Kids Trial
- Author
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Nam, Cyd S., Ross, Alexandra, Ruggiero, Cara, Ferguson, Marie, Mui, Yeeli, Lee, Bruce Y., and Gittelsohn, Joel
- Published
- 2019
32. Quantifying the Exposure to Antibiotic-Resistant Pathogens Among Patients Discharged From a Single Hospital Across All California Healthcare Facilities
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Datta, Rupak, Brown, Shawn, Nguyen, Vinh Q, Cao, Chenghua, Billimek, John, Avery, Taliser, Lee, Bruce Y, and Huang, Susan S
- Subjects
Medical Microbiology ,Biomedical and Clinical Sciences ,Clinical Sciences ,Biodefense ,Clinical Research ,Antimicrobial Resistance ,Vaccine Related ,Health Services ,Emerging Infectious Diseases ,Patient Safety ,Prevention ,Infectious Diseases ,Aetiology ,2.2 Factors relating to the physical environment ,Infection ,Adolescent ,Adult ,Aged ,Aged ,80 and over ,Anti-Bacterial Agents ,California ,Carrier State ,Clostridium ,Cross Infection ,Drug Resistance ,Bacterial ,Female ,Hospitals ,Humans ,Klebsiella pneumoniae ,Length of Stay ,Male ,Methicillin-Resistant Staphylococcus aureus ,Middle Aged ,Nursing Homes ,Patient Discharge ,Patient Readmission ,Retrospective Studies ,Vancomycin-Resistant Enterococci ,Young Adult ,Medical and Health Sciences ,Epidemiology ,Biomedical and clinical sciences ,Health sciences - Abstract
ObjectiveTo assess the time-dependent exposure of California healthcare facilities to patients harboring methicillin-resistant Staphylococcus aureus (MRSA), vancomycin-resistant enterococci (VRE), extended-spectrum β-lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae, and Clostridium difficile infection (CDI) upon discharge from 1 hospital.MethodsRetrospective multiple-cohort study of adults discharged from 1 hospital in 2005-2009, counting hospitals, nursing homes, cities, and counties in which carriers were readmitted, and comparing the number and length of stay of readmissions and the number of distinct readmission facilities among carriers versus noncarriers.ResultsWe evaluated 45,772 inpatients including those with MRSA (N=1,198), VRE (N=547), ESBL (N=121), and CDI (N=300). Within 1 year of discharge, MRSA, VRE, and ESBL carriers exposed 137, 117, and 45 hospitals and 103, 83, and 37 nursing homes, generating 58,804, 33,486, and 15,508 total exposure-days, respectively. Within 90 days of discharge, CDI patients exposed 36 hospitals and 35 nursing homes, generating 7,318 total exposure-days. Compared with noncarriers, carriers had more readmissions to hospitals (MRSA:1.8 vs 0.9/patient; VRE: 2.6 vs 0.9; ESBL: 2.3 vs 0.9; CDI: 0.8 vs 0.4; all P
- Published
- 2015
33. Vital Signs: Estimated Effects of a Coordinated Approach for Action to Reduce Antibiotic-Resistant Infections in Health Care Facilities - United States.
- Author
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Slayton, Rachel B, Toth, Damon, Lee, Bruce Y, Tanner, Windy, Bartsch, Sarah M, Khader, Karim, Wong, Kim, Brown, Kevin, McKinnell, James A, Ray, William, Miller, Loren G, Rubin, Michael, Kim, Diane S, Adler, Fred, Cao, Chenghua, Avery, Lacey, Stone, Nathan TB, Kallen, Alexander, Samore, Matthew, Huang, Susan S, Fridkin, Scott, and Jernigan, John A
- Subjects
Prevention ,Biodefense ,Health Services ,Emerging Infectious Diseases ,Infectious Diseases ,Clinical Research ,Vaccine Related ,Antimicrobial Resistance ,Aetiology ,2.2 Factors relating to the physical environment ,Infection ,Good Health and Well Being ,Anti-Bacterial Agents ,Bacteria ,Bacterial Infections ,Clostridioides difficile ,Cross Infection ,Drug Resistance ,Bacterial ,Health Facilities ,Humans ,United States ,Clostridium difficile ,General & Internal Medicine - Abstract
BackgroundTreatments for health care-associated infections (HAIs) caused by antibiotic-resistant bacteria and Clostridium difficile are limited, and some patients have developed untreatable infections. Evidence-supported interventions are available, but coordinated approaches to interrupt the spread of HAIs could have a greater impact on reversing the increasing incidence of these infections than independent facility-based program efforts.MethodsData from CDC's National Healthcare Safety Network and Emerging Infections Program were analyzed to project the number of health care-associated infections from antibiotic-resistant bacteria or C. difficile both with and without a large scale national intervention that would include interrupting transmission and improved antibiotic stewardship. As an example, the impact of reducing transmission of one antibiotic-resistant infection (carbapenem-resistant Enterobacteriaceae [CRE]) on cumulative prevalence and number of HAI transmission events within interconnected groups of health care facilities was modeled using two distinct approaches, a large scale and a smaller scale health care network.ResultsImmediate nationwide infection control and antibiotic stewardship interventions, over 5 years, could avert an estimated 619,000 HAIs resulting from CRE, multidrug-resistant Pseudomonas aeruginosa, invasive methicillin-resistant Staphylococcus aureus (MRSA), or C. difficile. Compared with independent efforts, a coordinated response to prevent CRE spread across a group of inter-connected health care facilities resulted in a cumulative 74% reduction in acquisitions over 5 years in a 10-facility network model, and 55% reduction over 15 years in a 102-facility network model.ConclusionsWith effective action now, more than half a million antibiotic-resistant health care-associated infections could be prevented over 5 years. Models representing both large and small groups of interconnected health care facilities illustrate that a coordinated approach to interrupting transmission is more effective than historical independent facilitybased efforts.Implications for public healthPublic health-led coordinated prevention approaches have the potential to more completely address the emergence and dissemination of these antibiotic-resistant organisms and C. difficile than independent facility-based efforts.
- Published
- 2015
34. Reply to O’Riordan et al
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McKinnell, James A, Bartsch, Sarah M, Lee, Bruce Y, Huang, Susan S, and Miller, Loren G
- Subjects
Biomedical and Clinical Sciences ,Health Sciences ,Carrier State ,Hospital Costs ,Humans ,Infection Control ,Mass Screening ,Methicillin-Resistant Staphylococcus aureus ,Staphylococcal Infections ,Medical and Health Sciences ,Epidemiology ,Biomedical and clinical sciences ,Health sciences - Published
- 2015
35. Cost-benefit analysis from the hospital perspective of universal active screening followed by contact precautions for methicillin-resistant Staphylococcus aureus carriers.
- Author
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McKinnell, James A, Bartsch, Sarah M, Lee, Bruce Y, Huang, Susan S, and Miller, Loren G
- Subjects
Nose ,Oropharynx ,Humans ,Staphylococcal Infections ,Cross Infection ,Mass Screening ,Colony Count ,Microbial ,Polymerase Chain Reaction ,Carrier State ,Infection Control ,Cost-Benefit Analysis ,Hospital Costs ,Methicillin-Resistant Staphylococcus aureus ,Epidemiology ,Medical and Health Sciences - Abstract
OBJECTIVE To explore the economic impact to a hospital of universal methicillin-resistant Staphylococcus aureus (MRSA) screening. METHODS We used a decision tree model to estimate the direct economic impact to an individual hospital of starting universal MRSA screening and contact precautions. Projected costs and benefits were based on literature-derived data. Our model examined outcomes of several strategies including non-nares MRSA screening and comparison of culture versus polymerase chain reaction-based screening. RESULTS Under baseline conditions, the costs of universal MRSA screening and contact precautions outweighed the projected benefits generated by preventing MRSA-related infections, resulting in economic costs of $104,000 per 10,000 admissions (95% CI, $83,000-$126,000). Cost-savings occurred only when the model used estimates at the extremes of our key parameters. Non-nares screening and polymerase chain reaction-based testing, both of which identified more MRSA-colonized persons, resulted in more MRSA infections averted but increased economic costs of the screening program. CONCLUSIONS We found that universal MRSA screening, although providing potential benefit in preventing MRSA infection, is relatively costly and may be economically burdensome for a hospital. Policy makers should consider the economic burden of MRSA screening and contact precautions in relation to other interventions when choosing programs to improve patient safety and outcomes.
- Published
- 2015
36. The Spread and Control of Norovirus Outbreaks Among Hospitals in a Region: A Simulation Model
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Bartsch, Sarah M, Huang, Susan S, Wong, Kim F, Avery, Taliser R, and Lee, Bruce Y
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Emerging Infectious Diseases ,Infectious Diseases ,Foodborne Illness ,Good Health and Well Being ,hospitals ,intervention ,norovirus ,outbreak - Abstract
BackgroundBecause hospitals in a region are connected via patient sharing, a norovirus outbreak in one hospital may spread to others.MethodsWe utilized our Regional Healthcare Ecosystem Analyst software to generate an agent-based model of all the acute care facilities in Orange County (OC), California and simulated various norovirus outbreaks in different locations, both with and without contact precautions.ResultsAt the lower end of norovirus reproductive rate (R0) estimates (1.64), an outbreak tended to remain confined to the originating hospital (≤6.1% probability of spread). However, at the higher end of R0 (3.74), an outbreak spread 4.1%-17.5% of the time to almost all other OC hospitals within 30 days, regardless of the originating hospital. Implementing contact precautions for all symptomatic cases reduced the probability of spread to other hospitals within 30 days and the total number of cases countywide, but not the number of other hospitals seeing norovirus cases.ConclusionsA single norovirus outbreak can continue to percolate throughout a system of different hospitals for several months and appear as a series of unrelated outbreaks, highlighting the need for hospitals within a region to more aggressively and cooperatively track and control an initial outbreak.
- Published
- 2014
37. Application of group model building in implementation research: A systematic review of the public health and healthcare literature
- Author
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Estrada-Magbanua, Weanne Myrrh, primary, Huang, Terry T.-K., additional, Lounsbury, David W., additional, Zito, Priscila, additional, Iftikhar, Pulwasha, additional, El-Bassel, Nabila, additional, Gilbert, Louisa, additional, Wu, Elwin, additional, Lee, Bruce Y., additional, Mateu-Gelabert, Pedro, additional, and S. Sabounchi, Nasim, additional
- Published
- 2023
- Full Text
- View/download PDF
38. Complementary Paths to Chagas Disease Elimination : The Impact of Combining Vector Control With Etiological Treatment
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Cucunubá, Zulma M., Nouvellet, Pierre, Peterson, Jennifer K., Bartsch, Sarah M., Lee, Bruce Y., Dobson, Andrew P., and Basáñez, Maria-Gloria
- Published
- 2018
39. Simulation modeling to assist with childhood obesity control : perceptions of Baltimore City policymakers
- Author
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Seifu, Leah, Ruggiero, Cara, Ferguson, Marie, Mui, Yeeli, Lee, Bruce Y., and Gittelsohn, Joel
- Published
- 2018
40. Estimated Cost to a Restaurant of a Foodborne Illness Outbreak
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Bartsch, Sarah M., Asti, Lindsey, Nyathi, Sindiso, Spiker, Marie L., and Lee, Bruce Y.
- Published
- 2018
41. Modeling the regional spread and control of vancomycin-resistant enterococci
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Lee, Bruce Y, Yilmaz, S Levent, Wong, Kim F, Bartsch, Sarah M, Eubank, Stephen, Song, Yeohan, Avery, Taliser R, Christie, Richard, Brown, Shawn T, Epstein, Joshua M, Parker, Jon I, and Huang, Susan S
- Subjects
Health Services and Systems ,Biomedical and Clinical Sciences ,Clinical Sciences ,Health Sciences ,Clinical Research ,Emerging Infectious Diseases ,Patient Safety ,Good Health and Well Being ,Anti-Bacterial Agents ,California ,Computer Simulation ,Cross Infection ,Enterococcus ,Gram-Positive Bacterial Infections ,Hospitals ,Humans ,Infection Control ,Prevalence ,Vancomycin ,Vancomycin Resistance ,Vancomycin-resistant Enterococcus ,Health care-associated infections ,Modeling ,Simulation ,article ,bacterial colonization ,bacterial transmission ,disease surveillance ,emergency care ,infection control ,nonhuman ,United States ,vancomycin resistant Enterococcus ,Nursing ,Public Health and Health Services ,Epidemiology ,Clinical sciences ,Public health - Abstract
BackgroundBecause patients can remain colonized with vancomycin-resistant enterococci (VRE) for long periods of time, VRE may spread from one health care facility to another.MethodsUsing the Regional Healthcare Ecosystem Analyst, an agent-based model of patient flow among all Orange County, California, hospitals and communities, we quantified the degree and speed at which changes in VRE colonization prevalence in a hospital may affect prevalence in other Orange County hospitals.ResultsA sustained 10% increase in VRE colonization prevalence in any 1 hospital caused a 2.8% (none to 62%) average relative increase in VRE prevalence in all other hospitals. Effects took from 1.5 to >10 years to fully manifest. Larger hospitals tended to have greater affect on other hospitals.ConclusionsWhen monitoring and controlling VRE, decision makers may want to account for regional effects. Knowing a hospital's connections with other health care facilities via patient sharing can help determine which hospitals to include in a surveillance or control program.
- Published
- 2013
42. Reply to Crnich and Drinka
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Lee, Bruce Y, Bartsch, Sarah M, and Huang, Susan S
- Subjects
Biomedical and Clinical Sciences ,Health Sciences ,Cross Infection ,Disease Outbreaks ,Humans ,Methicillin-Resistant Staphylococcus aureus ,Nursing Homes ,Staphylococcal Infections ,bacterial transmission ,epidemic ,glove ,hospital management ,hospitalization ,human ,infection prevention ,information processing ,letter ,methicillin resistant Staphylococcus aureus infection ,nonhuman ,nursing home ,practice guideline ,simulation ,Medical and Health Sciences ,Epidemiology ,Biomedical and clinical sciences ,Health sciences - Published
- 2013
43. The Regional Healthcare Ecosystem Analyst (RHEA): a simulation modeling tool to assist infectious disease control in a health system
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Lee, Bruce Y, Wong, Kim F, Bartsch, Sarah M, Yilmaz, S Levent, Avery, Taliser R, Brown, Shawn T, Song, Yeohan, Singh, Ashima, Kim, Diane S, and Huang, Susan S
- Subjects
Biomedical and Clinical Sciences ,Clinical Sciences ,Bioengineering ,Infectious Diseases ,Emerging Infectious Diseases ,Infection ,Good Health and Well Being ,California ,Computer Simulation ,Delivery of Health Care ,Hospital Administration ,Humans ,Infection Control ,Software ,Healthcare System ,Hospital Acquired Infections ,Hospitals ,Patient Sharing ,article ,computer program ,disease simulation ,disease transmission ,ethnicity ,health care facility ,health care policy ,health care system ,hospital bed capacity ,hospital readmission ,human ,infection ,infection control ,insurance ,intensive care unit ,length of stay ,methicillin resistant Staphylococcus aureus ,morbidity ,prevalence ,probability ,regional healthcare ecosystem analyst ,social status ,theoretical model ,computer simulation ,health care delivery ,hospital ,hospital management ,methodology ,organization and management ,United States ,Information and Computing Sciences ,Engineering ,Medical and Health Sciences ,Medical Informatics ,Biomedical and clinical sciences ,Health sciences ,Information and computing sciences - Abstract
ObjectiveAs healthcare systems continue to expand and interconnect with each other through patient sharing, administrators, policy makers, infection control specialists, and other decision makers may have to take account of the entire healthcare 'ecosystem' in infection control.Materials and methodsWe developed a software tool, the Regional Healthcare Ecosystem Analyst (RHEA), that can accept user-inputted data to rapidly create a detailed agent-based simulation model (ABM) of the healthcare ecosystem (ie, all healthcare facilities, their adjoining community, and patient flow among the facilities) of any region to better understand the spread and control of infectious diseases.ResultsTo demonstrate RHEA's capabilities, we fed extensive data from Orange County, California, USA, into RHEA to create an ABM of a healthcare ecosystem and simulate the spread and control of methicillin-resistant Staphylococcus aureus. Various experiments explored the effects of changing different parameters (eg, degree of transmission, length of stay, and bed capacity).DiscussionOur model emphasizes how individual healthcare facilities are components of integrated and dynamic networks connected via patient movement and how occurrences in one healthcare facility may affect many other healthcare facilities.ConclusionsA decision maker can utilize RHEA to generate a detailed ABM of any healthcare system of interest, which in turn can serve as a virtual laboratory to test different policies and interventions.
- Published
- 2013
44. The Importance of Nursing Homes in the Spread of Methicillin-resistant Staphylococcus aureus (MRSA) Among Hospitals
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Lee, Bruce Y, Bartsch, Sarah M, Wong, Kim F, Singh, Ashima, Avery, Taliser R, Kim, Diane S, Brown, Shawn T, Murphy, Courtney R, Yilmaz, Server Levent, Potter, Margaret A, and Huang, Susan S
- Subjects
Health Services and Systems ,Nursing ,Health Sciences ,Clinical Research ,Infectious Diseases ,Antimicrobial Resistance ,Health Services ,Emerging Infectious Diseases ,Infection ,Good Health and Well Being ,Adult ,California ,Cross Infection ,Disease Outbreaks ,Health Facility Size ,Hospitals ,Humans ,Infection Control ,Interinstitutional Relations ,Methicillin-Resistant Staphylococcus aureus ,Nursing Homes ,Patient Transfer ,Prevalence ,Staphylococcal Infections ,MRSA ,outbreak ,long-term care ,nursing homes ,hospitals ,article ,disease transmission ,epidemic ,health care facility ,hospital infection ,human ,methicillin resistant Staphylococcus aureus infection ,nursing home ,patient transport ,prevalence ,priority journal ,United States ,Public Health and Health Services ,Applied Economics ,Health Policy & Services ,Applied economics ,Health services and systems ,Policy and administration - Abstract
BackgroundHospital infection control strategies and programs may not consider control of methicillin-resistant Staphylococcus aureus (MRSA) in nursing homes in a county.MethodsUsing our Regional Healthcare Ecosystem Analyst, we augmented our existing agent-based model of all hospitals in Orange County (OC), California, by adding all nursing homes and then simulated MRSA outbreaks in various health care facilities.ResultsThe addition of nursing homes substantially changed MRSA transmission dynamics throughout the county. The presence of nursing homes substantially potentiated the effects of hospital outbreaks on other hospitals, leading to an average 46.2% (range, 3.3%-156.1%) relative increase above and beyond the impact when only hospitals are included for an outbreak in OC's largest hospital. An outbreak in the largest hospital affected all other hospitals (average 2.1% relative prevalence increase) and the majority (~90%) of nursing homes (average 3.2% relative increase) after 6 months. An outbreak in the largest nursing home had effects on multiple OC hospitals, increasing MRSA prevalence in directly connected hospitals by an average 0.3% and in hospitals not directly connected through patient transfers by an average 0.1% after 6 months. A nursing home outbreak also had some effect on MRSA prevalence in other nursing homes.ConclusionsNursing homes, even those not connected by direct patient transfers, may be a vital component of a hospital's infection control strategy. To achieve effective control, a hospital may want to better understand how regional nursing homes and hospitals are connected through both direct and indirect (with intervening stays at home) patient sharing.
- Published
- 2013
45. Predicting high prevalence of community methicillin-resistant Staphylococcus aureus strains in nursing homes.
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Murphy, Courtney R, Hudson, Lyndsey O, Spratt, Brian G, Quan, Victor, Kim, Diane, Peterson, Ellena, Tan, Grace, Evans, Kaye, Meyers, Hildy, Cheung, Michele, Lee, Bruce Y, Mukamel, Dana B, Enright, Mark C, Whealon, Matthew, and Huang, Susan S
- Subjects
Nose ,Humans ,Staphylococcal Infections ,Community-Acquired Infections ,Prevalence ,Multivariate Analysis ,Odds Ratio ,Carrier State ,Age Factors ,Aged ,Middle Aged ,Hispanic Americans ,Nursing Homes ,California ,Female ,Male ,Methicillin-Resistant Staphylococcus aureus ,staphylococcus protein A ,adolescent ,adult ,article ,bacterium identification ,child ,community associated methicillin resistant Staphylococcus aureus ,comorbidity ,DNA extraction ,female ,health care utilization ,human ,infant ,male ,methicillin resistant Staphylococcus aureus ,molecular typing ,multicenter study ,nonhuman ,nursing home patient ,prevalence ,scoring system ,screening ,Medical and Health Sciences ,Epidemiology - Abstract
We assessed characteristics associated with community-associated methicillin-resistant Staphylococcus aureus (CA-MRSA) carriage among residents of 22 nursing homes. Of MRSA-positive swabs, 25% (208/824) were positive for CA-MRSA. Median facility CA-MRSA percentage was 22% (range, 0%-44%). In multivariate models, carriage was associated with age less than 65 years (odds ratio, 1.2; P
- Published
- 2013
46. The Potential Regional Impact of Contact Precaution Use in Nursing Homes to Control Methicillin-Resistant Staphylococcus aureus
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Lee, Bruce Y, Singh, Ashima, Bartsch, Sarah M, Wong, Kim F, Kim, Diane S, Avery, Taliser R, Brown, Shawn T, Murphy, Courtney R, Yilmaz, S Levent, and Huang, Susan S
- Subjects
Biomedical and Clinical Sciences ,Clinical Sciences ,Prevention ,Patient Safety ,Antimicrobial Resistance ,Emerging Infectious Diseases ,Infectious Diseases ,Clinical Research ,Health Services ,Infection ,California ,Cross Infection ,Disease Outbreaks ,Hospitals ,Humans ,Methicillin-Resistant Staphylococcus aureus ,Models ,Theoretical ,Nursing Homes ,Staphylococcal Infections ,article ,disease surveillance ,disease transmission ,health care facility ,human ,infection control ,length of stay ,methicillin resistant Staphylococcus aureus ,methicillin resistant Staphylococcus aureus infection ,nursing home ,prevalence ,sensitivity analysis ,Medical and Health Sciences ,Epidemiology ,Biomedical and clinical sciences ,Health sciences - Abstract
ObjectiveImplementation of contact precautions in nursing homes to prevent methicillin-resistant Staphylococcus aureus (MRSA) transmission could cost time and effort and may have wide-ranging effects throughout multiple health facilities. Computational modeling could forecast the potential effects and guide policy making.DesignOur multihospital computational agent-based model, Regional Healthcare Ecosystem Analyst (RHEA).SettingAll hospitals and nursing homes in Orange County, California.MethodsOur simulation model compared the following 3 contact precaution strategies: (1) no contact precautions applied to any nursing home residents, (2) contact precautions applied to those with clinically apparent MRSA infections, and (3) contact precautions applied to all known MRSA carriers as determined by MRSA screening performed by hospitals.ResultsOur model demonstrated that contact precautions for patients with clinically apparent MRSA infections in nursing homes resulted in a median 0.4% (range, 0%-1.6%) relative decrease in MRSA prevalence in nursing homes (with 50% adherence) but had no effect on hospital MRSA prevalence, even 5 years after initiation. Implementation of contact precautions (with 50% adherence) in nursing homes for all known MRSA carriers was associated with a median 14.2% (range, 2.1%-21.8%) relative decrease in MRSA prevalence in nursing homes and a 2.3% decrease (range, 0%-7.1%) in hospitals 1 year after implementation. Benefits accrued over time and increased with increasing compliance.ConclusionsOur modeling study demonstrated the substantial benefits of extending contact precautions in nursing homes from just those residents with clinically apparent infection to all MRSA carriers, which suggests the benefits of hospitals and nursing homes sharing and coordinating information on MRSA surveillance and carriage status.
- Published
- 2013
47. Geotemporal Analysis ofNeisseria meningitidis Clones in the United States: 2000–2005
- Author
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Wiringa, Ann E, Shutt, Kathleen A, Marsh, Jane W, Cohn, Amanda C, Messonnier, Nancy E, Zansky, Shelley M, Petit, Susan, Farley, Monica M, Gershman, Ken, Lynfield, Ruth, Reingold, Arthur, Schaffner, William, Thompson, Jamie, Brown, Shawn T, Lee, Bruce Y, and Harrison, Lee H
- Subjects
Microbiology ,Biological Sciences ,Biomedical and Clinical Sciences ,Immunization ,Vaccine Related ,Prevention ,Aetiology ,2.2 Factors relating to the physical environment ,Infection ,Bacterial Outer Membrane Proteins ,Clone Cells ,Epidemiological Monitoring ,Gene Expression ,Humans ,Meningococcal Infections ,Multilocus Sequence Typing ,Neisseria meningitidis ,Retrospective Studies ,Serotyping ,Spatio-Temporal Analysis ,United States ,General Science & Technology - Abstract
BackgroundThe detection of meningococcal outbreaks relies on serogrouping and epidemiologic definitions. Advances in molecular epidemiology have improved the ability to distinguish unique Neisseria meningitidis strains, enabling the classification of isolates into clones. Around 98% of meningococcal cases in the United States are believed to be sporadic.MethodsMeningococcal isolates from 9 Active Bacterial Core surveillance sites throughout the United States from 2000 through 2005 were classified according to serogroup, multilocus sequence typing, and outer membrane protein (porA, porB, and fetA) genotyping. Clones were defined as isolates that were indistinguishable according to this characterization. Case data were aggregated to the census tract level and all non-singleton clones were assessed for non-random spatial and temporal clustering using retrospective space-time analyses with a discrete Poisson probability model.ResultsAmong 1,062 geocoded cases with available isolates, 438 unique clones were identified, 78 of which had ≥2 isolates. 702 cases were attributable to non-singleton clones, accounting for 66.0% of all geocoded cases. 32 statistically significant clusters comprised of 107 cases (10.1% of all geocoded cases) were identified. Clusters had the following attributes: included 2 to 11 cases; 1 day to 33 months duration; radius of 0 to 61.7 km; and attack rate of 0.7 to 57.8 cases per 100,000 population. Serogroups represented among the clusters were: B (n = 12 clusters, 45 cases), C (n = 11 clusters, 27 cases), and Y (n = 9 clusters, 35 cases); 20 clusters (62.5%) were caused by serogroups represented in meningococcal vaccines that are commercially available in the United States.ConclusionsAround 10% of meningococcal disease cases in the U.S. could be assigned to a geotemporal cluster. Molecular characterization of isolates, combined with geotemporal analysis, is a useful tool for understanding the spread of virulent meningococcal clones and patterns of transmission in populations.
- Published
- 2013
48. Geotemporal analysis of Neisseria meningitidis clones in the United States: 2000-2005.
- Author
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Wiringa, Ann E, Shutt, Kathleen A, Marsh, Jane W, Cohn, Amanda C, Messonnier, Nancy E, Zansky, Shelley M, Petit, Susan, Farley, Monica M, Gershman, Ken, Lynfield, Ruth, Reingold, Arthur, Schaffner, William, Thompson, Jamie, Brown, Shawn T, Lee, Bruce Y, and Harrison, Lee H
- Subjects
Clone Cells ,Humans ,Neisseria meningitidis ,Meningococcal Infections ,Bacterial Outer Membrane Proteins ,Serotyping ,Retrospective Studies ,Gene Expression ,United States ,Multilocus Sequence Typing ,Epidemiological Monitoring ,Spatio-Temporal Analysis ,General Science & Technology - Abstract
BackgroundThe detection of meningococcal outbreaks relies on serogrouping and epidemiologic definitions. Advances in molecular epidemiology have improved the ability to distinguish unique Neisseria meningitidis strains, enabling the classification of isolates into clones. Around 98% of meningococcal cases in the United States are believed to be sporadic.MethodsMeningococcal isolates from 9 Active Bacterial Core surveillance sites throughout the United States from 2000 through 2005 were classified according to serogroup, multilocus sequence typing, and outer membrane protein (porA, porB, and fetA) genotyping. Clones were defined as isolates that were indistinguishable according to this characterization. Case data were aggregated to the census tract level and all non-singleton clones were assessed for non-random spatial and temporal clustering using retrospective space-time analyses with a discrete Poisson probability model.ResultsAmong 1,062 geocoded cases with available isolates, 438 unique clones were identified, 78 of which had ≥2 isolates. 702 cases were attributable to non-singleton clones, accounting for 66.0% of all geocoded cases. 32 statistically significant clusters comprised of 107 cases (10.1% of all geocoded cases) were identified. Clusters had the following attributes: included 2 to 11 cases; 1 day to 33 months duration; radius of 0 to 61.7 km; and attack rate of 0.7 to 57.8 cases per 100,000 population. Serogroups represented among the clusters were: B (n = 12 clusters, 45 cases), C (n = 11 clusters, 27 cases), and Y (n = 9 clusters, 35 cases); 20 clusters (62.5%) were caused by serogroups represented in meningococcal vaccines that are commercially available in the United States.ConclusionsAround 10% of meningococcal disease cases in the U.S. could be assigned to a geotemporal cluster. Molecular characterization of isolates, combined with geotemporal analysis, is a useful tool for understanding the spread of virulent meningococcal clones and patterns of transmission in populations.
- Published
- 2013
49. Nursing home characteristics associated with methicillin-resistant Staphylococcus aureus (MRSA) Burden and Transmission
- Author
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Murphy, Courtney R, Quan, Victor, Kim, Diane, Peterson, Ellena, Whealon, Matthew, Tan, Grace, Evans, Kaye, Meyers, Hildy, Cheung, Michele, Lee, Bruce Y, Mukamel, Dana B, and Huang, Susan S
- Abstract
Abstract Background MRSA prevalence in nursing homes often exceeds that in hospitals, but reasons for this are not well understood. We sought to measure MRSA burden in a large number of nursing homes and identify facility characteristics associated with high MRSA burden. Methods We performed nasal swabs of residents from 26 nursing homes to measure MRSA importation and point prevalence, and estimate transmission. Using nursing home administrative data, we identified facility characteristics associated with MRSA point prevalence and estimated transmission risk in multivariate models. Results We obtained 1,649 admission and 2,111 point prevalence swabs. Mean MRSA point prevalence was 24%, significantly higher than mean MRSA admission prevalence, 16%, (paired t-test, p
- Published
- 2012
50. Simulation Shows Hospitals That Cooperate On Infection Control Obtain Better Results Than Hospitals Acting Alone
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Lee, Bruce Y, Bartsch, Sarah M, Wong, Kim F, Yilmaz, S Levent, Avery, Taliser R, Singh, Ashima, Song, Yeohan, Kim, Diane S, Brown, Shawn T, Potter, Margaret A, Platt, Richard, and Huang, Susan S
- Subjects
Health Services and Systems ,Policy and Administration ,Health Sciences ,Human Society ,Emerging Infectious Diseases ,Infectious Diseases ,Antimicrobial Resistance ,Clinical Research ,Infection ,California ,Computer Simulation ,Cross Infection ,Hospital Shared Services ,Hospitals ,Humans ,Methicillin-Resistant Staphylococcus aureus ,Patient Transfer ,Staphylococcal Infections ,United States ,article ,bacterial strain ,clinical decision making ,computer simulation ,contact isolation ,controlled study ,disease surveillance ,disease transmission ,glove ,health care personnel ,hospital admission ,hospital management ,human ,infection control ,major clinical study ,methicillin resistant Staphylococcus aureus ,methicillin resistant Staphylococcus aureus infection ,multicenter study ,patient care ,prevalence ,surgical gown ,Public Health and Health Services ,Applied Economics ,Health Policy & Services ,Health services and systems ,Policy and administration - Abstract
Efforts to control life-threatening infections, such as with methicillin-resistant Staphylococcus aureus (MRSA), can be complicated when patients are transferred from one hospital to another. Using a detailed computer simulation model of all hospitals in Orange County, California, we explored the effects when combinations of hospitals tested all patients at admission for MRSA and adopted procedures to limit transmission among patients who tested positive. Called "contact isolation," these procedures specify precautions for health care workers interacting with an infected patient, such as wearing gloves and gowns. Our simulation demonstrated that each hospital's decision to test for MRSA and implement contact isolation procedures could affect the MRSA prevalence in all other hospitals. Thus, our study makes the case that further cooperation among hospitals--which is already reflected in a few limited collaborative infection control efforts under way--could help individual hospitals achieve better infection control than they could achieve on their own.
- Published
- 2012
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