The Experts below are selected from a list of 22686 Experts worldwide ranked by ideXlab platform
Vedat Verter - One of the best experts on this subject based on the ideXlab platform.
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the impact of client choice on preventive Healthcare Facility network design
OR Spectrum, 2012Co-Authors: Yue Zhang, Oded Berman, Vedat VerterAbstract:In contrast with sick people who need urgent medical attention, the clientele of preventive Healthcare have a choice in whether to participate in the programs offered in their region. In order to maximize the total participation to a preventive care program, it is important to incorporate how potential clients choose the facilities to patronize. We study the impact of client choice behavior on the configuration of a preventive care Facility network and the resulting level of participation. To this end, we present two alternative models: in the "probabilistic-choice model" a client may patronize each Facility with a certain probability, which increases with the attractiveness of the available facilities. In contrast, the "optimal-choice model" stipulates that each client will go to the most attractive Facility. In this paper, we assume that the proximity to a Facility is the only attractiveness attribute considered by clients. To ensure the quality of care, we impose a bound on the mean waiting time as well as a minimum workload requirement at each open Facility. Subject to a total capacity limit, the number of open facilities as well as the location and the capacity (number of servers) of each open Facility is the main determinant of the configuration of a Facility network. Both models are formulated as a mixed-integer program. To solve the problems efficiently, we propose a probabilistic search algorithm and a genetic algorithm. Finally, we use the models to analyze the network of mammography centers in Montreal.
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a bilevel model for preventive Healthcare Facility network design with congestion
Iie Transactions, 2010Co-Authors: Yue Zhang, Oded Berman, Patrice Marcotte, Vedat VerterAbstract:Preventive Healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The level of participation in preventive Healthcare programs is a critical determinant in terms of their effectiveness and efficiency. This article presents a methodology for designing a network of preventive Healthcare facilities so as to improve its accessibility to potential clients and thus maximize participation in preventive Healthcare programs. The problem is formulated as a mathematical program with equilibrium constraints; i.e., a bilevel non-linear optimization model. The lower level problem which determines the allocation of clients to facilities is formulated as a variational inequality; the upper level is a Facility location and capacity allocation problem. The developed solution approach is based on the location–allocation framework. The variational inequality is formulated as a convex optimization problem, which can be solved by the gradient project...
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incorporating congestion in preventive Healthcare Facility network design
European Journal of Operational Research, 2009Co-Authors: Yue Zhang, Oded Berman, Vedat VerterAbstract:Preventive Healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The level of participation to preventive Healthcare programs is a crucial factor in terms of their effectiveness and efficiency. This paper provides a methodology for designing a network of preventive Healthcare facilities so as to maximize participation. The number of facilities to be established and the location of each Facility are the main determinants of the configuration of a Healthcare Facility network. We use the total (travel, waiting and service) time required for receiving the preventive service as a proxy for accessibility of a Healthcare Facility, and assume that each client would seek the services of the Facility with minimum expected total time. At each Facility, which we model as an M/M/1 queue so as to capture the level of congestion, the expected number of participants from each population zone decreases with the expected total time. In order to ensure service quality, the facilities cannot be operated unless their level of activity exceeds a minimum workload requirement. The arising mathematical formulation is highly nonlinear, and hence we provide a heuristic solution framework for this problem. Four heuristics are compared in terms of accuracy and computational requirements. The most efficient heuristic is utilized in solving a real life problem that involves the breast cancer screening center network in Montreal. In the context of this case, we found out that centralizing the total system capacity at the locations preferred by clients is a more effective strategy than decentralization by the use of a larger number of smaller facilities. We also show that the proposed methodology can be used in making the investment trade-off between expanding the total system capacity and changing the behavior of potential clients toward preventive Healthcare programs by advertisement and education.
Bryan Boulanger - One of the best experts on this subject based on the ideXlab platform.
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concentrations and mass loadings of hormones alkylphenols and alkylphenol ethoxylates in Healthcare Facility wastewaters
Chemosphere, 2010Co-Authors: Pranav M. Nagarnaik, Marc A Mills, Bryan BoulangerAbstract:Abstract Healthcare Facility wastewaters are an anticipated source of known endocrine disrupting chemicals to the environment. In this study, the composition and magnitude of eight steroid hormones, octylphenol (OP), nonylphenol (NP), 16 nonylphenol ethoxylates (NPEOs), and 10 octylphenol ethoxylates (OPEOs) in wastewater from a(n) hospital, nursing Facility, assisted living Facility, and independent living Facility are presented. Steroid hormone concentrations were variable for each sampling location, ranging from a non-detectable concentration of 17β-ethynylestradiol in all samples to 127 ng L −1 androstenedione in the hospital’s wastewater composite. OP and NP were not detected in any site’s samples. However, NPEOs were found at each sampling location with a maximum combined concentration of 260 μg L −1 for NPEOs with a chain length between 3 and 18 units in the assisted living Facility composite sample. OPEOs were only found in the hospital and nursing facilities samples with a maximum combined OPEO concentration of 13 μg L −1 for OPEOs with a chain length between 2 and 12 units in hospital wastewater. The total mass loading of hormones to the municipal sewer system from each Facility ranged from 2.5 mg d –1 at the assisted living Facility to 138 mg d –1 at the hospital. The total mass loading of the alklyphenol ethoxylates (NPEO + OPEO) is considerably higher than the estimated hormone mass loadings, ranging from 1.8 g d –1 at the independent living Facility to 54 g d –1 at the hospital Facility.
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concentrations and mass loadings of hormones alkylphenols and alkylphenol ethoxylates in Healthcare Facility wastewaters
Chemosphere, 2010Co-Authors: Pranav M. Nagarnaik, Marc A Mills, Bryan BoulangerAbstract:Healthcare Facility wastewaters are an anticipated source of known endocrine disrupting chemicals to the environment. In this study, the composition and magnitude of eight steroid hormones, octylphenol (OP), nonylphenol (NP), 16 nonylphenol ethoxylates (NPEOs), and 10 octylphenol ethoxylates (OPEOs) in wastewater from a(n) hospital, nursing Facility, assisted living Facility, and independent living Facility are presented. Steroid hormone concentrations were variable for each sampling location, ranging from a non-detectable concentration of 17beta-ethynylestradiol in all samples to 127ngL(-1) androstenedione in the hospital's wastewater composite. OP and NP were not detected in any site's samples. However, NPEOs were found at each sampling location with a maximum combined concentration of 260microgL(-1) for NPEOs with a chain length between 3 and 18 units in the assisted living Facility composite sample. OPEOs were only found in the hospital and nursing facilities samples with a maximum combined OPEO concentration of 13microgL(-1) for OPEOs with a chain length between 2 and 12 units in hospital wastewater. The total mass loading of hormones to the municipal sewer system from each Facility ranged from 2.5mgd(-1) at the assisted living Facility to 138mgd(-1) at the hospital. The total mass loading of the alklyphenol ethoxylates (NPEO+OPEO) is considerably higher than the estimated hormone mass loadings, ranging from 1.8gd(-1) at the independent living Facility to 54gd(-1) at the hospital Facility.
Steven W Johnson - One of the best experts on this subject based on the ideXlab platform.
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effectiveness of oral vancomycin for prevention of Healthcare Facility onset clostridioides difficile infection in targeted patients during systemic antibiotic exposure
Clinical Infectious Diseases, 2020Co-Authors: Steven W Johnson, Shannon V Brown, David H PriestAbstract:Background Limited retrospective data suggest prophylactic oral vancomycin may prevent Clostridioides difficile infection (CDI). We sought to evaluate the effectiveness of oral vancomycin for the prevention of Healthcare Facility-onset CDI (HCFO-CDI) in targeted patients. Methods We conducted a randomized, prospective, open-label study at Novant Health Forsyth Medical Center in Winston-Salem, North Carolina, between October 2018 and April 2019. Included patients were randomized 1:1 to either oral vancomycin (dosed at 125 mg once daily while receiving systemic antibiotics and continued for 5 days postcompletion of systemic antibiotics [OVP]) or no prophylaxis. The primary endpoint was incidence of HCFO-CDI. Secondary endpoints included incidence of community-onset Healthcare Facility-associated CDI (CO-HCFA-CDI), incidence of vancomycin-resistant Enterococci (VRE) colonization after receiving OVP, adverse effects, and cost of OVP. Results A total of 100 patients were evaluated, 50 patients in each arm. Baseline and hospitalization characteristics were similar, except antibiotic exposure. No events of HCFO-CDI were noted in the OVP group compared with 6 (12%) in the no-prophylaxis group (P = .03). CO-HCFA-CDI was identified in 2 patients who were previously diagnosed with HCFO-CDI. No patients developed new VRE colonization, with only 1 patient reporting mild gastrointestinal side effects to OVP. A total of 600 doses of OVP were given during the study, with each patient receiving an average of 12 doses. Total acquisition cost of OVP was $1302, $26.04 per patient. Conclusion OVP appears to protect against HCFO-CDI during in-patient stay in targeted patients during systemic antibiotic exposure. Further prospective investigation is warranted.
Marc Egrot - One of the best experts on this subject based on the ideXlab platform.
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gender asymmetry in Healthcare Facility attendance of people living with hiv aids in burkina faso
Social Science & Medicine, 2009Co-Authors: Blandine Bila, Marc EgrotAbstract:Anthropological research in Burkina Faso indicates that more HIV-positive women than HIV-positive men are attending care facilities for people living with HIV/AIDS (PLWH) and accessing antiretroviral medicine. This article, situated in the field of study of interactions between gender and AIDS, offers a description of this asymmetry and an anthropological analysis of the socio-cultural determinants, through analysis of data from ethnographic research among PLWH and health actors. Examining social representations of femininity and masculinity in Burkinabe society and the organisation of the Healthcare system in connection with gender shed light on the decision-making processes of both sexes around therapeutic choices and the itinerary of care. On the one hand, the social values attached to femininity, maternity and the status of wife create conditions for women that favour their attendance at care facilities for PLWH and encourage a widespread practice where wives take the place of their husbands in Healthcare queues. Moreover, health policies and the effects of women's empowerment within the Healthcare system strengthen women's access to health services. On the other hand, representations of masculinity are fully implicated in the cultural construction of men's reluctance to attend care facilities for PLWH.The values associated with thismasculinitycausemento run great health, economic and social risks, not only for themselves, but also for their wives and children. By better understanding the interaction between gender, the experience of HIV and the institutional organisation of Healthcare, we can identify ways to reduce men's reluctance to attend care facilities for PLWH and improve both prevention and treatment-oriented programmes.
Yue Zhang - One of the best experts on this subject based on the ideXlab platform.
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the impact of client choice on preventive Healthcare Facility network design
OR Spectrum, 2012Co-Authors: Yue Zhang, Oded Berman, Vedat VerterAbstract:In contrast with sick people who need urgent medical attention, the clientele of preventive Healthcare have a choice in whether to participate in the programs offered in their region. In order to maximize the total participation to a preventive care program, it is important to incorporate how potential clients choose the facilities to patronize. We study the impact of client choice behavior on the configuration of a preventive care Facility network and the resulting level of participation. To this end, we present two alternative models: in the "probabilistic-choice model" a client may patronize each Facility with a certain probability, which increases with the attractiveness of the available facilities. In contrast, the "optimal-choice model" stipulates that each client will go to the most attractive Facility. In this paper, we assume that the proximity to a Facility is the only attractiveness attribute considered by clients. To ensure the quality of care, we impose a bound on the mean waiting time as well as a minimum workload requirement at each open Facility. Subject to a total capacity limit, the number of open facilities as well as the location and the capacity (number of servers) of each open Facility is the main determinant of the configuration of a Facility network. Both models are formulated as a mixed-integer program. To solve the problems efficiently, we propose a probabilistic search algorithm and a genetic algorithm. Finally, we use the models to analyze the network of mammography centers in Montreal.
-
a bilevel model for preventive Healthcare Facility network design with congestion
Iie Transactions, 2010Co-Authors: Yue Zhang, Oded Berman, Patrice Marcotte, Vedat VerterAbstract:Preventive Healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The level of participation in preventive Healthcare programs is a critical determinant in terms of their effectiveness and efficiency. This article presents a methodology for designing a network of preventive Healthcare facilities so as to improve its accessibility to potential clients and thus maximize participation in preventive Healthcare programs. The problem is formulated as a mathematical program with equilibrium constraints; i.e., a bilevel non-linear optimization model. The lower level problem which determines the allocation of clients to facilities is formulated as a variational inequality; the upper level is a Facility location and capacity allocation problem. The developed solution approach is based on the location–allocation framework. The variational inequality is formulated as a convex optimization problem, which can be solved by the gradient project...
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incorporating congestion in preventive Healthcare Facility network design
European Journal of Operational Research, 2009Co-Authors: Yue Zhang, Oded Berman, Vedat VerterAbstract:Preventive Healthcare aims at reducing the likelihood and severity of potentially life-threatening illnesses by protection and early detection. The level of participation to preventive Healthcare programs is a crucial factor in terms of their effectiveness and efficiency. This paper provides a methodology for designing a network of preventive Healthcare facilities so as to maximize participation. The number of facilities to be established and the location of each Facility are the main determinants of the configuration of a Healthcare Facility network. We use the total (travel, waiting and service) time required for receiving the preventive service as a proxy for accessibility of a Healthcare Facility, and assume that each client would seek the services of the Facility with minimum expected total time. At each Facility, which we model as an M/M/1 queue so as to capture the level of congestion, the expected number of participants from each population zone decreases with the expected total time. In order to ensure service quality, the facilities cannot be operated unless their level of activity exceeds a minimum workload requirement. The arising mathematical formulation is highly nonlinear, and hence we provide a heuristic solution framework for this problem. Four heuristics are compared in terms of accuracy and computational requirements. The most efficient heuristic is utilized in solving a real life problem that involves the breast cancer screening center network in Montreal. In the context of this case, we found out that centralizing the total system capacity at the locations preferred by clients is a more effective strategy than decentralization by the use of a larger number of smaller facilities. We also show that the proposed methodology can be used in making the investment trade-off between expanding the total system capacity and changing the behavior of potential clients toward preventive Healthcare programs by advertisement and education.
