High workload and job stress are associated with lower practice performance in general practice: an observational study in 239 general practices in the Netherlands

Contains fulltext : 80493.pdf (publisher's version ) (Open Access)BACKGROUND: The impact of high physician workload and job stress on quality and outcomes of healthcare delivery is not clear. Our study explored whether high workload and job stress were associated with lower performance in general practices in the Netherlands. METHODS: Secondary analysis of data from 239 general practices, collected in practice visits between 2003 to 2006 in the Netherlands using a comprehensive set of measures of practice management. Data were collected by a practice visitor, a trained non-physician observer using patients questionnaires, doctors and staff. For this study we selected five measures of practice performance as outcomes and six measures of GP workload and job stress as predictors. A total of 79 indicators were used out of the 303 available indicators. Random coefficient regression models were applied to examine associations. RESULTS AND DISCUSSION: Workload and job stress are associated with practice performance.Workload: Working more hours as a GP was associated with more positive patient experiences of accessibility and availability (b = 0.16). After list size adjustment, practices with more GP-time per patient scored higher on GP care (b = 0.45). When GPs provided more than 20 hours per week per 1000 patients, patients scored over 80% on the Europep questionnaire for quality of GP care.Job stress: High GP job stress was associated with lower accessibility and availability (b = 0.21) and insufficient practice management (b = 0.25). Higher GP commitment and more satisfaction with the job was associated with more prevention and disease management (b = 0.35). CONCLUSION: Providing more time in the practice, and more time per patient and experiencing less job stress are all associated with perceptions by patients of better care and better practice performance. Workload and job stress should be assessed by using list size adjusted data in order to realise better quality of care. Organisational development using this kind of data feedback could benefit both patients and GP

Production of He-4 and (4) in Pb-Pb collisions at root(NN)-N-S=2.76 TeV at the LHC

Results on the production of He-4 and (4) nuclei in Pb-Pb collisions at root(NN)-N-S = 2.76 TeV in the rapidity range vertical bar y vertical bar <1, using the ALICE detector, are presented in this paper. The rapidity densities corresponding to 0-10% central events are found to be dN/dy4(He) = (0.8 +/- 0.4 (stat) +/- 0.3 (syst)) x 10(-6) and dN/dy4 = (1.1 +/- 0.4 (stat) +/- 0.2 (syst)) x 10(-6), respectively. This is in agreement with the statistical thermal model expectation assuming the same chemical freeze-out temperature (T-chem = 156 MeV) as for light hadrons. The measured ratio of (4)/He-4 is 1.4 +/- 0.8 (stat) +/- 0.5 (syst). (C) 2018 Published by Elsevier B.V.Peer reviewe

Multiplicity dependence of (anti-)deuteron production in pp collisions at root s=7 TeV

none1019siIn this letter, the production of deuterons and anti-deuterons in pp collisions at root s = 7 TeV is studied as a function of the charged-particle multiplicity density at mid-rapidity with the ALICE detector at the LHC. Production yields are measured at mid-rapidity in five multiplicity classes and as a function of the deuteron transverse momentum (p(T)). The measurements are discussed in the context of hadron-coalescence models. The coalescence parameter B-2, extracted from the measured spectra of (anti-)deuteronsand primary (anti-)protons, exhibits no significant p(T)-dependence for p(T) < 3 GeV/c, in agreement with the expectations of a simple coalescence picture. At fixed transverse momentum per nucleon, the B-2 parameter is found to decrease smoothly from low multiplicity pp to Pb-Pb collisions, in qualitative agreement with more elaborate coalescence models. The measured mean transverse momentum of (anti-)deuterons in pp is not reproduced by the Blast-Wave model calculations that simultaneously describe pion, kaon and proton spectra, in contrast to central Pb-Pb collisions. The ratio between the p(T)-integrated yield of deuterons to protons, d/p, is found to increase with the charged-particle multiplicity, as observed in inelastic pp collisions at different centre-of-mass energies. The d/p ratios are reported in a wide range, from the lowest to the highest multiplicity values measured in pp collisions at the LHC. (C) 2019 The Author(s). Published by Elsevier B.VnoneAcharya, S.; Acosta, F. T.; Adamova, D.; Adhya, S. P.; Adler, A.; Adolfsson, J.; Aggarwal, M. M.; Rinella, G. Aglieri; Agnello, M.; Ahammed, Z.; Ahmad, S.; Ahn, S. U.; Aiola, S.; Akindinov, A.; Al-Turany, M.; Alam, S. N.; Albuquerque, D. S. D.; Aleksandrov, D.; Alessandro, B.; Alfanda, H. M.; Alfaro Molina, R.; Ali, B.; Ali, Y.; Alici, A.; Alkin, A.; Alme, J.; Alt, T.; Altenkamper, L.; Altsybeev, I; Anaam, M. N.; Andrei, C.; Andreou, D.; Andrews, H. A.; Andronic, A.; Angeletti, M.; Anguelov, V; Anson, C.; Anticic, T.; Antinori, F.; Antonioli, P.; Anwar, R.; Apadula, N.; Aphecetche, L.; Appelshaeuser, H.; Arcelli, S.; Arnaldi, R.; Arratia, M.; Arsene, I. C.; Arslandok, M.; Augustinus, A.; Averbeck, R.; Azmi, M. D.; Badala, A.; Baek, Y. W.; Bagnasco, S.; Bailhache, R.; Bala, R.; Baldisseri, A.; Ball, M.; Baral, R. C.; Barbera, R.; Barioglio, L.; Barnafoldi, G. G.; Barnby, L. S.; Barret, V; Bartalini, P.; Barth, K.; Bartsch, E.; Bastid, N.; Basu, S.; Batigne, G.; Batyunya, B.; Batzing, P. C.; Bauri, D.; Bazo Alba, J. L.; Bearden, I. G.; Bedda, C.; Behera, N. K.; Belikov, I; Bellini, F.; Bello Martinez, H.; Bellwied, R.; Beltran, L. G. E.; Belyaev, V; Bencedi, G.; Beole, S.; Bercuci, A.; Berdnikov, Y.; Berenyi, D.; Bertens, R. A.; Berzano, D.; Betev, L.; Bhasin, A.; Bhat, I. R.; Bhatt, H.; Bhattacharjee, B.; Bianchi, A.; Bianchi, L.; Bianchi, N.; Bielcik, J.; Bielcikova, J.; Bilandzic, A.; Biro, G.; Biswas, R.; Biswas, S.; Blair, J. T.; Blau, D.; Blume, C.; Boca, G.; Bock, F.; Bogdanov, A.; Boldizsar, L.; Bolozdynya, A.; Bombara, M.; Bonomi, G.; Bonora, M.; Borel, H.; Borissov, A.; Borri, M.; Botta, E.; Bourjau, C.; Bratrud, L.; Braun-Munzinger, P.; Bregant, M.; Broker, T. A.; Broz, M.; Brucken, E. J.; Bruna, E.; Bruno, G. E.; Buckland, M. D.; Budnikov, D.; Buesching, H.; Bufalino, S.; Buhler, P.; Buncic, P.; Busch, O.; Buthelezi, Z.; Butt, J. B.; Buxton, J. T.; Caffarri, D.; Caines, H.; Caliva, A.; Calvo Villar, E.; Camacho, R. S.; Camerini, P.; Capon, A. A.; Carnesecchi, F.; Castellanos, J. Castillo; Castro, A. J.; Casula, E. A. R.; Sanchez, C. Ceballos; Chakraborty, P.; Chandra, S.; Chang, B.; Chang, W.; Chapeland, S.; Chartier, M.; Chattopadhyay, S.; Chauvin, A.; Cheshkov, C.; Cheynis, B.; Barroso, V. Chibante; Chinellato, D. D.; Cho, S.; Chochula, P.; Chowdhury, T.; Christakoglou, P.; Christensen, C. H.; Christiansen, P.; Chujo, T.; Cicalo, C.; Cifarelli, L.; Cindolo, F.; Cleymans, J.; Colamaria, F.; Colella, D.; Collu, A.; Colocci, M.; Concas, M.; Balbastre, G. Conesa; del Valle, Z. Conesa; Contin, G.; Contreras, J. G.; Cormier, T. M.; Morales, Y. Corrales; Cortese, P.; Cosentino, M. R.; Costa, F.; Costanza, S.; Crkovska, J.; Crochet, P.; Cuautle, E.; Cunqueiro, L.; Dabrowski, D.; Dahms, T.; Dainese, A.; Damas, F. P. A.; Dani, S.; Danisch, M. C.; Danu, A.; Das, D.; Das, I; Das, S.; Dash, A.; Dash, S.; Dashi, A.; De, S.; De Caro, A.; de Cataldo, G.; de Conti, C.; de Cuveland, J.; De Falco, A.; De Gruttola, D.; De Marco, N.; De Pasquale, S.; De Souza, R. D.; Degenhardt, H. F.; Deisting, A.; Deloff, A.; Delsanto, S.; Dhankher, P.; Di Bari, D.; Di Mauro, A.; Diaz, R. A.; Dietel, T.; Dillenseger, P.; Ding, Y.; Divia, R.; Djuvsland, O.; Dobrin, A.; Domenicis Gimenez, D.; Doenigus, B.; Dordic, O.; Dubey, A. K.; Dubla, A.; Dudi, S.; Duggal, A. K.; Dukhishyam, M.; Dupieux, P.; Ehlers, R. J.; Elia, D.; Engel, H.; Epple, E.; Erazmus, B.; Erhardt, F.; Erokhin, A.; Ersdal, M. R.; Espagnon, B.; Eulisse, G.; Eum, J.; Evans, D.; Evdokimov, S.; Fabbietti, L.; Faggin, M.; Faivre, J.; Fantoni, A.; Fasel, M.; Feldkamp, L.; Feliciello, A.; Feofilov, G.; Fernandez Tellez, A.; Ferrero, A.; Ferretti, A.; Festanti, A.; Feuillard, V. J. G.; Figiel, J.; Filchagin, S.; Finogeev, D.; Fionda, F. M.; Fiorenza, G.; Flor, F.; Floris, M.; Foertsch, S.; Foka, P.; Fokin, S.; Fragiacomo, E.; Francisco, A.; Frankenfeld, U.; Fronze, G. G.; Fuchs, U.; Furget, C.; Furs, A.; Girard, M. Fusco; Gaardhoje, J. J.; Gagliardi, M.; Gago, A. M.; Gajdosova, K.; Galvan, C. D.; Ganoti, P.; Garabatos, C.; Garcia-Solis, E.; Garg, K.; Gargiulo, C.; Garner, K.; Gasik, P.; Gauger, E. F.; Gay Ducati, M. B.; Germain, M.; Ghosh, J.; Ghosh, P.; Ghosh, S. K.; Gianotti, P.; Giubellino, P.; Giubilato, P.; Glaessel, P.; Gomez Coral, D. M.; Ramirez, A. Gomez; Gonzalez, V; Gonzalez-Zamora, P.; Gorbunov, S.; Gorlich, L.; Gotovac, S.; Grabski, V; Graczykowski, L. K.; Graham, K. L.; Greiner, L.; Grelli, A.; Grigoras, C.; Grigoriev, V; Grigoryan, A.; Grigoryan, S.; Gronefeld, J. M.; Grosa, F.; Grosse-Oetringhaus, J. F.; Grosso, R.; Guernane, R.; Guerzoni, B.; Guittiere, M.; Gulbrandsen, K.; Gunji, T.; Gupta, A.; Gupta, R.; Guzman, I. B.; Haake, R.; Habib, M. K.; Hadjidakis, C.; Hamagaki, H.; Hamar, G.; Hamid, M.; Hamon, J. C.; Hannigan, R.; Haque, M. R.; Harlenderova, A.; Harris, J. W.; Harton, A.; Hassan, H.; Hatzifotiadou, D.; Hauer, P.; Hayashi, S.; Heckel, S. T.; Hellbaer, E.; Helstrup, H.; Herghelegiu, A.; Hernandez, E. G.; Herrera Corral, G.; Herrmann, F.; Hetland, K. F.; Hilden, T. E.; Hillemanns, H.; Hills, C.; Hippolyte, B.; Hohlweger, B.; Horak, D.; Hornung, S.; Hosokawa, R.; Hota, J.; Hristov, P.; Huang, C.; Hughes, C.; Huhn, P.; Humanic, T. J.; Hushnud, H.; Husova, L. A.; Hussain, N.; Hussain, T.; Hutter, D.; Hwang, D. S.; Iddon, J. P.; Ilkaev, R.; Inaba, M.; Ippolitov, M.; Islam, M. S.; Ivanov, M.; Ivanov, V; Izucheev, V; Jacak, B.; Jacazio, N.; Jacobs, P. M.; Jadhav, M. B.; Jadlovska, S.; Jadlovsky, J.; Jaelani, S.; Jahnke, C.; Jakubowska, M. J.; Janik, M. A.; Jercic, M.; Jevons, O.; Bustamante, R. T. Jimenez; Jin, M.; Jones, P. G.; Jusko, A.; Kalinak, P.; Kalweit, A.; Kang, J. H.; Kaplin, V; Kar, S.; Uysal, A. Karasu; Karavichev, O.; Karavicheva, T.; Karczmarczyk, P.; Karpechev, E.; Kebschull, U.; Keidel, R.; Keil, M.; Ketzer, B.; Khabanova, Z.; Khan, A. M.; Khan, S.; Khan, S. A.; Khanzadeev, A.; Kharlov, Y.; Khatun, A.; Khuntia, A.; Kielbowicz, M. M.; Kileng, B.; Kim, B.; Kim, D.; Kim, D. J.; Kim, E. J.; Kim, H.; Kim, J. S.; Kim, J.; Kim, M.; Kim, S.; Kim, T.; Kindra, K.; Kirsch, S.; Kisel, I; Kiselev, S.; Kisiel, A.; Klay, J. L.; Klein, C.; Klein, J.; Klein, S.; Klein-Boesing, C.; Klewin, S.; Kluge, A.; Knichel, M. L.; Knospe, A. G.; Kobdaj, C.; Kofarago, M.; Koehler, M. K.; Kollegger, T.; Kondratyeva, N.; Kondratyuk, E.; Konopka, P. J.; Konyushikhin, M.; Koska, L.; Kovalenko, O.; Kovalenko, V; Kowalski, M.; Kralik, I; Kravcakova, A.; Kreis, L.; Krivda, M.; Krizek, F.; Krueger, M.; Kryshen, E.; Krzewicki, M.; Kubera, A. M.; Kucera, V; Kuhn, C.; Kuijer, P. G.; Kumar, L.; Kumar, S.; Kundu, S.; Kurashvili, P.; Kurepin, A.; Kurepin, A. B.; Kushpil, S.; Kvapil, J.; Kweon, M. J.; Kwon, Y.; La Pointe, S. L.; La Rocca, P.; Lai, Y. S.; Langoy, R.; Lapidus, K.; Lardeux, A.; Larionov, P.; Laudi, E.; Lavicka, R.; Lazareva, T.; Lea, R.; Leardini, L.; Lee, S.; Lehas, F.; Lehner, S.; Lehrbach, J.; Lemmon, R. C.; Leon Monzon, I; Levai, P.; Li, X.; Li, X. L.; Lien, J.; Lietava, R.; Lim, B.; Lindal, S.; Lindenstruth, V; Lindsay, S. W.; Lippmann, C.; Lisa, M. A.; Litichevskyi, V; Liu, A.; Ljunggren, H. M.; Llope, W. J.; Lodato, D. F.; Loginov, V; Loizides, C.; Loncar, P.; Lopez, X.; Lopez Torres, E.; Luettig, P.; Luhder, J. R.; Lunardon, M.; Luparello, G.; Lupi, M.; Maevskaya, A.; Mager, M.; Mahmood, S. M.; Mahmoud, T.; Maire, A.; Majka, R. D.; Malaev, M.; Malik, Q. W.; Malinina, L.; Mal'Kevich, D.; Malzacher, P.; Mamonov, A.; Manko, V; Manso, F.; Manzari, V; Mao, Y.; Marchisone, M.; Mares, J.; Margagliotti, G., V; Margotti, A.; Margutti, J.; Marin, A.; Markert, C.; Marquard, M.; Martin, N. A.; Martinengo, P.; Martinez, J. L.; Martinez, M., I; Garcia, G. Martinez; Pedreira, M. Martinez; Masciocchi, S.; Masera, M.; Masoni, A.; Massacrier, L.; Masson, E.; Mastroserio, A.; Mathis, A. M.; Matuoka, P. F. T.; Matyja, A.; Mayer, C.; Mazzilli, M.; Mazzoni, M. A.; Meddi, F.; Melikyan, Y.; Menchaca-Rocha, A.; Meninno, E.; Meres, M.; Mhlanga, S.; Miake, Y.; Micheletti, L.; Mieskolainen, M. M.; Mihaylov, D. L.; Mikhaylov, K.; Mischke, A.; Mishra, A. N.; Miskowiec, D.; Mitra, J.; Mitu, C. M.; Mohammadi, N.; Mohanty, A. P.; Mohanty, B.; Khan, M. Mohisin; Mondal, M. M.; Mordasini, C.; De Godoy, D. A. Moreira; Moreno, L. A. P.; Moretto, S.; Morreale, A.; Morsch, A.; Mrnjavac, T.; Muccifora, V; Mudnic, E.; Muehlheim, D.; Muhuri, S.; Mukherjee, M.; Mulligan, J. D.; Munhoz, M. G.; Muenning, K.; Munzer, R. H.; Murakami, H.; Murray, S.; Musa, L.; Musinsky, J.; Myers, C. J.; Myrcha, J. W.; Naik, B.; Nair, R.; Nandi, B. K.; Nania, R.; Nappi, E.; Naru, M. U.; Nassirpour, A. F.; Natal da Luz, H.; Nattrass, C.; Navarro, S. R.; Nayak, K.; Nayak, R.; Nayak, T. K.; Nazarenko, S.; De Oliveira, R. A. Negrao; Nellen, L.; Nesbo, S., V; Neskovic, G.; Ng, F.; Nielsen, B. S.; Nikolaev, S.; Nikulin, S.; Nikulin, V; Noferini, F.; Nomokonov, P.; Nooren, G.; Noris, J. C. 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A mean value analysis of a closed CP-terminal system with pre-emptive resume priorities and general service time distributions

This paper deals with the analysis of a queueing system which may be used as a model for a computer system with terminals, the so-called CP-terminal system, or a machine-interference model. The system can be viewed as a single server queue with a number of finite Poisson sources, general service time distributions and a preemptive resume priority scheduling. A recursive scheme will be derived for the computation of performance measures. The technique is based on mean value ideas and renewal arguments

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This note considers an alternative derivation of the basic recursive relation in the recently developed RECAL or recursion by chain algorithm for the evaluation of the normalization constant of a product-form closed multichain queueing network model. The technique is based on a z-transform representation of the set of normalization constants

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If networks of queues satisfy certain conditions, then the equilibrium distribution for the number of jobs in the various stations has the so-called product-form. In such cases there are relatively elegant and simple computational procedures for the relevant behavioral characteristics. Quite commonly, however, the conditions are too severe and exact solution is practically impossible for larger problems.\u3cbr/\u3e\u3cbr/\u3eIn this paper we will consider iterative approximations for networks of queues which either don't possess product-form solutions or are so large that exact solution becomes intractable even using the product-form of the solution. The approximations are based on a mean value analysis approach and use either aggregation of some sort or decomposition. For the details of the approximations heuristic arguments are used. The approach is worked out for some problem types

Iterative approximation for networks of queues

If networks of queues satisfy certain conditions, then the equilibrium distribution for the number of jobs in the various stations has the so-called product-form. In such cases there are relatively elegant and simple computational procedures for the relevant behavioral characteristics. Quite commonly, however, the conditions are too severe and exact solution is practically impossible for larger problems. In this paper we will consider iterative approximations for networks of queues which either don't possess product-form solutions or are so large that exact solution becomes intractable even using the product-form of the solution. The approximations are based on a mean value analysis approach and use either aggregation of some sort or decomposition. For the details of the approximations heuristic arguments are used. The approach is worked out for some problem types