Design of an Information System for optimizing the Programming of nursing work shifts

dc.creatorOsores, F.
dc.creatorCabrera, G.
dc.creatorLinfati, R.
dc.creatorUmaña-Ibañez, S.
dc.creatorCoronado-Henández, J.
dc.creatorGatica, G.
dc.date2020-08-12T15:35:45Z
dc.date2020-08-12T15:35:45Z
dc.date2020
dc.date.accessioned2023-10-03T19:03:46Z
dc.date.available2023-10-03T19:03:46Z
dc.identifier1757-8981
dc.identifier1757-899X
dc.identifierhttps://hdl.handle.net/11323/6910
dc.identifierdoi:10.1088/1757-899X/844/1/012044
dc.identifierCorporación Universidad de la Costa
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9167276
dc.descriptionHealth institutions operate twenty-four hours a day, seven days a week. They face a demand that fluctuates daily. Unlike jobs with fixed hours and obligatory days off, in health, operational continuity is required. The allocation for nursing shifts generates a rotation of people for health services according to legal and casuistic guidelines. Assigning and planning shifts results in a workload that takes an average of five to six extra hours. Existing applications offer a partial solution because they do not consider the news and contingencies of a health service. A web application is presented that, given a list of nurses, historical shifts and restrictions, a work shift planning is generated. This application comes to support the current shift allocation method based on electronic spreadsheets. The development consists of two modules. The first module has a shift allocation algorithm developed in C ++ and the second module has a graphical interface. As a case study, a set of health services from Chile and Colombia was used. The services have a defined number of nurses, who work different shifts according to the role and need of the institution. The results obtained are similar to a historical one. The proposed system takes less time and delivers various files and parameters that can be useful for nurses, the service and the health institution
dc.formatapplication/pdf
dc.languageeng
dc.publisherCorporación Universidad de la Costa
dc.relation[1] Fügener A, Pahr A and Brunner J O 2018 Mid-term nurse rostering considering cross-training effects Int. J. Prod. Econ. vol 196 pp 176–187
dc.relation[2] Azaiez M N and Al Sharif S S 2005 A 0-1 goal programming model for nurse scheduling, Comput. Oper. Res. vol 32 no 3 pp 491–507
dc.relation[3] Burke E K, Curtois T, Post G, Qu R, and Veltman B 2008 A hybrid heuristic ordering and variable neighbourhood search for the nurse rostering problem Eur. J. Oper. Res. vol 188 no 2, pp 330–341
dc.relation[4] Burke E K, Curtois T, Qu R, and Vanden Berghe G 2010 A scatter search methodology for the nurse rostering problem J. Oper. Res. Soc. vol 61 no 11 pp 1667–1679
dc.relation[5] De Causmaecker P and Vanden Berghe B 2011 A categorisation of nurse rostering problems, J. Sched vol 14 no 1 pp 3–16
dc.relation[6] Dowsland K A 1998 Nurse scheduling with tabu sGGGarch and strategic oscillation Eur. J. Oper. Res.vol 106 no 2–3 pp 393–407
dc.relation[7] Valouxis C and Housos E 2000 Hybrid optimization techniques for the workshift and rest assignment of nursing personnel Artif. Intell. Med. vol 20 no 2 pp 155–175
dc.relation[8] Vanhoucke V and Maenhout B 2009 On the characterization and generation of nurse scheduling problem instances Eur. J. Oper. Res. vol 196 no 2 pp 457–467
dc.relation[9] Komarudin, M A, Guerry T and Vanden Berghe G 2013 The roster quality staffing problem – A methodology for improving the roster quality by modifying the personnel structure Eur. J. Oper. Res. vol 230 no 3 pp 551–562
dc.relation[10] Miller H E, Pierskalla W P and Rath G J 1976 Nurse Scheduling Using Mathematical Programming Oper. Res. vol 24 no 5 pp 857–870
dc.relation[11] Warner D M 1976 Scheduling Nursing Personnel According to Nursing Preference: A Mathematical Programming Approach Oper. Res. vol. 24 no 5 pp 842–856
dc.relation[12] Berrada I, Ferland J A and Michelon P 1996 A multi-objective approach to nurse scheduling with both hard and soft constraints Socioecon. Plann. Sci. vol 30 no 3 pp 183–193
dc.relation[13] Clark A, Moule P Topping A and Serpell M 2015 Rescheduling nursing shifts: scoping the challenge and examining the potential of mathematical model based tools J. Nurs. Manag. vol 23 no 4 pp 411–420
dc.relation[14] MJC2 2018 Workforce Planning & Scheduling
dc.relation[15] Bester M J, Nieuwoudt I and Van Vuuren J H 2007 Finding good nurse duty schedules: a case study J. Sched. vol 10 no 6 pp 387–405
dc.relation[16] Cheang B, Li H, Lim A, and Rodrigues B 2003 Nurse rostering problems––a bibliographic survey Eur. J. Oper. Res., vol 151 no 3 pp 447–460
dc.relation[17] Erhard M, Schoenfelder J, Fügener A and Brunner J O 2018 State of the art in physician scheduling Eur. J. Oper. Res. vol 265 no 1 pp 1–18
dc.relation[18] Jaumard B, Semet F and Vovor T 1998 A generalized linear programming model for nurse scheduling Eur. J. Oper. Res. vol 107 no 1 pp 1–18
dc.relation[19] Burke E K, De Causmaecker P, Vanden Berghe G and Van Landeghem H 2004 The State of the Art of Nurse Rostering J. Sched. vol 7 no 6 pp 441–499
dc.relation[20] Bard J F and Purnomo H W 2005 Preference scheduling for nurses using column generation Eur. J. Oper. Res. vol 164 no 2 pp 510–534
dc.relation[21] Constantino A A, Landa-Silva D, de Melo E L, de Mendonça C F X, Rizzato D B and Romão W 2013 A heuristic algorithm based on multi-assignment procedures for nurse scheduling Ann. Oper. Res.
dc.relation[22] Lin C C, Kang J R, Chiang D J, and Chen C L 2015 Nurse Scheduling with Joint Normalized Shift and Day-Off Preference Satisfaction Using a Genetic Algorithm with Immigrant Scheme Int. J. Distrib. Sens. Networks, vol 11 no 7 p. 595419
dc.relation[23] Romero Conrado A, Coronado-Hernandez J, Rius-Sorolla G, and García-Sabater J 2019A Tabu List-Based Algorithm for Capacitated Multilevel Lot-Sizing with Alternate Bills of Materials and Co-Production Environments Appl. Sci. vol 9 no 7 p 1464
dc.relation[24] Vélez Vargas V, Henao Baena V and Calvo Salcedo 2018 A Design and implementation of a wired intercommunication prototype for hospital care INGE CUC vol 14 no 1 pp 101–112
dc.relation[25] Ernst A, Jiang H, Krishnamoorthy M and SierD 2004 Staff scheduling and rostering: A review of applications, methods and models Eur. J. Oper. Res.vol 153 no 1 pp 3–27
dc.relation[26] Lin C C, Kang J R, Liu W Y and Deng D J 2014 Modelling a Nurse Shift Schedule with Multiple Preference Ranks for Shifts and Days-Off Math. Probl. Eng. vol 2014 pp 1–10
dc.relation[27] Wu T H,Yeh J Yand Lee Y M 2015 A particle swarm optimization approach with refinement procedure for nurse rostering problem Comput. Oper. Res. vol 54 pp 52–63
dc.relation[28] Wijegunaratne I and Fernandez G 1998 The Three-Tier Application Architecture pp. 41–78.
dc.relation[29] International Organization for Standardization 2005 ISO/IEC 25000: Systems and software engineering - Systems and software Quality Requirements and Evaluation (SQuaRE).
dc.rightsCC0 1.0 Universal
dc.rightshttp://creativecommons.org/publicdomain/zero/1.0/
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.sourceIOP Conference Series: Materials Science and Engineering
dc.sourcehttps://iopscience.iop.org/article/10.1088/1757-899X/844/1/012044/meta
dc.subjectInformation system
dc.subjectProgramming
dc.subjectWork Shifts
dc.titleDesign of an Information System for optimizing the Programming of nursing work shifts
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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