Set the Nurses Working Hours Using Graph Coloring Method and Simulated Annealing Algorithm
|
|
- Shanon Hall
- 5 years ago
- Views:
Transcription
1 Set the Nurses Working Hours Using Graph Coloring Method and Simulated Annealing Algorithm Elham Photoohi Bafghi Department of Computer, Bafgh Branch, Islamic Azad University, Bafgh, Iran. Abstract Adjustment of nursing programs in the specified period as it can cover the requirements of hospitals, nurses and patients is a challenging task for nursing managers. The project aims to design intelligent system as a scheduler by a system of Simulated Annealing Algorithm to provide better services to patients and overcome traditional scheduling problems. Of course, the property of graph coloring is used to do this. The project has been applied to design programs based on the data derived from interviews and shifts of nurse managers in the hospital. Data analysis has been taken by converting the process of planning of the expert to the mathematical function of Simulated Annealing Algorithm using the C # programming language. Planning and scheduling of nursing shift work was designed by the system which has a high efficiency compared to individual and leads to increased efficiency of managers, increased job satisfaction of nurses, reduced problems of working with paper reports and observing the needs of the staff in addition to considering the hospital requirements. Finally, the performance of the proposed algorithm was compared with genetic algorithms. Regarding the number of groups made up in relation to the number of nurses in the conducted tests, Simulated Annealing Algorithm was capable for planning in all cases while the genetic algorithm programming is taken in 92% of the scheduling cases. Keywords: shift of nurses, genetic algorithm, algorithm of metals annealing. INTRODUCTION Health is one of the national strategic areas of development of information technology in the country and nursing care is an essential component of health care. Optimal regulation of nursing scheduler has a prominent effect on reducing hospital costs, increasing nurses job satisfaction, quality of care and increase of hospital entrance budget. So hospital can reduce programming problems in addition to increase of the performance by having the optimum regulation of nursing shifts by having better programming for the human resources and optimal use of working labors. Planning and scheduling of the sources in traditional ways and the respect to the individual excellence, staffs requirements and equitable distribution of advantages and favorable demographic shift demand for nursing managers, difficult and time consuming so. Intelligent and automated planning and business planning can be used for the calculation of working hours of nurses to provide better services to patients and nursing managers used to deal with problems. Planning and scheduling of the resources in traditional and the respect of staff superiority and equitable distribution of favorable division of shift is somehow difficult for nursing managers. Intelligent and automated planning can be used for the calculation of working hours and business planning of nurses to provide better services to patients and oppose nursing managers to deal with problems. In hospitals, nursing planning is taken in three personal methods, performed periodic and cyclical. Individual planning taken based on staff s demand, possesses large benefits such as reduced absence, increased organizational conscientiousness, induction of professional independence and saving managing times. However, there are some inherent problems, such as priority of the individual needs to the needs of health care organizations, non-compliance with proper distribution of ranks to provide better care and unfair distribution of desirable shifts. Private health centers that often have fixed sources, apply cyclic planning method, so that for a certain period of time, they assign a fixed program to their sources. But in this method less justice is observed. Non-cyclical program has high flexibility for working as the working hours and holidays of employees varies from week to week. In this method, in addition to the importance given to personal desires, needs of the sections are also considered. Since the current process of planning for nursing shifts at most of the hospitals, is taken in non-cyclic way and due to the diversity of the program, observation of demands of the section, planning for staffs requirements and the equitable distribution of sources in the traditional programs is more complicated and time-consuming. In this project, the problem is raised in this way and the solution is proposed. Aikline pointed out that since the 1970s, the viewpoint of solving problems using computer has been created by experts. He believes that his investigation about methods of optimization of planning follows a total overall goal of "how to find good possible solutions in the shortest possible time" [1]. The results show that for problem solving sessions for nurses appointments, the proposed algorithm, as a meta-heuristic method is the most applied method [2].Studies have shown that genetic algorithms, is the most evolutionary and most widely-known algorithm, possesses immense power of problem solving [3, 4]. GA, as a method of finding the optimal solution of a problem is defined as the conventional methods in artificial intelligence. Infrastructure components of the evolutionary process in genetic algorithm are included of the population genetic program, reproduction, mutation, competition and choice. In this way, by gradual removing the improper species and at the same time by optimal amplification of higher species, nature can continue to improve each generation by different characteristics. In fact, the natural evolution can be summarized as random search and survival of the fittest [2, 5]. The main purpose of this project is to design smart systems, nursing scheduler 8195
2 algorithm by Simulated Annealing Algorithm (annealing of metals). A method is implemented in this project to provide a consolidated program regarding the number of nurses in a hospital. RESEARCH BACKGROUND Chang and Sherman (2002), conducted a mathematical modeling in a two-stage study for a scheduling system according to the requirements of hospital management and government regulations of nurses and nurse's shift preferences. Researcher named Hofe, considered the purpose of planning, as a constrain for solving the nurses scheduling problem and have shown that other techniques can be also used for solving the nurses scheduling problems. Chang and Sherman (2002), mathematical modeling in a two-stage study for a scheduling system according to the requirements of hospital management and government regulations nurses and nurse's shift preferences. Researcher Hofe purpose of planning, problem solving scheduling restrictions for nurses and other techniques have shown that nurses are able to solve scheduling problems. Maier and Wolfe (2005) studied the Viena hospital and applied the ant colony optimization method to allocate nurses in hospitals based on some specific limitations. Rothstein and non-rotating schedule Warner had examined the non-rotating scheduling as the use of true method was related to operations of offices and hospitals house working. GRAPH COLORING METHODS Graph Coloring Problem (GCP) is about having a graph G and aim to determine the minimum required colors for coloring the vertices of the graph, so that no two adjacent vertices have the same color. The minimum number of colors required for this purpose is called the color number of graphs shown by χ (G). This is a very difficult problem in NP-Complete series [6]. Johnson et al., showed that none of the proposed deterministic algorithms, are able to color the even relatively small graph with 70 vertices and density of 0.5 [7]. The mean of graph density refers to the ratio of the number of graph edges to the edges of a complete graph with the same number of vertices. Solving the graph coloring problem is difficult even in approximation and it is proved that no polynomial algorithm is able to color a graph with colors lower than 2 χ (G) (Unless it is proven that P=N). GENETIC ALGORITHM This algorithm codes a potential solution to a specific problem on the data structure (such as chromosome) and applies combined operators on these structures to save the vital information. Board of problems apply Genetic algorithm is very extensive and it could be said that genetic algorithm is a universal search technology and a very convenient way to get the global optimal way. Genetic algorithm is type of a powerful search algorithms counts as the most popular and widely used evolutionary algorithms. Therefore, since these types of algorithms are based on biological evolution, they imitate the concepts of heritage, genetic and mutations. Considering the fact that the coloring is one of the oldest and most famous problems in graph theory and allocates various applications, it is known as NP-Hard problems for arbitrary graphs. While it can be solved for certain categories of graphs, including complete polynomial graphs. A lot of work have been dedicated to develop efficient algorithms for graph coloring problems, as an important part of these works can be devoted to intelligent design and exploration. So the genetic algorithm can be used for graph coloring problem to achieve the optimal solution [8]. THE STEPS OF GENETIC ALGORITHM The genetic algorithm steps include coding, evaluation, selection, cutting and mutations. Coding step is the hardest step to solve the problem by using genetic algorithms. In the standard genetic algorithms, string with limited length shows each chromosome. A string may include a series of binary, correct, or characters bits. Solution of the problem must be encoded in strings. In fact, at this stage, we build the possible chromosomal sequences for an answer. Coding scheme is important because it has a significant impact on the accuracy of the genetic algorithm. You may be able to improve genetic algorithm in a decent time by applying a proper simulation for the responses. After configuration for each possible response, the basic population is formed by assembly of these structures. In evaluation step, a fitness value is assigned to each chromosome. The genetic algorithm uses the quality of a chromosome to determine its compatibility, then applies it to determine the likelihood that the chromosome can stay alive in the next generation. Genetic algorithm produces offspring of a pair of chromosomes in the population. Chromosome with high fitness value will survive and chromosomes with low fitness value are destroyed. The next step is about selection. Parents are selected randomly with probability proportional to the fitness value attributed to them. Cutting is the most important step in genetic algorithm. Some parents chromosomes are directly simulated to the number of children. In other cases, pairs of parents are cut and resulting chromosomes are inserted into the population of children. Cutting is depended on the cutting rate. Mutation selects some of the genes of each chromosome randomly and varies them. The probability of this event is governed by mutation rate. Genetic Algorithm is evaluated by implementation of procedure step by step including: 1) Start algorithm with a population of N random individuals (chromosomes), 2) calculation of adjustment for each chromosome, 3) Selection of two parent chromosome, based on higher adjustment, 4) Apply of cutting regarding the rate for one of the children, 5) Put the created offspring into a complex as a new generation, 6) Replacement of the new generation in the basic population, 7) Go to step 2 (after consolidation of new generation, the algorithm returns once again to the evaluation stage.) [9]. RESEARCH METHODOLOGY In this project as a applicable one on the basis of data derived from nursing shifts scheduler, samples from two sections of the hospital with the highest complexity of planning were selected as default. The data collection tools included of 8196
3 programs of nurses shifts. Then the proposed system was designed based on data obtained by selected sections with non-random planning. Data analysis was taken by evaluation, pre-processing and post-processing of data and calculations of the price functions based on the trend of scheduling of the expert ones to the numerical function and programming based on the Simulated Annealing Algorithm, via C in Visual Studio environment. In the final step, the comparison was taken by genetic algorithms for evaluation of system performance. THE SAMPLE PROPOSED METHOD Evaluation of studies conducted in this area shows that there are several ways for solving the scheduling and timing of nurses programs, but most of them solve a simple model or are depended on a particular problem in a hospital. For example, in Chen and Wornell s studied the ratings were not considered. In a study conducted by Hancock, times of start of work were considered to be flexible instead of three constant times and ratings was not considered for nurses. In addition, it was allowed to have higher or lower staff relative to the number of required employees [,11].In this project, the purpose functions were determined based on the definition of the problem, while the purpose function in different studies were considered to be depended on the type of problem definition in a specific hospital. In this project lower number of limitations were considered in the problem, it is recommended to consider more limitations in future studies to get closer to the answer in the real world. In the present study, in the second part, based on the plans it was observed that program was written for 15 people instead of 20, practically, because one of the personnel did not have the physical presence because of leaving. So, in order to have a more natural response, the program was designed of 15 people in the system and obtained a more actual percentage in reduction of costs. Since data processing and adjustment of shift tables for the staff takes much time from the nursing managers and the applied model schedules the nursing affairs more rapidly, a 92% of save was occurred in the case of time scheduling and improvement of managers performance in relation to the application of genetic algorithms. In addition, program regulation time for each person was reduced. Difference of program regulation time in different studies was taken by using various methods and strategies. Providing people with nursing services in hospitals and health centers is considered as the person has the competency and skills for providing proper services. Also planning for the nurses is among the biggest challenges in the hospitals, because scheduling requires to provide hospitals while providing the individual requirements of the nurses which leads to a continues challenge. The system developed in this project has advantages over the existing internet-based systems, because in addition to valuing employees demands, it also cares about the regulations and requirements of hospital. Another benefit of the designed system is about the uniform distribution of forces that leads to opposition against any form of injustice in shifts distribution and due to the reduction of overtime work loads, employees will be more satisfied and will improve the quality of care. In addition, for evaluation o the approach presented by the designed system in the case of lack of personnel, a more justice program could be provided by homogenous distribution of working hours among other personnel in relation to the experts. While the approach of expert people is included of adding the working hours of some people and non-uniform distribution of working hours of absent people among the existed ones. So the designed system is able to have an equitable distribution of program while lack of personnel among the others, as the fairer program leads to higher satisfaction of the personnel and approximation of working hours to designed ones and reduction of excess load of some nurses. In general, in this project the case of regulation of working hours of nursing shifts was defined for the first time in local scale by means of Simulated Annealing Algorithm, as maximum number of 20 nurses were distributed in 3 shift appointments of morning, evening and night during a week uniformly. According to the results of this study, it can be concluded that since the present health organization is still prepared in the country in a manual and paper-based manner, this problem takes so much time and cost of excess paper for maintenance of programs and taking management decisions. Since there is the ability to automatically provide such information, the use of intelligent methods to provide optimum program seems to be necessary. Results showed the present condition of planned shift of nurses in hospitals often consists of a flexible noncyclic application of programming that converts individual planning to a satisfactory method for management of the complexities of nursing program. For creating a specific timing and setting appointment for each nurse in the specific time interval, some patterns and models should be provided including number of nurses, working hours and number of days determined for scheduling. Working appointments for a complete day is divided in 3 parts based on the scheduling program for each nurse which puts him or her in one of these three sections, as every day has a special schedule. Usually, for uniform distribution of working sources during a week, the first criteria is taken by conversion of individual s scheduling trend as the firs cost function. The number of nurses per shift varies according to different working hours in the day. Determination of the number of nurses per shift is taken by the administrator or supervisor first. To determine the working hours of nurses, some series of personal or business features are considered including profession and gender. These characteristics are very important in determining the appointment orders. This structure is called as the compatibility or non-compatibility of any nurse in relation to another one. In order to provide a mathematical model to determine the relationship between nurses for setting appointments, the adjacency matrix is used. The adjacency matrix is defined as a matrix with the equal number of rows and columns. Adjacency matrix has unique feature. It is known that all the elements of the main diagonal value are equal to zero. In an adjacency matrix, if the numerical value of the first row, second column is equal to one, for sure, it is clear that the numerical value of the second row, first column is also equal to one. In this part, number of each row and each column represents a person who is naturally considered to be a number. When the value of an element is equal to one, it means that two nurses have nothing to do with each other and 8197
4 cannot turn on a work plan or be connected simultaneously. Finally, the adjacency matrix is used for creating graphs. Then coloring is taken regarding the graph coloring properties and use of Simulated Annealing Algorithm. There is an unique adjacency matrix (alone) for each graph and there is not any adjacent for any two matrix. According to an adjacency matrix that shows the relationship between nurses actually one graph is achieved. Then the chromatic number obtains according to the graph coloring. The more accurate graph coloring, the more efficient number of nurses who are working in a same shift. Nurses are grouped here and the fewer number of colors used for coloring is preferred. This algorithm acts as a group to be neutral. The first group starts in this way and blank nodes take any color, respectively. The fitness function is used for optimization of graph coloring. The lower chromatic number the more optimized fitness function. Heuristic algorithms are both discrete and continuous. Discrete types are such as genetic algorithms, particle and of ant algorithms. In these types of algorithms first the answers are created and from the first in algorithm, the chromatic number is obtained and then multiplied by the number of errors existed in edges. Errors are so that for example if 3 1nd 1 nodes are connected in the graph, both of them in the same color (red), that is considered as an error. In the simulation, each nurse is considered as a node in the graph. Figure 1 shows how to paint nodes in the graph by the algorithm SA, with minimum 3 different colors. As shown in Table 1 after running the program, according to the number of nurses that has been determined in the first row, fitness value was determined for cooling algorithm (SA) and Genetic Algorithm (GA). If the target number is lower than fitness function, it is would be optimal. Once five nurses are considered, the fitness value of both will be the same for each algorithm. Of course, this case stands for a total of people, but when the number 20 is considered, the fitness value of Simulated Annealing Algorithm (SA) function is less than genetic algorithm (GA), and this trend also stands for higher categorization of nurses. In the case of nurses categorization, results are shown in Table 2 after running the program. Table 2: number of formed groups in relation to the number of nurses. Nurse SA GA About the laws that included in routine programs, the nurses attended in the night shift, will not be involved completely in the next day shift. Also always the working conditions are not the same necessarily for all nurses who work in a hospital. Some of the nurses can be considered as alternative for replacement. In this part, some tests are taken on the working procedure and finally took the best of the simulated case will be shown. The number of nurses in the morning shift 5 people The number of nurses in the evening shift 4 people The number of nurses in the night shift 3 people The total number of considered nurses 20 people The program was run according to the above conditions and results are listed in Table 3. Table 3: Colors considered for each node (nurse) in SA algorithm Figure 1: Graph coloring with nodes by SA algorithm THE RESULTS OF THE SIMULATION Among the objectives concerned by the project, it is to minimize the error with lower chromatic number. Fitness function will be derived by multiplied chromatic number with the number of errors. After running the program, fitness value compared to the number of number of nurses was obtained as results can be seen in Table 1. Nurse SA GA Table 1: Fitness value in relation to the nurses N. Nurse Color Graph According to Table 3, each nurse represents a node of graph, representing a color by the specified number. Number of figures shows a specific color. G1=1, 2, 7, 14, G2=3, 19, G3=5, 9, 17, 20, G4=, 16, 18, G5=11, 12, 13, GB=8, 6, 15, 4, According to the above equation Gn represents the grouping of the colors, as each group has a special color. For example, in the group G1 nurses who hold the number 1, 2,7,14 have 16 colors. GB shows the neutral node. Neutral nodes will have the effect on the fitness function. GB can be in any color. The value of fitness function in this mode is equal to for 8198
5 cooling algorithm of metals. The number of errors is zero and its chromatic number is equal to 5. Weekly planning and appointments to any nurse is taken by SA as shown in the Table 4. Table 4: Nurses shift schedule during a week by GA Saturday N M E - N - M E M E - - M M - E N Sunday O N M E O E M E M M - - N N E M O Monday N O M E N E M E M M - - O O E M N Tuesday O N M E O E M E M M - - N N E M O Wednesday N O M E N E M E M M - - O O E M N Thursday O N M E O E M E M M - - N N E M O Friday N O M E N E M E M M - - O O E M N As shown in Table 4, programming was taken for 20 nurses during a week. The letter N refers to night shift, the letter E means afternoon shift, the letter M stands for the morning shift and the letter O is also used to be the rest time for the mode nurse. Number of nurses was assigned from 1 to 20. As shown in the table, the nurse No.1 is shifted at night for Saturday, while Sunday is considered as the rest day. This programming is suggested by SA algorithm. This case was also done by genetic algorithms resulted in Tables 5 and 6. The value of fitting function in this case for the GA was Number of errors was zero while the chromatic No. was 7. Also grouping of the colours was as shown below: G1=1, 6, G2=2, 11, 12, 14, 18, G3=5, 15, G4=, 17, G5=16, 19, 20, GB=13, 7, 9, 8, Table 5: Colors considered for each node (nurse) in GA Color Graph Table 6: Nurses appointments during a week by GA X N M - - E N E - E - M M N M E - - M - - As shown in Table 6, appointments of the 20 nurses were taken just in one day which is practically out of the program application trend. That happened because of the formed grouping by genetics algorithm. CONCLUSIONS This study was conducted to adjust the working hours of nurses using graph coloring and Simulated Annealing Algorithm. The project was applicable and aimed to design the Plan designed based on the data derived from shift programs and interviews with nurse managers in the hospital. Data analysis has been taken by converting the process of planning of the experts into the mathematical and programming function by Simulated Annealing Algorithm using the C # programming language. The results showed that problems of shifts and programming are especially proper to be solved by Simulated Annealing Algorithm. Results obtained in this project indicated a high-performance of SA algorithm in solving the nursing shifts problems compared to that of genetic algorithm in this respect. REFERENCES [1] Bahadorani, Solving the problem of graph coloring with genetic algorithm. First National Conference on application of intelligent systems in Science and Technology, Azad University, Quchan Branch, [2] A. Darvish. The design of intelligent systems of regulation of nursing schedules using genetic algorithms. Journal of Nursing and Midwifery, Tehran University of Medical Sciences (Haayat),Vol. 15, No. 2, pp , [3] M. A. Bozorgzadh. The use of evolutionary algorithms with double chromosome structure for solving graph coloring problems, the first conference of fuzzy and intelligent systems, Ferdowsi University of Mashhad, [4] M. Shahsavar. The optimum design of genetic algorithms with statistical approaches, the National Conference of data security, Qazvin University, [5] H. Yarmohammadi. The new algorithm for metals cooling by dynamic type, for global optimization, The third National Conference of Metaheuristic and its application in Science and Engineering, Azad University of Fereydunkenar, [6] C. Maier, H. Wolfe. Cyclical Scheduling and Allocation of Nursing staff. Socio Economic Planning Sciences, vol. 7, pp , [7] S. Siferd, W. Benton. Workforce Staffing and Scheduling Hospital Nursing Specific Models. European Journal of Operational Research, Vol. 60, No. 3, pp , 20. [8] A. Neri. Application of Imperialist Competitive Algorithm in Online PI Controller. IEEE, Second International Conference on Intelligent Systems, Modelling and Simulation, Vol. 87, No. 2, pp , [9] R. Dorne, J. Hao. A new genetic local search algorithm for graph coloring, in Parallel Problem Solving From Nature V. Amsterdam, The Netherlands: N. Holland, 1498, pp [] W. M. Hancock. A heuristic approach to nurse scheduling in hospital units with non stationary, urgent demand, and a fixed staff size. J Soc Health Syst, Vol. 2, No. 2, pp , [11] B. Chen, G. Wornell. Object-oriented implementation of heurestic search methods for graph coloring, maximum clique, and satisfiabilit", Proceedings of the 2nd DIMACS implementation challenge, Series in Discrete Mathematical and Theoretical Computer Science, vol. 26, pp ,
A Generic Two-Phase Stochastic Variable Neighborhood Approach for Effectively Solving the Nurse Rostering Problem
Algorithms 2013, 6, 278-308; doi:10.3390/a6020278 Article OPEN ACCESS algorithms ISSN 1999-4893 www.mdpi.com/journal/algorithms A Generic Two-Phase Stochastic Variable Neighborhood Approach for Effectively
More informationNursing Manpower Allocation in Hospitals
Nursing Manpower Allocation in Hospitals Staff Assignment Vs. Quality of Care Issachar Gilad, Ohad Khabia Industrial Engineering and Management, Technion Andris Freivalds Hal and Inge Marcus Department
More informationPlanning Calendar Grade 5 Advanced Mathematics. Monday Tuesday Wednesday Thursday Friday 08/20 T1 Begins
Term 1 (42 Instructional Days) 2018-2019 Planning Calendar Grade 5 Advanced Mathematics Monday Tuesday Wednesday Thursday Friday 08/20 T1 Begins Policies & Procedures 08/21 5.3K - Lesson 1.1 Properties
More informationMaximizing the nurses preferences in nurse scheduling problem: mathematical modeling and a meta-heuristic algorithm
J Ind Eng Int (2015) 11:439 458 DOI 10.1007/s40092-015-0111-0 ORIGINAL RESEARCH Maximizing the nurses preferences in nurse scheduling problem: mathematical modeling and a meta-heuristic algorithm Hamed
More informationHow to deal with Emergency at the Operating Room
How to deal with Emergency at the Operating Room Research Paper Business Analytics Author: Freerk Alons Supervisor: Dr. R. Bekker VU University Amsterdam Faculty of Science Master Business Mathematics
More informationProceedings of the 2005 Systems and Information Engineering Design Symposium Ellen J. Bass, ed.
Proceedings of the 2005 Systems and Information Engineering Design Symposium Ellen J. Bass, ed. ANALYZING THE PATIENT LOAD ON THE HOSPITALS IN A METROPOLITAN AREA Barb Tawney Systems and Information Engineering
More informationImproving Patient s Satisfaction at Urgent Care Clinics by Using Simulation-based Risk Analysis and Quality Improvement
MPRA Munich Personal RePEc Archive Improving Patient s Satisfaction at Urgent Care Clinics by Using Simulation-based Risk Analysis and Quality Improvement Sahar Sajadnia and Elham Heidarzadeh M.Sc., Industrial
More informationA Preliminary Study into the Use of an Evolutionary Algorithm Hyper-heuristic to Solve the Nurse Rostering Problem
A Preliminary Study into the Use of an Evolutionary Algorithm Hyper-heuristic to Solve the Nurse Rostering Problem Christopher Rae School of Mathematics, Statistics & Computer Science University of KwaZulu-Natal
More informationQuality Management Building Blocks
Quality Management Building Blocks Quality Management A way of doing business that ensures continuous improvement of products and services to achieve better performance. (General Definition) Quality Management
More informationCITY OF GRANTS PASS SURVEY
CITY OF GRANTS PASS SURVEY by Stephen M. Johnson OCTOBER 1998 OREGON SURVEY RESEARCH LABORATORY UNIVERSITY OF OREGON EUGENE OR 97403-5245 541-346-0824 fax: 541-346-5026 Internet: OSRL@OREGON.UOREGON.EDU
More informationStaffing and Scheduling
Staffing and Scheduling 1 One of the most critical issues confronting nurse executives today is nurse staffing. The major goal of staffing and scheduling systems is to identify the need for and provide
More information27A: For the purposes of the BAA, a non-u.s. individual is an individual who is not a citizen of the U.S. See Section III.A.2 of the BAA.
HR001117S0039 Lagrange BAA Frequently Asked Questions (FAQs) (as of 08/17/17) The Proposers Day webcast may be viewed by clicking on the Proposers Day Slides link under the Lagrange BAA on the DARPA/DSO
More informationA Greedy Double Swap Heuristic for Nurse Scheduling
A Greedy Double Swap Heuristic for Nurse Scheduling Murphy Choy 1 and Michelle Cheong Singapore Management University, School of Information System 80 Stamford Road, Singapore 178902 Email: murphychoy@smu.edu.sg;
More informationAn Investigation into the Effect of Mcclelland Motivational Factors on Productivity Including the Employed Nurses in Ahwaz Medical Education Hospitals
An Investigation into the Effect of Mcclelland Motivational Factors on Including the Employed Nurses in Ahwaz Medical Education Hospitals 148 Karamollah Daneshfard, MA Student of Public Management, Management
More informationThe Hashemite University- School of Nursing Master s Degree in Nursing Fall Semester
The Hashemite University- School of Nursing Master s Degree in Nursing Fall Semester Course Title: Statistical Methods Course Number: 0703702 Course Pre-requisite: None Credit Hours: 3 credit hours Day,
More informationOptimization of Hospital Layout through the Application of Heuristic Techniques (Diamond Algorithm) in Shafa Hospital (2009)
Int. J. Manag. Bus. Res., 1 (3), 133-138, Summer 2011 IAU Motaghi et al. Optimization of Hospital Layout through the Application of Heuristic Techniques (Diamond Algorithm) in Shafa Hospital (2009) 1 M.
More informationHome Health Care: A Multi-Agent System Based Approach to Appointment Scheduling
Home Health Care: A Multi-Agent System Based Approach to Appointment Scheduling Arefeh Mohammadi, Emmanuel S. Eneyo Southern Illinois University Edwardsville Abstract- This paper examines the application
More informationPANELS AND PANEL EQUITY
PANELS AND PANEL EQUITY Our patients are very clear about what they want: the opportunity to choose a primary care provider access to that PCP when they choose a quality healthcare experience a good value
More informationThe Nottingham eprints service makes this work by researchers of the University of Nottingham available open access under the following conditions.
Li, Jingpeng and Aickelin, Uwe (2003) 'A Bayesian Optimisation Algorithm for the urse Scheduling Problem'. In: The 2003 Congress for Evolutionary Computation, 2003, Canberra, Australia. Access from the
More informationGeneral Practice Extended Access: March 2018
General Practice Extended Access: March 2018 General Practice Extended Access March 2018 Version number: 1.0 First published: 3 May 2017 Prepared by: Hassan Ismail, Data Analysis and Insight Group, NHS
More informationStimulation of medical decision expert system by using of time color Petri net method
IJCSI Internal Journal Computer Sci Issues, Vol. 9, Issue 3, No 2, May 2012 www.ijcsi.org 382 Stimul medical decision expert system by using color Petri net method 1 Neda Darvish, 2 Khikmat.Kh.Muminov,
More informationITT Technical Institute. HT201 Health Care Statistics Onsite Course SYLLABUS
ITT Technical Institute HT201 Health Care Statistics Onsite Course SYLLABUS Credit hours: 4 Contact/Instructional hours: 40 (40 Theory Hours) Prerequisite(s) and/or Corequisite(s): Prerequisites: GE127
More informationCall for Posters. Deadline for Submissions: May 15, Washington, DC Gaylord National Harbor Hotel October 18 21, 2015
Call for Posters Washington, DC Gaylord National Harbor Hotel October 18 21, 2015 Deadline for Submissions: May 15, 2015 APhA is the official education provider and meeting manager of JFPS 2015. 15-123
More informationAutomatically Recommending Healthy Living Programs to Patients with Chronic Diseases through Hybrid Content-Based and Collaborative Filtering
2014 IEEE International Conference on Bioinformatics and Biomedicine Automatically Recommending Healthy Living Programs to Patients with Chronic Diseases through Hybrid Content-Based and Collaborative
More informationAPPLICATION OF SIMULATION MODELING FOR STREAMLINING OPERATIONS IN HOSPITAL EMERGENCY DEPARTMENTS
APPLICATION OF SIMULATION MODELING FOR STREAMLINING OPERATIONS IN HOSPITAL EMERGENCY DEPARTMENTS Igor Georgievskiy Alcorn State University Department of Advanced Technologies phone: 601-877-6482, fax:
More informationCase Study. Check-List for Assessing Economic Evaluations (Drummond, Chap. 3) Sample Critical Appraisal of
Case Study Work in groups At most 7-8 page, double-spaced, typed critical appraisal of a published CEA article Start with a 1-2 page summary of the article, answer the following ten questions, and then
More informationCOST BEHAVIOR A SIGNIFICANT FACTOR IN PREDICTING THE QUALITY AND SUCCESS OF HOSPITALS A LITERATURE REVIEW
Allied Academies International Conference page 33 COST BEHAVIOR A SIGNIFICANT FACTOR IN PREDICTING THE QUALITY AND SUCCESS OF HOSPITALS A LITERATURE REVIEW Teresa K. Lang, Columbus State University Rita
More informationTHE USE OF SIMULATION TO DETERMINE MAXIMUM CAPACITY IN THE SURGICAL SUITE OPERATING ROOM. Sarah M. Ballard Michael E. Kuhl
Proceedings of the 2006 Winter Simulation Conference L. F. Perrone, F. P. Wieland, J. Liu, B. G. Lawson, D. M. Nicol, and R. M. Fujimoto, eds. THE USE OF SIMULATION TO DETERMINE MAXIMUM CAPACITY IN THE
More informationFinal Report. Karen Keast Director of Clinical Operations. Jacquelynn Lapinski Senior Management Engineer
Assessment of Room Utilization of the Interventional Radiology Division at the University of Michigan Hospital Final Report University of Michigan Health Systems Karen Keast Director of Clinical Operations
More informationAn analysis of the average waiting time during the patient discharge process at Kashani Hospital in Esfahan, Iran: a case study
An analysis of the average waiting time during the patient discharge process at Kashani Hospital in Esfahan, Iran: a case study Sima Ajami and Saeedeh Ketabi Abstract Strategies for improving the patient
More informationConflict-Handling Modes of Vocational Health Occupations Teachers, Nursing Supervisors and Staff Development Personnel
Journal of Health Occupations Education Volume 2 Number 2 Article 5 1987 Conflict-Handling Modes of Vocational Health Occupations Teachers, Nursing Supervisors and Staff Development Personnel Lou J. Ebrite
More informationDo hospitals react to random demand pressure by early discharges?
Do hospitals react to random demand pressure by early discharges? Filipa Albano Pedro Pita Barros NOVA School of Business and Economics STATA User Group Meeting Lisbon 2012 2 Outline Motivation; The Negative
More information1 Numbers in Healthcare
1 Numbers in Healthcare Practice This chapter covers: u The regulator s requirements u Use of calculators and approximation u Self-assessment u Revision of numbers 4 Healthcare students and practitioners
More informationDWA Standard APEX Key Glencoe
CA Standard 1.0 DWA Standard APEX Key Glencoe 1.0 Students solve equations and inequalities involving absolute value. Introductory Algebra Core Unit 03: Lesson 01: Activity 01: Study: Solving x = b Unit
More informationMethicillin resistant Staphylococcus aureus transmission reduction using Agent-Based Discrete Event Simulation
Methicillin resistant Staphylococcus aureus transmission reduction using Agent-Based Discrete Event Simulation Sean Barnes PhD Student, Applied Mathematics and Scientific Computation Department of Mathematics
More informationBegin Implementation. Train Your Team and Take Action
Begin Implementation Train Your Team and Take Action These materials were developed by the Malnutrition Quality Improvement Initiative (MQii), a project of the Academy of Nutrition and Dietetics, Avalere
More informationOrganizational Communication in Telework: Towards Knowledge Management
Association for Information Systems AIS Electronic Library (AISeL) PACIS 2001 Proceedings Pacific Asia Conference on Information Systems (PACIS) December 2001 Organizational Communication in Telework:
More informationReport on the Pilot Survey on Obtaining Occupational Exposure Data in Interventional Cardiology
Report on the Pilot Survey on Obtaining Occupational Exposure Data in Interventional Cardiology Working Group on Interventional Cardiology (WGIC) Information System on Occupational Exposure in Medicine,
More informationGoals of System Modeling:
Goals of System Modeling: 1. To focus on important system features while downplaying less important features, 2. To verify that we understand the user s environment, 3. To discuss changes and corrections
More informationSimulated Metamorphosis - A Novel Optimizer
, 22-24 October, 2014, San Francisco, USA Simulated Metamorphosis - A vel Optimizer Michael Mutingi, Charles Mbohwa Abstract This paper presents a novel metaheuristic algorithm, simulated metamorphosis
More informationCourse Syllabus. Web Page: Textbooks can be purchased at the Campus Bookstore or online at
Course Syllabus Course: MAT240 (Multivariable Calculus) Semester: Spring 2012 Section: 35289 Day(s): MW Time: 10:55AM-1:05PM Location: CM-454 Meeting Dates: January 18 May 11 INSTRUCTOR Name: Christopher
More informationHEALTH WORKFORCE SUPPLY AND REQUIREMENTS PROJECTION MODELS. World Health Organization Div. of Health Systems 1211 Geneva 27, Switzerland
HEALTH WORKFORCE SUPPLY AND REQUIREMENTS PROJECTION MODELS World Health Organization Div. of Health Systems 1211 Geneva 27, Switzerland The World Health Organization has long given priority to the careful
More informationPublished by: PIONEER RESEARCH & DEVELOPMENT GROUP ( 32
Real Time Patient Monitoring System Via Ecg Signal Using GSM Network: A Preliminary Study Mohammed F. Alsharekh 1, Anwar Hassan Ibrahim 2, Muhammad Islam 3, Asim Aziz 4 1 Electical Engineering, Unaizah
More informationYale University 2017 Transportation Survey Report February 2018
Walking and riding trollies to Yale Bowl for a football game. Photo courtesy of Yale University. Yale University 2017 Transportation Survey Report February 2018 A campus-wide transportation survey was
More informationInternational Conference on Management Science and Innovative Education (MSIE 2015)
International Conference on Management Science and Innovative Education (MSIE 2015) The Critical Success Factors of Biotechnology and Pharmaceutical Industry in SIAT---Integration Entrepreneur, Entrepreneurial
More informationDISTRICT BASED NORMATIVE COSTING MODEL
DISTRICT BASED NORMATIVE COSTING MODEL Oxford Policy Management, University Gadjah Mada and GTZ Team 17 th April 2009 Contents Contents... 1 1 Introduction... 2 2 Part A: Need and Demand... 3 2.1 Epidemiology
More informationNinth National GP Worklife Survey 2017
Ninth National GP Worklife Survey 2017 Jon Gibson 1, Matt Sutton 1, Sharon Spooner 2 and Kath Checkland 2 1. Manchester Centre for Health Economics, 2. Centre for Primary Care Division of Population Health,
More informationHOW TO USE THE WARMBATHS NURSING OPTIMIZATION MODEL
HOW TO USE THE WARMBATHS NURSING OPTIMIZATION MODEL Model created by Kelsey McCarty Massachussetts Insitute of Technology MIT Sloan School of Management January 2010 Organization of the Excel document
More informationSurgery Scheduling with Recovery Resources
Surgery Scheduling with Recovery Resources Maya Bam 1, Brian T. Denton 1, Mark P. Van Oyen 1, Mark Cowen, M.D. 2 1 Industrial and Operations Engineering, University of Michigan, Ann Arbor, MI 2 Quality
More informationGantt Chart. Critical Path Method 9/23/2013. Some of the common tools that managers use to create operational plan
Some of the common tools that managers use to create operational plan Gantt Chart The Gantt chart is useful for planning and scheduling projects. It allows the manager to assess how long a project should
More informationFEASIBILITY STUDY ON ACADEMICAL ENTREPRENEURSHIP ENGLISH FROM THE VIEWPOINT OF SCHOLARS AND STUDENTS OF ISLAMIC AZAD UNIVERSITY OF ISFAHAN
FEASIBILITY STUDY ON ACADEMICAL ENTREPRENEURSHIP ENGLISH FROM THE VIEWPOINT OF SCHOLARS AND STUDENTS OF ISLAMIC AZAD UNIVERSITY OF ISFAHAN Sadighe Solaymanipoor 1, Zohre Saadatmand (PhD) 2 1 Department
More informationConnecting Inpatient and Residential Treatment to Systems of Care
0th Annual RTC Conference Presented in Tampa, March 007 Connecting Inpatient and Residential Treatment to Systems of Care Mary Armstrong, Ph.D., Norín Dollard, Ph.D., Stephanie Romney, Ph.D., Keren S.
More informationDecreasing Environmental Services Response Times
Decreasing Environmental Services Response Times Murray J. Côté, Ph.D., Associate Professor, Department of Health Policy & Management, Texas A&M Health Science Center; Zach Robison, M.B.A., Administrative
More informationUnemployment. Rongsheng Tang. August, Washington U. in St. Louis. Rongsheng Tang (Washington U. in St. Louis) Unemployment August, / 44
Unemployment Rongsheng Tang Washington U. in St. Louis August, 2016 Rongsheng Tang (Washington U. in St. Louis) Unemployment August, 2016 1 / 44 Overview Facts The steady state rate of unemployment Types
More informationInstructions for National Science Foundation (NSF)-style proposals
Comprehensive Examination Oral Examination: Proposal Defense Department of Physics and Astronomy Instructions for National Science Foundation (NSF)-style proposals Prepare the proposal as if you will be
More informationSwarm Intelligence: Charged System Search
Swarm Intelligence: Charged System Search Intelligent Robotics Seminar Alireza Mollaalizadeh Bahnemiri 15. December 2014 Alireza M.A. Bahnemiri Swarm Intelligence: CSS 1 Content What is Swarm Intelligence?
More information3. Does the institution have a dedicated hospital-wide committee geared towards the improvement of laboratory test stewardship? a. Yes b.
Laboratory Stewardship Checklist: Governance Leadership Commitment It is extremely important that the Laboratory Stewardship Committee is sanctioned by the hospital leadership. This may be recognized by
More informationEXECUTIVE SUMMARY. Introduction. Methods
EXECUTIVE SUMMARY Introduction University of Michigan (UM) General Pediatrics offers health services to patients through nine outpatient clinics located throughout South Eastern Michigan. These clinics
More informationIntelligence. Intelligence. Workload forecasting with Cerner Clairvia. Workload forecasting with Cerner Clairvia
Intelligence Intelligence Workload forecasting with Cerner Clairvia Workload forecasting with Cerner Clairvia Better patient outcomes occur when you have the right care giver, in the right place, at the
More informationRESEARCH METHODOLOGY
Research Methodology 86 RESEARCH METHODOLOGY This chapter contains the detail of methodology selected by the researcher in order to assess the impact of health care provider participation in management
More informationDesign of a Grant Proposal Development System Proposal Process Enhancement and Automation
Design of a Grant Proposal Development System 1 Design of a Grant Proposal Development System Proposal Process Enhancement and Automation Giselle Sombito, Pranav Sikka, Jeffrey Prindle, Christian Yi George
More informationNursing and Midwifery Rostering. Policy. Asst. Director of Nursing, Workforce Planning. & Modernisation. Directorate of Primary Care and Older.
Policy Title Nursing and Midwifery Rostering Policy Policy Reference Number PrimCare11/01 Implementation Date January 2011 Review Date January 2013 Responsible Officer Asst. Director of Nursing, Workforce
More informationThe impact of nurses' empowerment and decision-making on the care quality of patients in healthcare reform plan
International Academic Institute for Science and Technology International Academic Journal of Organizational Behavior and Human Resource Management Vol. 2, No. 9, 2015, pp. 33-39. ISSN 2454-2210 International
More informationA Study on the Satisfaction of Residents in Wuhan with Community Health Service and Its Influence Factors Xiaosheng Lei
4th International Education, Economics, Social Science, Arts, Sports and Management Engineering Conference (IEESASM 2016) A Study on the Satisfaction of Residents in Wuhan with Community Health Service
More information2-5 December 2012 Bangkok, Thailand. Edited by. Voratas Kachitvichyanukul Huynh Trung Luong Rapeepun Pitakaso
Proceedings of Abstracts and Papers (on CD-ROM) of The 13 th Asia Pacific Industrial ngineering and Management Systems Conference 2012 and the 1 Asia Pacific Division Meeting of the International Foundation
More informationPaper Getting to Know the No-Show: Predictive Modeling of Missing a Medical Appointment
Paper 3603-2018 Getting to Know the No-Show: Predictive Modeling of Missing a Medical Appointment ABSTRACT Joe Lorenz and Kayla Hawkins, Grand Valley State University Patients not showing up for appointments,
More informationRETAIL INDUSTRY AWARD STATE TO FOOD, BEVERAGE AND TOBACCO MANUFACTURING AWARD 2010 (AN to MA000073)
These summaries are for members only. Please do not download these documents and pass them on to other bakeries as they may not apply to their business. These summaries have intellectual property. By distributing
More informationAn Indirect Genetic Algorithm for a Nurse Scheduling Problem
An Indirect Genetic Algorithm for a Nurse Scheduling Problem Computers & Operations Research, 31(5), pp 761-778, 2004. Uwe Aickelin School of Computer Science University of Nottingham NG8 1BB UK uxa@cs.nott.ac.uk
More informationNHS Dental Services Quarterly Vital Signs Reports
NHS Dental Services Quarterly Vital Signs Reports Dental Services Gateway ref: NHSBSA/DSD/0008 Introduction The NHS Dental Services (NHS DS) has been working closely with the Department of Health (DH)
More informationCourse Instructor Karen Migl, Ph.D, RNC, WHNP-BC
Stephen F. Austin State University DeWitt School of Nursing RN-BSN RESEARCH AND APPLICATION OF EVIDENCE BASED PRACTICE SYLLABUS Course Number: NUR 439 Section Number: 501 Clinical Section Number: 502 Course
More informationThe adult social care sector and workforce in. North East
The adult social care sector and workforce in 2015 Published by Skills for Care, West Gate, 6 Grace Street, Leeds LS1 2RP www.skillsforcare.org.uk Skills for Care 2016 Copies of this work may be made for
More informationuncovering key data points to improve OR profitability
REPRINT March 2014 Robert A. Stiefel Howard Greenfield healthcare financial management association hfma.org uncovering key data points to improve OR profitability Hospital finance leaders can increase
More informationSalvo Model for Anti-Surface Warfare Study
Salvo Model for Anti-Surface Warfare Study Ed Hlywa Weapons Analysis LLC In the late 1980 s Hughes brought combat modeling into the missile age by developing an attrition model inspired by the exchange
More informationApplication of Value Engineering to Improve Discharging Procedure in Healthcare Centers (Case Study: Amini Hospital, Langroud, Iran)
International Journal of Engineering Management 2017; 1(1): 1-10 http://www.sciencepublishinggroup.com/j/ijem doi: 10.11648/j.ijem.20170101.11 Application of Value Engineering to Improve Discharging Procedure
More informationCost Sharing. Cost Sharing. ERS provides a facility to easily enable and track multiple certifications on Effort Reports.
Cost Sharing ERS provides a facility to easily enable and track multiple certifications on Effort Reports. Typically, Department Administrators or certifiers are responsible for activating this feature.
More informationResearch on the command mode of ship formation cooperative engagement under the network condition
Advanced Materials Research Online: 2014-02-06 ISSN: 1662-8985, Vols. 889-890, pp 1222-1226 doi:10.4028/www.scientific.net/amr.889-890.1222 2014 Trans Tech Publications, Switzerland Research on the command
More informationUNITED STATES PATENT AND TRADEMARK OFFICE The Patent Hoteling Program Is Succeeding as a Business Strategy
UNITED STATES PATENT AND TRADEMARK OFFICE The Patent Hoteling Program Is Succeeding as a Business Strategy FINAL REPORT NO. OIG-12-018-A FEBRUARY 1, 2012 U.S. Department of Commerce Office of Inspector
More informationComparing Job Expectations and Satisfaction: A Pilot Study Focusing on Men in Nursing
American Journal of Nursing Science 2017; 6(5): 396-400 http://www.sciencepublishinggroup.com/j/ajns doi: 10.11648/j.ajns.20170605.14 ISSN: 2328-5745 (Print); ISSN: 2328-5753 (Online) Comparing Job Expectations
More informationWaiting Patiently. An analysis of the performance aspects of outpatient scheduling in health care institutes
Waiting Patiently An analysis of the performance aspects of outpatient scheduling in health care institutes BMI - Paper Anke Hutzschenreuter Vrije Universiteit Amsterdam Waiting Patiently An analysis of
More informationA Deterministic Approach to Nurse Rerostering Problem
A Deterministic Approach to Nurse Rerostering Problem Saangyong Uhmn 1, Young-Woong Ko 2 and Jin Kim 3,* 1,2,3 Department of Computer Engineering, Hallym University, Chuncheon, 24252, Republic of Korea.
More informationPrimary Care Workforce Survey 2013
Experimental Report Primary Care Workforce Survey 2013 Out of Hours GP Services Strand Sections 1,2,3 and 6 Publication Date 19 November 2013 Contents Introduction... 2 Method of completing the survey...
More informationQUEUING THEORY APPLIED IN HEALTHCARE
QUEUING THEORY APPLIED IN HEALTHCARE This report surveys the contributions and applications of queuing theory applications in the field of healthcare. The report summarizes a range of queuing theory results
More informationNorth Carolina. CAHPS 3.0 Adult Medicaid ECHO Report. December Research Park Drive Ann Arbor, MI 48108
North Carolina CAHPS 3.0 Adult Medicaid ECHO Report December 2016 3975 Research Park Drive Ann Arbor, MI 48108 Table of Contents Using This Report 1 Executive Summary 3 Key Strengths and Opportunities
More informationComparing Two Rational Decision-making Methods in the Process of Resignation Decision
Comparing Two Rational Decision-making Methods in the Process of Resignation Decision Chih-Ming Luo, Assistant Professor, Hsing Kuo University of Management ABSTRACT There is over 15 percent resignation
More informationBMA quarterly tracker survey
BMA quarterly tracker survey Current views from across the medical profession Quarter 3: July 2015 Background The BMA s Health Policy and Economic Research Unit (HPERU) manages an online panel of approximately
More informationBAPTIST HEALTH SCHOOLS LITTLE ROCK-SCHOOL OF NURSING NSG 4027: PROFESSIONAL ROLES IN NURSING PRACTICE
BAPTIST HEALTH SCHOOLS LITTLE ROCK-SCHOOL OF NURSING NSG 4027: PROFESSIONAL ROLES IN NURSING PRACTICE M1 ORGANIZATION PROCESSES AND DIVERSIFIED HEALTHCARE DELIVERY 2007 LECTURE OBJECTIVES: 1. Analyze economic,
More informationA STOCHASTIC APPROACH TO NURSE STAFFING AND SCHEDULING PROBLEMS
A STOCHASTIC APPROACH TO NURSE STAFFING AND SCHEDULING PROBLEMS Presented by Sera Kahruman & Elif Ilke Gokce Texas A&M University INEN 689-60 Outline Problem definition Nurse staffing problem Literature
More informationA Balanced Scorecard Approach to Determine Accreditation Measures with Clinical Governance Orientation: A Case Study of Sarem Women s Hospital
A Balanced Scorecard Approach to Determine Accreditation Measures with Clinical Governance Orientation: A Case Study of Sarem Women s Hospital Abbas Kazemi Islamic Azad University Sajjad Shokohyand Shahid
More informationImproving patient access to general practice
Report by the Comptroller and Auditor General Department of Health and NHS England Improving patient access to general practice HC 913 SESSION 2016-17 11 JANUARY 2017 4 Key facts Improving patient access
More informationOptimizing the planning of the one day treatment facility of the VUmc
Research Paper Business Analytics Optimizing the planning of the one day treatment facility of the VUmc Author: Babiche de Jong Supervisors: Marjolein Jungman René Bekker Vrije Universiteit Amsterdam Faculty
More informationA Hybrid Heuristic Ordering and Variable Neighbourhood Search for the Nurse Rostering Problem
School of Computer Science and Information Technology University of Nottingham Jubilee Campus NOTTINGHAM NG8 1BB, UK Computer Science Technical Report No. NOTTCS-TR-2005-9 A Hybrid Heuristic Ordering and
More informationSIMULATION FOR OPTIMAL UTILIZATION OF HUMAN RESOURCES IN SURGICAL INSTRUMENTS DISTRIBUTION IN HOSPITALS
SIMULATION FOR OPTIMAL UTILIZATION OF HUMAN RESOURCES IN SURGICAL INSTRUMENTS DISTRIBUTION IN HOSPITALS Arun Kumar School of Mechanical & Production Engineering, Nanyang Technological University, Singapore
More informationSpecialty Care System Performance Measures
Specialty Care System Performance Measures The basic measures to gauge and assess specialty care system performance include measures of delay (TNA - third next available appointment), demand/supply/activity
More informationGeneral Practice Extended Access: September 2017
General Practice Extended Access: September 2017 General Practice Extended Access September 2017 Version number: 1.0 First published: 31 October 2017 Prepared by: Hassan Ismail, NHS England Analytical
More informationModels for Bed Occupancy Management of a Hospital in Singapore
Proceedings of the 2010 International Conference on Industrial Engineering and Operations Management Dhaka, Bangladesh, January 9-10, 2010 Models for Bed Occupancy Management of a Hospital in Singapore
More informationGP Allocation of Non- Personnel Costs to Grants
Procedure: Policy: Number: Allowable Uses of Funds and Adherence to Cost Circulars GP0800.3 Allocation of Non- Personnel Costs to Grants ( ) Complete Revision Supersedes: Page: ( ) Partial Revision Page
More informationMost surgical facilities in the US perform all
ECONOMICS AND HEALTH SYSTEMS RESEARCH SECTION EDITOR RONALD D. MILLER Changing Allocations of Operating Room Time From a System Based on Historical Utilization to One Where the Aim is to Schedule as Many
More informationThe Study of Students Entrepreneurial Orientation According to the Knowledge, Attitude and Entrepreneurial Capabilities
JOURNAL OF APPLIED SCIENCES RESEARCH ISSN: 1819-544X Published BY AENSI Publication EISSN: 1816-157X http://www.aensiweb.com/jasr 2016 March; 12(3): pages 106-111 Open Access Journal The Study of Students
More informationFamily Service Practice Audit
Northeast Service Delivery Area Family Service Practice Audit Report Completed: June 2014 Office of the Provincial Director of Child Welfare and Aboriginal Services Quality Assurance Branch Table of Contents
More informationQuality and Equality Integrated Impact Assessment Policy
Subject: Quality and Equality Integrated Impact Assessment Policy Meeting: NHS MK CCG Shadow Board Date of Meeting: 2 October 2012 Report of: Alison Jamson, NHSMK&N Introduction NHS Milton Keynes Clinical
More information