Career intensity of patients in a hospital”. I

Career Episode 2:  Introduction: 2.1. The subject of the second career episode is ‘Balancing the intensity of patients in a hospital”. I worked on this project for 5 months from February 2011 to June 2011. The successful execution of the project was necessary for the completion of my Bachelor in Industrial Engineering from Eski?ehir Osmangazi University, Eski?ehir, Turkey.

The project took place in Eski?ehir/Turkey, where the hospital and my university are located. I worked alone on the project.   Background:  2.2. Eski?ehir Osmangazi University was established in 1970 in Eski?ehir.

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  It was started its academic life with the Faculties of Medicine, Engineering & Architecture and Arts & Sciences. Economic & Administrative Sciences; Health Services School, Eski?ehir Health Services Vocational School, Institutes of Natural Sciences, Metallurgy, Medical Sciences and Social Sciences were founded in 1993. Eski?ehir Osmangazi University continues to provide education with its 38 years of knowledge.   2.3.

Eski?ehir State Hospital was founded in 1971 with a capacity of 200 beds. Today, it is a regional hospital with an indoor area of 11.927 m2 on an area of approximately 30.963 m2 and a capacity of 995 beds.   2.

4. Hospital management complains that some corridors are overloaded and some corridors are empty. There is an unbalanced patient population distribution at the hospital. The purpose of this project is to arrange hospital corridors by balancing patient intensity. The average number of patients in 2010, the number of rooms in the current situation, and the number of rooms required by the services including the auxiliary rooms at the end of the regulation are given below.

          Services The average number of patients The number of current rooms The number of required rooms Internal Medicine 71726 7 8 Physical Medicine and Rehabilitation 42695 2 2 Neurology  39617 5 5 Dermatology  37837 4 5 Otorhinolaryngology 37579 4 5 Pulmonology  36052 4 5 Eye Diseases  35646 4 4 Orthopedia  33937 3 6 Psychiatry  33095 4 4 Urology  24734 5 5 General Surgery  21343 6 13 Brain and Nerve Surgery  15721 4 4 Cardiology  12576 4 4 Gastroenterology  7368 1 1 Infectious Diseases 6278 1 4 Nephrology  6036 1 1 Cardiovascular surgery  5869 2 3 Plastic Surgery  4240 1 1 Thoracic Surgery 712 1 1 Periodontal Disease  572 1 1    2.5. The use of heuristic methods instead of analytical methods gains weight in solving the problem of line balancing which is a combinatorial structure. For this purpose, many methods have been developed which are applied manually or in the computer environment. In this project, I have decided to use heuristic methods that can not guarantee the best solution but often find the best solutions in a short time. One of the easiest and most understandable of these intuitive methods is the largest candidate rule. This method is based on the idea that “if the longest workpiece is placed first, the others can be placed more easily in the remaining places so that a good balancing can be achieved.” The algorithm of the largest candidate rule is:1.

Sort business elements in descending order2. The first eligible (non-assigned, non-violating priority constraints and not exceeding the station duration) at the beginning of the list is assigned to the first station3. Apply Step 2 to all remaining members of the next station4. Apply steps 2 and 3 to all stations.   2.

6. I performed several different responsibilities for this project. My duties included the following:2.6.1. Searching different sources of information to collect the required details for the project.2.

6.2. Planning of the project in accordance with the project requirements.2.

6.3. Writing macro codes using the corresponding method.2.

6.4. Analyzing the output of the program.

2.6.5. Preparing the layout of the proposed system.2.6.6.

Preparing essential project reports and other associated documents of the project.2.6.7. Making project presentation. Personal Engineering Activity:  2.7. I started my work by collecting the details from the analysis of the concerned literature.

I visited university’s library and read newspapers for latest articles and journals. I also scrolled internet to get more details on the topic. I also held meetings with the relevant people to learn about the patient’s  intensity in the past years, to get a map of the current settlements and to find out the needs of the hospital management.  2.8. Although the problem I addressed resembles that of the assembly line balancing problem, the constraints of both problems were different.

There were precedence constraints in the assembly line balancing problem but in my problem, there were zoning constraints. Zoning constraints mean that when a service unit is assigned to any place, it should be assigned with all of its room. Other constraints are approximately equal to the total number of patients and the total number of rooms in the service groups placed at various locations in the corridors. The aim of this project is to stabilize patient intensity in corridors. According to these constraints, the largest candidate rule that has been rearranged is shown in the flowchart below.

I wrote excel macro codes to solve the problem with this algorithm.    2.9. The challenging part of this project was that the project does not include cycle time, production costs or costs that are seen in production systems. My only purpose on this project is to balance the patient density in the corridors. For this reason, I did not find the meaningful calculation of a number such as   for calculating the number of stations in assembly line balancing problems. I entered the Excel program which is used for solving the problem, the largest number of requested patients and the maximum number of rooms intuitively.

In order to create a more balanced settlement, I aimed to minimize the balancing delays calculated by the groups formed by the algorithm which regards the number of patients as the primary constraint and the groups formed by the algorithm which takes the number of rooms as the primary constraint. The results that I found for various values are given below.      The largest number of patients The largest number of rooms Balance delay 1 Balance delay 1 According to number of patients 95000   14 0,28 0,16 90000   15 0,12 0,08 85500   15 0,20 0,21 85000   15 0,20 0,21 84870   15 0,20 0,21 84782   15 0,20 0,21 According to number of rooms 95000   14 0,16 0,02 90000   15 0,12 0,08 85500   15 0,07673 0,08 85000   15 0,07130 0,08 84870   15 0,06988 0,08 84782   15 0,068919 0,08         I have identified the situation with the smallest balance delay as the best solution. In this case, the largest number of patients belonging to groups is 84782, the largest number of rooms is 15. The best case results are shown below.

  GROUPS TOTAL PATIENT NUMBER TOTAL ROOM NUMBER 1 General Surgery 2 Orthopedia Gastroenterology Nephrology   58834 15 2 General Surgery 1 Neurology Psychiatry 82562 15 3 Dermatology Otorhinolaryngology Infectious Diseases Thoracic Surgery   82406 15 4 Pulmonology Urology Brain and Nerve Surgery Plastic surgery   80747 15 5 Internal Medicine 1 Internal Medicine 2 Cardiology   84302 12 6 Eye Diseases Cardiovascular surgery  Physical Medicine and Rehabilitation Periodontal Disease    84782 10  2.10. In this case, which I regard as the best solution, I reach with the algorithm that accepts the number of rooms as the primary constraint and the number of patients as the secondary constraint.  I placed the groups I obtained in the hospital corridors intuitively and give the presentation to the management of the hospital for the proposed placement plan.

The layout I suggest is as follows.           Summary  2.11.

My only goal was to make it easier for patients to move in the hospital and increase the quality of service for the hospital because it is a business in the hospitals sector. I have developed a new method by making some changes in the biggest candidate algorithm which is known as a simple but effective way to solve this problem. I have created groups that have the almost equal number of rooms and number of patients by help of the developed method. As a result, patient density was balanced in the hospital corridor and quality of service was improved by avoiding excessive accumulation. The project was very important for my engineering course and it required complete demonstration of managerial, technical, and professional skills in planning, executing and reporting on an engineering project within a defined time. I enhanced my project management and research skills. I learned methods of data collection from all resources. I improved my communication, coordination and presentation skills.

It was a great opportunity and I would use these skills in my future projects.