Decision Based Management System for Hospital Bed Allocation

Transcription

1 Decision Based Management System for Hospital Bed Allocation 1 Tosin A. Adesuyi, 2 Mojisola G. Asogbon, 3 Stella. A. Akinladenu, 4 PerpetualI. Oladoja 1, 2, 3, 4 Department of Computer Science Federal University of Technology Akure, Ondo State, Nigeria. Abstract - In developing countries, the management of inpatient bed allocation is increasingly becoming complex as a result of inadequate bed capacity, poor scheduling policies and financial constraints in hospitals. The use of a decision based system could aid hospital staff and health decision makers to carry out efficient in-patient beds allocation, thus potentially reducing costs and in-patient length of stay. This study developed a Decision Based Management System for Hospital Bed Allocation in other to enhance easy accessibility and efficient bed allocation in the hospital in a fairly and timely manner using State Specialist Hospital, Akure, Ondo State, Nigeria as case study and Microsoft Visual Studio, C#, ASP.net and SQL SERVER 2005 tools for the implementation. The analysis of the manual method served as the input used to developed and experiment the functionalities of the proposed system. Keywords - Hospital, In-patient, Bed Allocation, Decision Management System, Bed Allocation Model. 1. Introduction Hospital is an institution for the treatment, care, and cure of the sick and wounded, the study of disease, and the training of physicians, nurses, and allied health care personnel [1]. People that visit hospital for a particular treatment are called patients and the visit could be outpatient or in-patient. Out-patients are short visit to the hospital that last not more than a day, while in-patients are visit to the hospital that require at least one night stay in a ward [2]. Bed allocation is the management of all processes necessary to place a patient into an appropriate vacant bed in the hospital. There are many different types of hospital bed, reflecting differences in the kind of patient they are designed to accommodate. The processes taken into consideration include the admission of a patient, length of stay, type of specialist bed (if needed) and the pending discharge date [3]. The management of available and appropriate beds and their occupancy levels in hospitals is an integral part of the economical and ethical management of health care [3]. Most times, poor bed allocation management occur as a result of shortage of bed spaces which can lead to cancellations of admissions for planned surgery, admission to inappropriate wards, delay in admitting emergency patients, and transfers of existing inpatients between wards thereby delaying their discharge which can cause enormous frustration and distress [7]. Hospital management and staff must find a balance between the demands for available beds and demands through the needs of continuous care of the patient and emergency. This can be achieved using a properly developed bed allocation decision management system that will aid hospital staff and health decision makers, thus reducing costs and in-patient length of stay. 2. Related Works [4] focused on minimizing patients' length of stay for their surgery by developing amodelfor allocating operating room capacity to different medical specialties. First, the study presented the mixed integer programming (MIP) model for operating room capacity allocation to minimize inpatients' length of stay and then developed a basic model with two variant, made up of constraints. The first variant of the model considered emergency situations that could arise for each specialty at the hospital while the second variant was based on post-operative care for patientsin the hospital. The model output gives optimized allocation of operating rooms to each specialty for each day. The model was simulated using MATLAB. However the major drawback in the work was that the optimization part of the model does not account for uncertainty in the problem parameters. [3] worked on Innovative Hospital Bed Management Using Spatial Technology. The work shows that existing hospital s systems rely on a large number of diverse methods to gather and collate patient related information. The research was geared towards investigating how the application of GIS can benefit the health care industry and provide a simple universal graphical output system that is applicable and useful to all 473

2 levels of medical careers in the hospital environment.[5] proposed a model for modeling bed allocation problems with uncertain length of stay for each patient. The research emphasized that in hospitals, the queuing model requires waiting until free bed is available when there are insufficient beds available to admit ill and sick people. The major aim of the work is to effectively reduce the patients time in queue, thus improving the public satisfaction in health service. Two bed allocation methods were presented, Hybrid intelligent algorithmwas employed to implement these methods. Finally, numerical example were provided to demonstrate the feasibility of the proposed algorithm.[6] introduced three bed prediction models that will aid hospital planners to anticipate bed demand so as to manage resources efficiently. The research emphasized that over-crowding is perhaps the most common scene that people see in the emergency department of a Hospital and stated further that the ability to forecast the random arrival patterns would definitely be the key solution to over-crowding problems. The work employed three different techniques to aid bed management in planning resources namely; the regression model with sufficient predictive ability to allow hospital planners to forecast the following week s average occupancy, the poisson bed occupancy model that help bed planners in estimating bed occupancy and to allocate optimal number of beds based on length of stay and admissions data, and simulation model developed using Arena for predicting following week s bed occupancy level. 2.1 Hospital Bed Allocation State Specialist Hospital, Akure, Nigeria is a government hospital with various departments in which patients are directed to depending on their health issues. Beds are allocated at the level of hospital ward which is based on hospital units which include: General unit (Male and Female ward): The general unit consists of both the male and female ward, which is different from all other units in the hospital because patients that are admitted have common diseases such as malaria, typhoid, fever etc. There are at least thirty beds in both the male and female ward in general unit. Surgical unit: The surgical unit is the actual operating rooms, where surgical procedures are performed. All operating rooms have an operating table that can be adjusted to accommodate the surgical procedure and facilitate the use of sophisticated monitoring equipment. Instruments and equipment, such as lasers or television screens, are brought into the operating room as needed. There are at least ten beds in the surgical unit. Paediatric unit (Children s ward): The paediatric unit admits only children and is equipped with instruments and equipment that are suitable for the small size of its patients.there are minimum of ten beds in the Paediatric unit. Dentist unit: The dentist unit specializes in the diagnosis, prevention, and treatment of diseases and conditions of the oral cavity. The dental team includes dental assistants, dental hygienists, dental technicians, and dental therapists. There are at least five beds in the dentist unit. Accident and Emergency unit: The accident and emergency department is staffed 24 hours a day by doctors and nurses who have been trained to diagnose health problems. These doctors and nurses perform medical or surgical treatments that stabilize a patient s condition so that the patient can be moved to another part of the hospital for additional care. When the emergency room is crowded with patients, emergency department staff identify and respond immediately to the most seriously ill or injured patients. There are minimum of fifteen beds in this unit. Maternity unit: The maternity unit, also found in many hospitals, offers delivery rooms where pregnant women stay for the birth of their babies. The maternity unit is divided into three units: pre-natal unit where pregnant women stay before delivery, labour unit where the delivery takes place and post-natal unit where they stay after the delivery. There are at least six beds in the prenatal unit, three beds in the labour unit and twelve beds in the post-natal unit. 3. System Architecture and Methodology 3.1 Bed Allocation Model (BAM) Fig. 1 shows the architectural diagram of the Bed Allocation Model (BAM).The model deals with allocation of free bed space to in-patient and this is done by first checking if there are free bed space(s) in patient s ward and then picks at random a particular bed number; afterward it assigns it to a particular patient. In a case where there is no free bed space, the model directs the patient to the waiting list. It waits until there is/are free space(s); it then allocates the patient to a bed space (removing the patient from waiting list). The model also stores in-patient information in the waiting list using first - in -first - out (FIFO) and Priority scheduling manner. In-patients with critical cases overrides other in-patients with normal or minimal cases in the waiting list. 474

3 β β 1 8 A single addition of a patient to the waiting list where λ 0 will update the variables as follows: 1 9 where Q represents total number of patient in the waiting list. β Φ λ 0 where Q A single removal of a patient from the waiting list where λ 0 will update the variables as follows: Fig. 1 Architectural diagram of BAM Eq. (1) to (14) shows the mathematical representation of the model. Let T represents universal set containing all the beds in a ward; F: set of free bed space in a ward, and P: set of occupied bed space in a ward such that: Q Q 1 where Q 0 β β 1 λ λ 1 4. System Implementation T t, t, t,, t F f, f, f,, f P p, p, p,, p F T P T T F P λ n F β n P Φ n T Φ λ β where represents number of free bed space in a ward, represents number of occupied bed space in a ward, represents the total number of beds in a ward. A single allocation of a patient where λ 0 will update the variables as follows: λ λ 1 β β 1 A single de-allocation of a patient where update the variables as follows: λ λ β 0 will 7 The model was implemented with the aid of visual studio 2010, the integrated development environment where development takes place using of XHTML, CSS. SQ LSERVER 2005, a relational database was used as the data storage for the whole application while ASP.net and HTML.net tag wereused to designthe user interface. Lastly, C# programming language was used to code the mathematical model. The Database schema consists of four tables namely: Allocation table, Waiting-list table, Space-status table and Patient-register table. The Allocation table stores free bed space available, it stores the card number, allocated unit and bed number of the patient. Waiting-list table stores the patients that are yet to be allocated a bed space; it stores the card number, patient name, health category, arrival time and date of the patient. Patient-register table stores new patient that just arrived for admission, it stores the card number, patient name, stay status and health category. Space-status table stores the stay status whether discharged or not, it stores the units, number of free space and number of occupied space of the patient. Fig. (2) to (4) show some of the cross sectional interface of the developed Bed Allocation system. 475

4 Fig. 4 Patient s Waiting List Interface Fig. 2 Login Interface Fig. 2 is login interface is where user supply their login details to access the system. Fig. 5 shows the report of all allocated patients in all wards. This report enable and assist the administrative personnel to know the records of all allocated bed space in the hospital. Fig. 5 Report of all allocated patients Interface Fig. 3 Patience Registration Interface Patient to be admitted is registered using the interface in fig. 3 by keying in the patient medical details. A successful registration shows that there is available bed space in the ward where patient is to be admitted and it will assign it to the patient otherwise it will automatically direct the patient registration to a waiting list shown in fig Conclusion The enormous importance of hospital bed allocation model has been identified with emphasis on their use in allocating bed space to hospital patient and also deallocating them, and also in the management of hospital equipment. The main technique used in the software development of this project is Bed Allocation Model (BAM)which is used to analyze mathematical approach of how beds are allocated, de-allocated and priority levels and emergency cases in hospital. The allocation is based on patient classified category wards as prescribed by the physician. However the developed model still give room 476

5 for administrative personnel to influence the waiting-list. This can be improved upon to disallowed personnel biasness. Acknowledgment We sincerely appreciation the management and staff of State Specialist Hospital, Akure, Ondo State, Nigeria for providing useful information and resources for the actualization of this research work. References [1] W. Lippincott, and Wilkins, Stedman s Medical Dictionary 28 th Edition, NOOK press, [2] Roger Henderson (2013), accessed June [3] A. G. Nicholls, and F. R. Young, "Innovative hospital bed management using spatial technology, Spatial Science Queensland, Vol.2, No. 2, 2007, pp [4] G. V. Sreenath, K. V. Sastha, M. Sarah, and S. C. Kailas, Operating Room Allocation Using Mixed Integer Linear Programming (MILP) Department Of Mechanical Engineering College Of Engineering,University of Kerala, Palayam, Thiruvananthapuram, India, [5] G. Ling, L. Liang, and G. Lianlong, Uncertain Models for Bed Allocation, Global Journal of Health Science, Vol. 2, No. 2, 2010, pp [6] K. Arun, and M. John, Models for Bed Occupancy Management of a Hospital School of Aerospace, Mechanical and Manufacturing Engineering RMIT University, Melbourne, Victoria 3000, Australia [7] N. C. Proudlove, K. Gordon, and R. Boaden, "Can good bed management solve the overcrowding in accident and emergency departments"emerg Med J,Vol.20, No. 2, 2003, pp Biography Adesuyi Akinwale Tosin presently a Software Engineer with the Computer Resource Center of the Federal University of Technology Akure, Ondo State, Nigeria. He holds a Master s degree in Computer Science from The Federal University of Technology Akure, Ondo State, Nigeria in He has papers published in reputable journals. His areas of research include; E- learning, Ontology, Computer and Network Security, and Machine learning, Data mining and Data Science. Asogbon Mojisola Grace holds a Master s degree in Computer Science from The Federal University of Technology Akure, Ondo State, Nigeria in Her areas of research include; Database Management, Applied Artificial Intelligence and Data mining and Knowledge Discovery. Akinladenu Stella Ademayowa presently a Maters student at the department of Computer Science Federal University of Technology Akure, Ondo State, Nigeria. Her areas of research include; Soft Computing and Computer Networks. OladojaIlobekemen Perpetual presently a PhD student at the department of Computer Science Federal University of Technology Akure, Ondo State, Nigeria. She holds a Master s degree in Computer Science from the same University in She has published quite a number of scientific papers in her research interest areas which spans E-learning, Ontology, Web Technology Language and Data mining. 477