A Advance Decision Support System for the Operating ROOM

IJSRD - International Journal for Scientific Research & Development| Vol. 3, Issue 08, 2015 | ISSN (online): 2321-0613

Advance Decision Support System for the Operating Theater 1,2

Mule Ravindra H.1 Patel H. H.2 Department of Computer Engineering 1,2 DCOER, Pune University

Abstract—The present hospital info systems offered publicly hospitals, lack a choice network part that might facilitate succeed higher coming up with solutions. Thus, AN intelligent call network has been developed, permitting the centralization and standardization of processes planning, the potency improvement of the operating theatre and well structure the waiting lists for surgical fragile scenario. The intelligence of the system fashioned with the assistance data processing and optimization techniques that enhance surgery length predictions and hospital room surgery schedules. The experimental results that show vital output, reducing overtime, under time, and higher resource utilization.

During this topic, intelligent call network for operating theatre planning and planning, and therefore the performance improvement is conferred. The 2 major functions of the system are: (i)To live the performance of the operating theatre (ii) to assist users production higher planning alternatives by supporting the task of making higher plans with data processing and optimization technique.

Key words: Intelligent Decision Support System, Operating Theater, Planning, Scheduling I. INTRODUCTION As quality-of-life improves and societies live longer, health care organizations face important will increase on their demand. it's a vicious loop. Population is ageing attributable to higher health help that is supported by pricey technological advances and aged population needs multiplied care. These factors increase health care prices and need higher management of existing resources. during this context, to take care of smart service levels and patient satisfaction, health care organizations are two-faced with 2 options: either expand capability or improve existing resources utilization. The former implies large capital investments and is thus, a troublesome strategic call.

However, rising processes associated potency entails an structure development set of actions that may be performed additional simply, involving less investment. The surgery is commonly thought-about the most important budget client and revenue center in a very hospital, additionally; its performance incorporates a severe impact on society.

Waiting lists for surgery area unit a essential issue that have an effect on several lives, thus being perpetually battled by health care organizations and governments. In this paper, driven by a real-world case, we tend to gift associate intelligent call network for surgery designing and programming, and therefore the performance improvement achieved with it. The system was designed for 2 user profiles, surgeons and hospital managers, providing them a designing framework for military science and operational issues (though we are going to concentrate on the operational level). the 2 main functions of the system are: (i) to supply users the means that to watch and to live the performance of the surgery and (ii) to assist users production higher programming alternatives by supporting the task of making higher plans with data processing and optimization

techniques. Our work was integrated within a business method improvement project that occurred in a very massive Portuguese public hospital, permitting the team to achieve a elementary understanding of the surgery programming method and therefore the corresponding user wants. The project introduced us to a reality with associate heterogeneous means of labor across the various specialties and low guideline compliance. These behaviors result from poor structure observance and lack of progress standardization. To tackle this case, we've devised a system that helps to standardize the design processes and to regulate quality and productivity.

II. LITERATURE SURVEY In this section we discussed about literature survey on cloud data security.

A. F. Dexter, R. D. Traub, and F. Qian, ―Comparison of statistical methods to predict the time to complete a series of surgical cases,‖ J. Clinical Monitoring and Computing, vol.

15, pp. 45–51, 1999 We present a statistical model for predicting the time to complete a series of successive, elective surgical cases. The use of sample means of case times and turnover times when scheduling cases does not minimize the operating room labor costs analogous with errors in foretell times to complete series of cases. The problem of minimizing analogous labor costs (both under and over utilization) can be converted to the problem of least absolute deviation regression. The dependent variables are the times to entire series of cases. The unconventional variables are the numbers of cases in each series that are in various categories (i.e., combinations of scheduled procedures and surgeons).

Although the computational method is preferred on theoretical grounds to that involving sample means, petition of both methods shows that the more practical method is to use the sample means of previous case times and turnovers.

B. B. Cardoen, E. Demeulemeester, and J. Beliën, ―Operating room planning and scheduling: A literature review,‖Eur. J. Oper. Res., vol. 201, no. 3, pp. 921–932, 2010 This paper provides a review of recent research on operating room planning and scheduling. We evaluate the literature on multiple Øelds that are related to either the problem setting the technical features (e.g. solution technique or qualm, incorporation). Since papers are pooled and evaluated in various ways, a diversiØed and detailed overview is obtained that facilitates the identiØcation of manuscripts related to the reader's speciØc interests. Throughout the literature review, we summarize the signiØcant trends in research on operating room planning and scheduling and we identify areas that need to be addressed in the future.

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Advance Decision Support System for the Operating Theater (IJSRD/Vol. 3/Issue 08/2015/123)

C. F. Guerrieroand R. Guido, ―Operational research in the management of the operating theatre: A survey,‖ Health Care Manage. Sci., vol. 14, pp. 89–114, 2011 Operating theater represents one of the most critical and expensive hospital resources since a high percentage of the hospital admissions is due to surgical interventions. The main aim are to guarantee the most utilization of medical resources, the delivery of surgery at the right time, the maximization of profitability (i.e., patient flow) without incurring additional costs or excessive patient waiting time.

The operating theater management is a process very complex: the use of mathematical and simulation models, and quantitative techniques plays, thus a crucial role. The main objective of this paper is to provide a structured literature review on how Operational Research can be applied to the surgical planning and scheduling processes. A particular attention is on the published papers that present the most interesting mathematical (raise and simulation) models and solution approaches developed to address the problems arising in operating theaters. Directions for future researches are also highlighted.

D. J. Blake and M. Carter, ―Surgical process scheduling: A structured review,‖J. Soc. Health Syst., vol. 5, no. 3, pp.

17–30, 1997.

No other department in uences the workload of a hospital more than the Department of Surgery and in particular, the activities in the operating room. These bustle are governed by the master surgical schedule (MSS), which states which patient types receive surgery on which day. In this paper we describe an systematic approach to project the workload for downstream departments based on this MSS. Specifically the ward tenancy, distributions, patient admission/discharge distributions, and the distributions for ongoing interventions/treatments is computed. Convalesce after surgery requires the support of multiple departments, such as nursing, physiotherapy, rehabilitation and long term care.

With our model, managers from these departments can decide their workload by aggregating tasks associated with recovering surgical patients. The model, which supported the development of a new MSS at the Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, furnish the foundation for a decision support tool to relate downstream hospital departments to the operating room III. PROPOSED APPROACH FRAMEWORK AND DESIGN A. Problem Definition Main want for call web is correct planning of crucial patients. crucial patients ought to get regular as early as attainable, attributable to risk issue related to their life. Next want is type business purpose of take for everybody needs to grow their business and thus through use of DSS organization can give smart services to user so attracting the shoppers to towards them. Another want might be to cut back investment in enlargement of organization B. Proposed System The system was mainly designed for two users, as surgeons and hospital managers. This will provide them a planning framework for tactical and operational problems. The two main functions of the system are: (i) to provide users the means to monitor and to measure the performance of the

operating theater and (ii) to aid users devising better scheduling alternatives by supporting the task of creating better plans with data mining and optimization techniques.

In later sections we will first see need for developing decision support system and further evolution of decision support system starting with old ones which have least functionality to current ones with advance functionality. We will also see advantages and benefits of each strategy. Next section is all about evolution of decision support system for Operation Theater.

Fig: one shows general flow of activities in higher cognitive process. 1st we've got set of data, upon that activity referred to as as knowledge acquisition is performed which has knowledge cleansing, knowledge pre-processing, and knowledge transformation activities. These activities can convert data into info. Next data processing is performed on generated info which can yield information.

Information is hidden info that we'd like to extract. In conclusion by use of data we will create choices which can result in actions. In context of DSS for operation theater knowledge may be no of patients, doctors operating in organization, obtainable physical resources etc. By method {of knowledge|of knowledge|of info} acquisition we are going to gather this data and refine it to provide information.

Next mistreatment technique called data processing we are going to analyze our input parameters to provide information. Information is actual choices created by system. Next through method of optimization we are going to enhance the result of call created by DSS

Fig 1: System architecture Diagram C. Mathematical Model 1, if patient i is assigned to the shift in day d, on operating room r and time t, xidrt = 0, Otherwise 1, if the surgeon s is assigned to the shift in day d, on operating room and time t ysdrt = I., Otherwise 1) Objective Functionsa) Minimization of the Number of Surgeries Maximize f1 = i€N d€D r€R t€T idrt where, N –Number of Patients D –Number of Days.

R – Number of Operating Rooms.

T- indicates Time. b) Maximization of the mean utilization of the operating rooms over a week span

where, ∑- Summation N –Number of Patients D –Number of Days.

R – Number of Operating Rooms. T- indicates Time. di-i th day of Week

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Advance Decision Support System for the Operating Theater (IJSRD/Vol. 3/Issue 08/2015/123)

c)

Maximization of the waiting time

Where, Wi - waiting time for i th patient.

Pi – Priority of ith patient.

2) Constraints Available capacity of the operating rooms, in terms of time, must be respected with no overtime ∑i € Nxidrt(di +ct) ≤ C Adrt, V d € D, r € R, t € T A patient can only be assigned to a room, day, part of the day, if the room is available for his specialty, xidrt≤Adrt, V i € N , d € D , r € R ,t € T 3) Surgeon Availability ysdrt≤Ssdt V s € S, d € D, r € R, t € T 4) Surgeon Allocation to Operating Room ∑r € R∑t € Tysdrt≤ 1 , V s € S , d € D 5) Relation between Patients and Surgeon

6) Domains of the variables ysdrt € {0,1} , xidrt€ {0,1}.

IV. WORK DONE In this section we are discussing the Scheduling, scenarios, performance metrics used etc.

A. Input In this user signature is the input for our Scheduling of Operation Room.

B. Hardware and Software Configuration Hardware Requirements: Processor Pentium IV 2.6 GHz Ram 512 MB DD RAM Monitor 15” COLOR Hard Disk 20 GB Software Requirements: Front End Java Tools Used NetBeans Operating System Windows 7/8 Database Mysql Cloud server Amazon.com,somee.com C. Results It is evident that the proposed RSA based scheme communication cost of DPRP scheme is more when compared with the proposed RSA based scheme.

V. CONCLUSION In summary, this paper reports the event of a choice web meant to endorse the method of OR planning. The answer given is especially directed to the economic management of the OR, wherever data processing and improvement elements ar supplementary to permit for simpler planning.

With best data this work is that the 1st to mix the aforementioned techniques to scale back surgery uncertainty and to realize a more robust utilization of this resources through planning improvement in call support systems.

Theoutcome, regarding each planning and estimation of length of surgery, ar higher than the present reality and additionally give the end- user away once coming up with, compared to the ways employed in the past. Extensions of the improvement model to incorporate alternative upstream and downstream resources shall be thought-about within the future, likewise because the development of a simulation part to higher measure generated solutions.

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Advance Decision Support System for the Operating Theater (IJSRD/Vol. 3/Issue 08/2015/123)

A structured review,”J. Soc. Health Syst., vol. 5, no. 3, pp. 17– 30, 1997.

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