• Sun. Dec 3rd, 2023

Healthcare Definition

Healthcare Definition, You Can't Live Withou It.

Evaluating building performance in healthcare facilities using entropy and graph heuristic theories

A hospital is made up of various units that work together to provide exemplary patient care. Some of the units involved include surgical suits, emergency areas, diagnostic imaging departments, critical care units, newborn intensive care areas, and laboratories. The design of a health facility is guided by its primary functions, which include research, inpatient and outpatient, diagnosis, or administration purposes1. When redesigning a hospital, the designer must consider the current status, such as the facility location, whom the facility serves, and the level of the facility expected. As the first step in the redesign process, this article aims to redesign the hospital by evaluating and weighing various standards in building a healthcare facility that meets international set requirements. American Institute of Architecture (AIA) Guidelines for Design and Construction of Health Care Facilities2, American Society of Heating, Refrigerating, and Air-Conditioning Engineering (ASHRAE)3, ventilation standards for healthcare facilities, and Health Technical Memorandum (HTM) guidelines for design, installation, validation, and verification of medical gas pipeline systems4, Facility guideline institution (FGI) for Design and Construction of Health Care Facilities5, were used as standard references for the evaluation process.

The implemented decision matrices can PROVIDE a definite structure in which various options can be compared to make a better decision. A weighted decision matrix compares a group of choices to the criteria considered in the decision-making process. Therefore, many researchers have developed a variety of weighting methods to assist with Materials and Methods. The materials and methods section should include adequate details to allow all procedures to be repeated. It may be divided into headed subsections if several methods are described. In decision making, including the analytic hierarchy process, critic method, and entropy method6.

Entropy method

Entropy is a method used to evaluate the weight of a given problem, in which the decision conditions for a set of applicant materials contain a particular volume of information. R. Clausius, a physicist, predicted the thermodynamic theory of entropy in 1865. It is a formal factor of the mater that denotes the state of thermodynamic systems7. In 1948, Shannon presented entropy into the data concept, which was used to determine the ambiguity of indications of information source knowns as follows: information entropy. The entropy method is primarily used in information theory to signify communication ambiguity, assess the capacity for separate assessment power to permit decision data, and determine the virtual weight. As shown in the judgment matrix, the entropy weight can be intended. “The smaller the entropy of evaluated information criterion, the greater the weight of the information criterion8, which is a solitary factual if the fundamental expectations that the entire foundations of information are dependable.

The entropy method is significant for several reasons: it estimates the information of the sign in addition to the practice point of the variance of the sign to determine the actual information and sign weight kept in check in the identified data. The weighting of entropy specifies the virtual significance of the constant sign in the struggle, which is under the circumstances of a specified appraisal thing, as demonstrated in Fig. 1.

Figure 1
figure 1

The method of determining and aggregating weight source.

Benefits of the entropy method

This method is well known for effectively determining the divergence of responses and contrast intensity and reckoning their weights appropriately9.

Furthermore, it recommends that the available information is adequate, and if not enough, additional information is needed10.

This approach allows for the quantitative evaluation of the success and cost responses.

The entropy weight method plan provides an additional difference in coefficient approval for answers. It is appropriate for an entropy plan to determine a significant disagreement between the decision-making answers11.

The strategy of this method aids in the calculation of the weight and is an immensely effective technique for evaluating indicators.

Limitation of the entropy method

The entropy computed weights missing specialist decisions; therefore, it only considers entropy values12,13.

This method does not provide any involvement in the designer’s first choice.

The efficiency of the entropy method in making decisions demonstrates that the preference for this method is problematic, as it does not consider rank perception.

The entropy method is used for weighting our standards collected after most of the methods are analyzed for weighting, and the lack of a standard can be measured in any department to apply the evaluation process. However, we encounter a significant issue with the layout facilities; hence, graph-theoretic-based heuristics are used to measure the layout score compared to the criteria that must be considered in the decision-making process. Therefore, many researchers have developed a variety of weighting methods to help in decision making, including the analytic hierarchy process, critic method, and entropy method.

Multi-criteria decision-making analysis can be described as a research approach that assists in creating a complex decision through explicit consideration in a transparent manner, which is essential because it makes it easy to clearly understand the question, thereby improving the efficiency and consistency of the decision-making process, as described by14.

The facility layout problem (FLP) is the placement of facilities in a plant area where it is a significant component of the organization because it represents the organization’s largest and most expensive assets (Figs. 2, 3). Theoretically, a graph is one approach to heuristic theories for solving the layout problem: when the objective is to maximize profit, the facility layout problem is to determine, in a given edge-weighted graph G, a maximum weight planar subgraph15,16.

Figure 2
figure 2

Facility layout problems.

Figure 3
figure 3

Facility layout problems.

Literature review

The evaluation was a step in the hospital’s redesign, and the facility has been described as a complex undertaking studied and analyzed by many researchers. Many researchers have studied and analyzed this process. Furthermore, it must incorporate the technical requirements demanded by the current and modern medical needs and consider the functional requirements in collaboration of a variety of units. The planner must consider issues such as healing capabilities, stressful workforce environments, the anxiety experienced by patients, and the sustainability of the facility17. Patients expect a given health facility to be easy to navigate, have a friendly and welcoming front or reception area, have soothing interiors such as cool colors, meet spiritual needs, and be able to view nature or access daylight while in the facility. It must also consider the needs of the working staff at heart by taking notice of such issues as break rooms, the distances they travel to serve their patients, their proximity to the patients they handle, and nature interior needs, which allow performing tasks at optimal levels, reflecting the quality of the patient. Care they give18.

19 Presented a new construction algorithm for a computer-aided plant layout. The layouts are created using ALDEP, whereas the adjacency-based heuristic and the maximum adjacency-based objective are used to evaluate them. The solution was built based on objectively measurable mathematical expressions. According to the findings, the layout generated by the adjacency-based heuristic has a higher layout score than that generated by the automated layout design program (ALDEP), and the adjacency-based heuristic can generate a shorter material handling distance than ALDEP.

Many types of research have been conducted on redesigning healthcare facilities to meet the required standards at a certain level. Building a new hospital allows aligning the hospital’s layout with the intended logistical idea. This method is used to assess the flexibility and adaptability of a design for operations management to a specific instance. The case chosen is about a new Dutch hospital built on a new site after the merger of two hospitals. The new hospital introduces twenty-first century airport operations management concepts for designing an outpatient clinic. The twenty-first-century airport’s concept aims to use the hospital building space by centralizing the waiting areas20,21.

In22, a redesigned model for clinical pharmacy in a university hospital in Colombia was described, which is the hospital unit tasked with making purchases, compounding, distributing various items, and storing purposes in a hospital. The model was described to contribute significantly to the increased interventions, which was estimated to be 70%. There was a 134% cost reduction, and most pharmacists’ time was devoted to patient care rather than administrative activities. The activities of technicians and technologists were more focused on patient care. Approach for assessing hospital building design in terms of operations management to ensure that the design is fit for purpose aids in the efficient and effective operation of healthcare facility processes in the present and the future. An evaluation approach is a valuable tool for assessing both functionality and the ability of a building design’s operational control to meet future advancements.

A variety of automated algorithms have been used to assist layout planners in developing alternate layouts. An automated layout design program (ALDEP) was created to improve the existing layout, whereas the computerized relative allocation of facilities technique (CRAFT) was created to improve the existing layout. Better results will be obtained by investigating hypotheses that combine the two algorithms rather than using them separately. The goal of this study was to use ALDEP to determine the best plan for Jaya Mandiri and improve it with CRAFT. The enhanced layout of the CRAFT was the best layout based on the cost of material handling, manufacturing lead time, and adjacency-based score23.


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