A Multiobjective Approach to the Reorganization of Health-Service Areas: A Case Study

1988 ◽  
Vol 20 (11) ◽  
pp. 1461-1470 ◽  
Author(s):  
J Malczewski ◽  
W Ogryczak
Keyword(s):  
Health Care ◽  
Health Service ◽  
Real Life ◽  
Optimization Techniques ◽  
Compromise Solution ◽  
Objective Functions ◽  
Service Areas ◽  
Multiobjective Approach ◽  
Multiobjective Analysis

In this paper the authors present an application of optimization techniques to the real-life problem of the reorganization of health-service areas. The problem is formulated as a linear programming problem with three objective functions. The values of the three objective functions proved to vary significantly depending on the assumed hierarchy of the objectives. Nevertheless, the multiobjective analysis based on parametric techniques was found to provide a compromise solution which implied significant improvement in the performance of the health-care system.

scholarly journals Investigating the Potential of Network Optimization for a Constrained Object Detection Problem

2021 ◽  
Vol 7 (4) ◽  
pp. 64
Author(s):  
Tanguy Ophoff ◽  
Cédric Gullentops ◽  
Kristof Van Beeck ◽  
Toon Goedemé
Keyword(s):  
Computational Complexity ◽  
Object Detection ◽  
Network Optimization ◽  
Real Life ◽  
Optimization Techniques ◽  
Training Data ◽  
Single Shot ◽  
Standard Object ◽  
Number Of Classes

Object detection models are usually trained and evaluated on highly complicated, challenging academic datasets, which results in deep networks requiring lots of computations. However, a lot of operational use-cases consist of more constrained situations: they have a limited number of classes to be detected, less intra-class variance, less lighting and background variance, constrained or even fixed camera viewpoints, etc. In these cases, we hypothesize that smaller networks could be used without deteriorating the accuracy. However, there are multiple reasons why this does not happen in practice. Firstly, overparameterized networks tend to learn better, and secondly, transfer learning is usually used to reduce the necessary amount of training data. In this paper, we investigate how much we can reduce the computational complexity of a standard object detection network in such constrained object detection problems. As a case study, we focus on a well-known single-shot object detector, YoloV2, and combine three different techniques to reduce the computational complexity of the model without reducing its accuracy on our target dataset. To investigate the influence of the problem complexity, we compare two datasets: a prototypical academic (Pascal VOC) and a real-life operational (LWIR person detection) dataset. The three optimization steps we exploited are: swapping all the convolutions for depth-wise separable convolutions, perform pruning and use weight quantization. The results of our case study indeed substantiate our hypothesis that the more constrained a problem is, the more the network can be optimized. On the constrained operational dataset, combining these optimization techniques allowed us to reduce the computational complexity with a factor of 349, as compared to only a factor 9.8 on the academic dataset. When running a benchmark on an Nvidia Jetson AGX Xavier, our fastest model runs more than 15 times faster than the original YoloV2 model, whilst increasing the accuracy by 5% Average Precision (AP).

The NHS — is Scotland Different? a Case Study of the Management of Health Care in the Hospital Service in the West of Scotland 1947 – 1987

2000 ◽  
Vol 45 (5) ◽  
pp. 155-158 ◽  
Author(s):  
D. McTavish
Keyword(s):  
Health Care ◽  
Health Service ◽  
Private Practice ◽  
Central Government ◽  
Medical Professional ◽  
Hospital Service ◽  
The West ◽  
New Managerialism ◽  
Hospital Boards

Management of the health service in Scotland and England, has since its creation, shown both divergence and congruence. In the initial decades in Scotland the executive hospital boards (which contained strong medical professional membership) and central government had a clearer relationship than in England. The health service-civil service machinery in Scotland was without doubt more to the forefront with higher status in the Scottish ‘polity’ than was the case in England. The 1970s reforms also indicated difference: despite the pro managerialist tones of the Farquarson Lang report in Scotland, a managerial emphasis was more apparent in the English reforms. By the 1980s, the government's clear intention that their ‘radical’ agenda should apply in Scotland and England was implemented in many instances: aspects of the new managerialism were applied as vigorously in the case examined than anywhere in England: the attempt to draw clinicians into resource management (as advocated in the Griffiths report) appeared to have advanced further in Scotland until well into the 1990s. Yet in other aspects, Scotland diverged from parts of England in the implementation of the 1980's agenda most notably in the growth of private practice though the case indicated significant Scottish developments here too. The article concludes by speculating on some Scottish differences in the coming years.

An Approach to Improved Decentralized Design: The Modified Approximation-Based Decentralized Design (MADD) Framework

2007 ◽  
Author(s):  
Ashwin P. Gurnani ◽  
Kemper Lewis
Keyword(s):  
Nash Equilibrium ◽  
Bounded Rationality ◽  
Large Scale ◽  
Optimization Techniques ◽  
Objective Functions ◽  
Design Problems ◽  
Decentralized Design ◽  
The Impact ◽  
Rational Reaction Set

The design of large scale complex engineering systems requires interaction and communication between multiple disciplines and decentralized subsystems. One common fundamental assumption in decentralized design is that the individual subsystems only exchange design variable information and do not share objective functions or gradients. This is because the decentralized subsystems can either not share this information due to geographical constraints or choose not to share it due to corporate secrecy issues. Game theory has been used to model the interactions between distributed design subsystems and predict convergence and equilibrium solutions. These game theoretic models assume that designers make perfectly rational decisions by selecting solutions from their Rational Reaction Set (RRS), resulting in a Nash Equilibrium solution. However, empirical studies reject the claim that decision makers always make rational choices and the concept of Bounded Rationality is used to explain such behavior. In this paper, a framework is proposed that uses the idea of bounded rationality in conjunction with set-based design, metamodeling and multiobjective optimization techniques to improve solutions for convergent decentralized design problems. Through the use of this framework, entitled Modified Approximation-based Decentralized Design (MADD) framework, convergent decentralized design problems converge to solutions that are superior to the Nash equilibrium. A two subsystem mathematical problem is used as case study and simulation techniques are used to study the impact of the framework parameters on the final solution. The discipline specific objective functions within the case study problem are unconstrained and continuous — however, the implementation of the MADD framework is not restricted to such problems.

Objective Reduction Using Axiomatic Design and Product-Related Dependencies: A Layout Synthesis of an Autonomous Greenhouse Case Study

2020 ◽  
Author(s):  
Yann-Seing Law-Kam Cio ◽  
Yuanchao Ma ◽  
Aurelian Vadean ◽  
Giovanni Beltrame ◽  
Sofiane Achiche
Keyword(s):  
Optimization Problem ◽  
Real Life ◽  
Axiomatic Design ◽  
Objective Functions ◽  
Nsga Ii ◽  
Design Problems ◽  
Objective Reduction ◽  
Layout Synthesis ◽  
Design Perspective

Abstract Many-objective optimization problem (MaOP) is defined as optimization with more than 3 objective functions. This high number of objectives makes the comparing solutions more challenging. This holds true for design problems which are MaOPs by nature due to the inherent complexity and multifaceted nature of real-life applications. In the last decades, many strategies have attempted to overcome MaOPs such as removing objectives based on their impact on the optimization. However, from a design perspective, removing objectives could lead to an under optimal, unfeasible or unreliable design. Consequently, objective aggregation seems to be a better approach since objectives can be grouped based on design features controlled by the designers. The proposed methodology uses Axiomatic Design to decompose a system into subsystems or components, and Product-Related Dependencies Management to identify the dependencies between components and formulate the objectives. Then, these objectives are aggregated based on the subsystems found with the Axiomatic Design. The methodology, applied to the layout synthesis of an autonomous greenhouse, can trim down the number of objectives from 15 to 5. Then, using a modified non-dominated sorting genetic algorithm-II (NSGA-II) combined with the objective aggregation, we were able to increase the number of “good” concepts found from 9 to 33 out of a total of 50 obtained designs.

Improving health care costing with resource consumption accounting

2016 ◽  
Vol 29 (6) ◽  
pp. 646-663
Author(s):  
Hasan Ozyapici ◽  
Veyis Naci Tanis
Keyword(s):  
Health Care ◽  
Real Life ◽  
Resource Consumption ◽  
Selling Price ◽  
Health Care Administrators ◽  
Content Type ◽  
The Difference ◽  
Costing System ◽  
Traditional Costing

Purpose – The purpose of this paper is to explore the differences between a traditional costing system (TCS) and resource consumption accounting (RCA) based on a case study carried out in a hospital. Design/methodology/approach – A descriptive case study was first carried out to identify the current costing system of the case hospital. An exploratory case study was then conducted to reveal how implementing RCA within the case hospital assigns costs differently to gallbladder surgeries than the current costing system (i.e. a TCS). Findings – The study showed that, in contrast to a TCS, RCA considers the unused capacity, which is the difference between the work that can be performed based on current resources and the work that is actually being performed. Therefore, it assigns lower total costs to open and laparoscopic gallbladder surgeries. The study also showed that by separating costs into fixed and variable RCA allows managers to benefit from a pricing strategy based on the difference between the service’s selling price and variable costs incurred in providing that service. Research limitations/implications – The limitation of this study is that, because of time constraints, the implementation was performed in the general surgery department only. However, since RCA is an advanced system that has the same application procedures for any department inside in a hospital, managers need only time gaps to implement this system to all parts of the hospital. Practical implications – This study concluded that RCA is better than a TCS for use in health care settings that have high overhead costs because it accurately assigns overhead costs to services by considering unused capacities incurred by a hospital. Consequently, this study provides insight into both measuring and managing unused capacities within the health care sector. This study also concluded that RCA helps health care administrators increase their competitive advantage by allowing them to determine the lowest service price. Originality/value – Since the literature review found no study comparing RCA with TCS in a real-life health care setting, little is known about differences arising from applying these systems in this context. Thus, the current study fills this gap in the literature by comparing RCA with TCS for both open and laparoscopic gallbladder surgeries.

Caught in the “Traps of Managed Competition”? Examples of Russian Health Care Reforms from St. Petersburg and the Leningrad Region

1997 ◽  
Vol 27 (4) ◽  
pp. 661-686 ◽  
Author(s):  
Sarah Curtis ◽  
Natasha Petukhova ◽  
Galina Sezonova ◽  
Nadia Netsenko
Keyword(s):  
Health Care ◽  
Health Service ◽  
Service Systems ◽  
Leningrad Region ◽  
Managed Competition ◽  
Health Care Reforms ◽  
Future Policy ◽  
The City ◽  
Different Parts

Elements of a “managed market” for health services have been introduced into the Russian health care system, which under the Soviet regime was run as a comprehensive state-managed system. The authors examine the recent development of health service reforms in a case study of the city of St. Petersburg and the surrounding Leningrad region. Evidence from key informants and a local survey of service users shows how alternative models of the managed market are being introduced in different parts of the study area. A critical review of the market-oriented strategies for reform emerging in the case study suggests that such reforms carry risks associated with the “traps of managed competition.” Future policy for health service systems in Russia must take these risks more fully into account.

scholarly journals Embedding the Pillars of Quality in Health Information Technology Solutions Using “Integrated Patient Journey Mapping” (IPJM): Case Study (Preprint)

2019 ◽  
Author(s):  
Stephen McCarthy ◽  
Paidi O'Raghallaigh ◽  
Simon Woodworth ◽  
Yoke Yin Lim ◽  
Louise C Kenny ◽  
...  
Keyword(s):  
Health Care ◽  
Information Technology ◽  
Health Service ◽  
Health Information ◽  
Health Care Quality ◽  
Care Quality ◽  
Multidisciplinary Teams ◽  
Patient Journey ◽  
Connected Health

BACKGROUND Health information technology (HIT) and associated data analytics offer significant opportunities for tackling some of the more complex challenges currently facing the health care sector. However, to deliver robust health care service improvements, it is essential that HIT solutions be designed by parallelly considering the 3 core pillars of health care quality: clinical effectiveness, patient safety, and patient experience. This requires multidisciplinary teams to design interventions that both adhere to medical protocols and achieve the tripartite goals of effectiveness, safety, and experience. OBJECTIVE In this paper, we present a design tool called <i>Integrated Patient Journey Mapping</i> (IPJM) that was developed to assist multidisciplinary teams in designing effective HIT solutions to address the 3 core pillars of health care quality. IPJM is intended to support the analysis of requirements as well as to promote empathy and the emergence of shared commitment and understanding among multidisciplinary teams. METHODS A 6-month, in-depth case study was conducted to derive findings on the use of IPJM during <i>Learning to Evaluate Blood Pressure at Home</i> (LEANBH), a connected health project that developed an HIT solution for the perinatal health context. Data were collected from over 700 hours of participant observations and 10 semistructured interviews. RESULTS The findings indicate that IPJM offered a constructive tool for multidisciplinary teams to work together in designing an HIT solution, through mapping the physical and emotional journey of patients for both the current service and the proposed connected health service. This allowed team members to consider the goals, tasks, constraints, and actors involved in the delivery of this journey and to capture requirements for the digital touchpoints of the connected health service. CONCLUSIONS Overall, IPJM facilitates the design and implementation of complex HITs that require multidisciplinary participation. CLINICALTRIAL

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