A cost simulation for mammography examinations taking into account equipment failures and resource utilization characteristics

Coelli, F. C.; Almeida, R. M. V. R.; Pereira, Wagner Coelho de Albuquerque

doi:10.1111/j.1365-2753.2009.01294.x

Cited by 12 publications

(7 citation statements)

References 24 publications

(20 reference statements)

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“…In addition to two previously mentioned studies about increasing vaccine cold storage equipment [47, 91], we identified just nine OR studies related to medical equipment. Some examples include a cost-utility analysis of introducing PET scanning technology for lung cancer diagnosis in Iran [102]; a DES model of a mammography clinic in Brazil that took into account equipment failures and maintenance [103]; a queuing model developed to improve response and turn-around time of equipment repair work orders in a clinical engineering department in Cuba [104]; and models to help inform general medical equipment purchasing [105] and replacement schedules [106] in LMICs.…”

Section: Resultsmentioning

confidence: 99%

Operations research in global health: a scoping review with a focus on the themes of health equity and impact

Bradley

Jung

Tandon-Verma

et al. 2017

Health Res Policy Sys

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BackgroundOperations research (OR) is a discipline that uses advanced analytical methods (e.g. simulation, optimisation, decision analysis) to better understand complex systems and aid in decision-making.SummaryHerein, we present a scoping review of the use of OR to analyse issues in global health, with an emphasis on health equity and research impact. A systematic search of five databases was designed to identify relevant published literature. A global overview of 1099 studies highlights the geographic distribution of OR and common OR methods used. From this collection of literature, a narrative description of the use of OR across four main application areas of global health – health systems and operations, clinical medicine, public health and health innovation – is also presented. The theme of health equity is then explored in detail through a subset of 44 studies. Health equity is a critical element of global health that cuts across all four application areas, and is an issue particularly amenable to analysis through OR. Finally, we present seven select cases of OR analyses that have been implemented or have influenced decision-making in global health policy or practice. Based on these cases, we identify three key drivers for success in bridging the gap between OR and global health policy, namely international collaboration with stakeholders, use of contextually appropriate data, and varied communication outlets for research findings. Such cases, however, represent a very small proportion of the literature found.ConclusionPoor availability of representative and quality data, and a lack of collaboration between those who develop OR models and stakeholders in the contexts where OR analyses are intended to serve, were found to be common challenges for effective OR modelling in global health.Electronic supplementary materialThe online version of this article (doi:10.1186/s12961-017-0187-7) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Operations research in global health: a scoping review with a focus on the themes of health equity and impact

Bradley

Jung

Tandon-Verma

et al. 2017

Health Res Policy Sys

View full text Add to dashboard Cite

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“…CT exams were characterized and divided into stages, each one measured during on-site surveys at CT services in small and average-size hospitals and medical clinics, Brazil. The studied CTs covered all their technological range in the country (1,2,4,16, and 128 slices CTs). Exams were followed in 10 devices of three brands, nine health units, and five cities (three radiological clinics, three general clinics, four general hospitals).…”

Section: Datamentioning

confidence: 99%

“…[1][2][3] However, determining which CT model is the most suitable for a specific setup is not always simple, and numerical methods such as computer simulation may be useful to this end. [4][5][6] Simulations allow for analyzing the behavior of a system without its actual implementation, are widely used in many areas of science, and, increasingly, are used in the modeling of health systems. 7 The objective of this study was to analyze the type of CT scanners most suitable for hospitals of different sizes, contingent on 'hospital scenarios' (structural/organizational changes in hospital resources and exam rates).…”

Section: Introductionmentioning

confidence: 99%

Discrete‐event models for the simulation of computed tomography sectors according to hospital structural/organizational changes and expected patient arrival rates

Santos

Pereira

Almeida

2021

Health Planning & Management

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Objective:To analyze the types of computed tomography (CT) scanners most suitable for different hospital sizes and 'scenarios' (exam rates and structural/organizational changes), using discrete-event simulation models. Materials and methods:CT exams were divided into stages, measured during on-site surveys at CT services in small and average size private hospitals. Ten devices in nine health units, five cities and two states of Brazil were studied to this end, and the following data were collected: Time spent in each stage for each type of exam; average monthly number of exams performed and general characteristics of exams.Three arrival rates were defined (103, 154 and 206 patients/ day), representing expected demand for the studied units.From these parameters, six scenarios were simulated, consisting of changes in personnel and hospital structure (e.g., 'adding a changing room') in a base scenario (one CT, one changing room, no nursing assistance, arrival rate 1). Results:It was possible to identify a scenario most useful for very large demands, such as large emergency hospitals in big cities, (a CT, nursing assistance and three changing rooms added to the base scenario). Another identified scenario was more adequate for small demands (adding a changing room to the base scenario).

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“…Then, adjustments to the model are implemented to understand the effect such changes would have on key performance indicators in a real‐world setting. Common changes DES models consider in a healthcare setting include adding additional staff, 15‐18 beds, 19‐21 or equipment; 11,15 changing scheduling policies; 21‐24 process design; 18,25 layout redesign; 14,26 and the impact of changes in demand 21,27 or discharge rates 28 . The application and value of using such models has been documented extensively 29‐35 …”

Section: Introductionmentioning

confidence: 99%

A discrete event simulation to evaluate impact of radiology process changes on emergency department computed tomography access

Maass

Halter

Huschka

et al. 2021

Evaluation Clinical Practice

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Background Hospitals face the challenge of managing demand for limited computed tomography (CT) resources from multiple patient types while ensuring timely access. Methods A discrete event simulation model was created to evaluate CT access time for emergency department (ED) patients at a large academic medical center with six unique CT machines that serve unscheduled emergency, semi‐scheduled inpatient, and scheduled outpatient demand. Three operational interventions were tested: adding additional patient transporters, using an alternative creatinine lab, and adding a registered nurse dedicated to monitoring CT patients in the ED. Results All interventions improved access times. Adding one or two transporters improved ED access times by up to 9.8 minutes (Mann‐Whitney (MW) CI: [−11.0,−8.7]) and 10.3 minutes (MW CI [−11.5, −9.2]). The alternative creatinine and RN interventions provided 3‐minute (MW CI: [−4.0, −2.0]) and 8.5‐minute (MW CI: [−9.7, −8.3]) improvements. Conclusions Adding one transporter provided the greatest combination of reduced delay and ability to implement. The projected simulation improvements have been realized in practice.

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A cost simulation for mammography examinations taking into account equipment failures and resource utilization characteristics

Abstract: Discrete-event simulation allowed for the definition of the more efficient clinic, contingent on the expected prevalence of resource utilization and equipment failures.

Cited by 12 publications

References 24 publications

Operations research in global health: a scoping review with a focus on the themes of health equity and impact

Operations research in global health: a scoping review with a focus on the themes of health equity and impact

Discrete‐event models for the simulation of computed tomography sectors according to hospital structural/organizational changes and expected patient arrival rates

A discrete event simulation to evaluate impact of radiology process changes on emergency department computed tomography access

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