IDENTIFICATION AND REVIEW OF COST-EFFECTIVENESS MODEL PARAMETERS: A QUALITATIVE STUDY

Objectives: Health economic models are developed as part of the health technology assessment process to determine whether health interventions represent good value for money. These models are often used to directly inform healthcare decision making and policy. The information needs for the model require the use of other types of information beyond clinical effectiveness evidence to populate the model's parameters. The purpose of this research study was to explore issues concerned with the identification and use of information for the development of such models.Methods: Three focus groups were held in February 2011 at the University of Sheffield with thirteen UK HTA experts. Attendees included health economic modelers, information specialists and systematic reviewers. Qualitative framework analysis was used to analyze the focus group data.Results: Six key themes, with related sub-themes, were identified dealing with decisions and judgments; searching methods; selection and rapid review of evidence; team communication; modeler experience and clinical input and reporting methods. There was considerable overlap between themes.Conclusions: Key issues raised by the respondents included the need for effective communication and teamwork throughout the model development process, the importance of using clinical experts as well as the need for transparent reporting of methods and decisions.

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The Development of the Air Anti-Submarine Warfare MissionTestbed as a Tool for the Development of Operator Models

Proceedings of the Human Factors Society Annual Meeting ◽

10.1177/154193128803201617 ◽

1988 ◽

Vol 32 (16) ◽

pp. 1073-1077 ◽

Cited By ~ 2

Author(s):

Wayne W. Zachary ◽

Monica C. Zubritzky ◽

Floyd A. Glenn

Keyword(s):

Decision Making ◽

Information Processing ◽

Real Time ◽

Information Needs ◽

Model Development ◽

Experimental Investigations ◽

Human Factors Engineering ◽

Distributed Intelligence ◽

Tactical Decisions ◽

Types Of Information

The central concern of human factors engineering (HFE) is facilitating a productive relationship between man and machine. A new generation of man-machine systems has arisen in which the machine acts in a relatively intelligent manner to enhance the operator's decision-making capabilities in real-time multi-tasking situations. These systems have been termed “distributed intelligence systems” (DIS) because intelligence is distributed among all system entities, whether they are human or computer. The ability of these systems to aid humans in a flexible, interactive fashion depends on the capability of the machine to predict the human's information needs in a given decision-making situation. Thus, the DIS must incorporate a model that reflects the operator's information processing requirements for the tasks necessary to operate the system. To construct this model, it is necessary to develop a DIS testbed where experimental investigations can occur. The mission environment chosen for simulation is the Naval Air Anti-Submarine Warfare (ASW) mission, whose objectives to search for, find, and attack the enemy submarine involve complex tactical decisions in a real-time multi-tasking environment. In the Air ASW mission, most significant tactical decisions are made by the Tactical Coordinator (TACCO), the main operator of the system. The aspects of the testbed discussed in this paper include those elements of the simulation and responsibilities of the TACCO needed to illustrate the types of information processing tasks involved in the ASW mission. Also, the data collection capabilities of the testbed and how this data will be applied to operator model development will be discussed.

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Clinically applicable artificial intelligence system for dental diagnosis with CBCT

Scientific Reports ◽

10.1038/s41598-021-94093-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Matvey Ezhov ◽

Maxim Gusarev ◽

Maria Golitsyna ◽

Julian M. Yates ◽

Evgeny Kushnerev ◽

...

Keyword(s):

State Of The Art ◽

Model Development ◽

Clinical Effectiveness ◽

Anatomical Landmarks ◽

Periapical Lesion ◽

Artificial Intelligence System ◽

Intelligence System ◽

Significant Difference ◽

Diagnostic Capabilities ◽

Lesion Localization

AbstractIn this study, a novel AI system based on deep learning methods was evaluated to determine its real-time performance of CBCT imaging diagnosis of anatomical landmarks, pathologies, clinical effectiveness, and safety when used by dentists in a clinical setting. The system consists of 5 modules: ROI-localization-module (segmentation of teeth and jaws), tooth-localization and numeration-module, periodontitis-module, caries-localization-module, and periapical-lesion-localization-module. These modules use CNN based on state-of-the-art architectures. In total, 1346 CBCT scans were used to train the modules. After annotation and model development, the AI system was tested for diagnostic capabilities of the Diagnocat AI system. 24 dentists participated in the clinical evaluation of the system. 30 CBCT scans were examined by two groups of dentists, where one group was aided by Diagnocat and the other was unaided. The results for the overall sensitivity and specificity for aided and unaided groups were calculated as an aggregate of all conditions. The sensitivity values for aided and unaided groups were 0.8537 and 0.7672 while specificity was 0.9672 and 0.9616 respectively. There was a statistically significant difference between the groups (p = 0.032). This study showed that the proposed AI system significantly improved the diagnostic capabilities of dentists.

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Conceptualising changes to tobacco and alcohol policy as affecting a single interlinked system

BMC Public Health ◽

10.1186/s12889-020-10000-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Duncan Gillespie ◽

Jenny Hatchard ◽

Hazel Squires ◽

Anna Gilmore ◽

Alan Brennan

Keyword(s):

Health Economic ◽

Policy Change ◽

Conceptual Understanding ◽

Communicable Disease ◽

Model Development ◽

Economic Models ◽

Alcohol Policy ◽

Policy System ◽

The People ◽

Main Components

Abstract Background To support a move towards a coordinated non-communicable disease approach in public health policy, it is important to conceptualise changes to policy on tobacco and alcohol as affecting a single interlinked system. For health economic models to effectively inform policy, the first step in their development should be to develop a conceptual understanding of the system complexity that is likely to affect the outcomes of policy change. Our aim in this study was to support the development and interpretation of health economic models of the effects of changes to tobacco and alcohol policies by developing a conceptual understanding of the main components and mechanisms in the system that links policy change to outcomes. Methods Our study was based on a workshop from which we captured data on participant discussions on the joint tobacco–alcohol policy system. To inform these discussions, we prepared with a literature review and a survey of participants. Participants were academics and policy professionals who work in the United Kingdom. Data were analysed thematically to produce a description of the main components and mechanisms within the system. Results Of the people invited, 24 completed the survey (18 academic, 6 policy); 21 attended the workshop (16 academic, 5 policy). Our analysis identified eleven mechanisms through which individuals might modify the effects of a policy change, which include mechanisms that might lead to linked effects of policy change on tobacco and alcohol consumption. We identified ten mechanisms by which the tobacco and alcohol industries might modify the effects of policy changes, grouped into two categories: Reducing policy effectiveness; Enacting counter-measures. Finally, we identified eighteen research questions that indicate potential avenues for further work to understand the potential outcomes of policy change. Conclusions Model development should carefully consider the ways in which individuals and the tobacco and alcohol industries might modify the effects of policy change, and the extent to which this results in an unequal societal distribution of outcomes. Modelled evidence should then be interpreted in the light of the conceptual understanding of the system that the modelling necessarily simplifies in order to predict the outcomes of policy change.

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Exploring User Information Needs in Online Pet Adoption Profiles

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1071181320641311 ◽

2020 ◽

Vol 64 (1) ◽

pp. 1308-1312

Author(s):

Zoe M. Becerra ◽

Sweta Parmar ◽

Keenan May ◽

Rachel E. Stuck

Keyword(s):

Information Needs ◽

Online Shopping ◽

Physical Characteristics ◽

User Needs ◽

User Group ◽

Animal Shelters ◽

Types Of Information ◽

The Right ◽

And Behavior ◽

Level Of Importance

With the increase of online shopping, animal shelters can use websites to allow potential adopters to view adoptable animals and increase the number of adoptions. However, little research has evaluated the information needs of this user group. This study conducted a user needs analysis to determine the types of information potential adopters want when searching for a new pet, specifically a cat or dog. Twenty-six participants ranked different behavioral and physical characteristics based on the level of importance and identified their top five overall characteristics. In general, cat adopters ranked the cat’s personality and behavior to be very important and dog adopters found physical characteristics highly important. This study shows the importance of understanding potential adopters’ needs to provide relevant and valued information on online pet adoption profiles. The recommendations and insights can be used to develop pet profiles that meet adopters’ needs and help adopters find the right pet.

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Providing Telephone-Based Support for Patients With Haematological Malignancies: A Qualitative Investigation of Expert Nurses

Canadian Journal of Nursing Research ◽

10.1177/08445621211013231 ◽

2021 ◽

pp. 084456212110132

Author(s):

Sarah J. Liptrott ◽

Penny Bee ◽

Karina Lovell

Keyword(s):

Information Needs ◽

Framework Analysis ◽

Dynamic Information ◽

Perceived Needs ◽

Intervention Acceptability ◽

Provider Perspective ◽

Expert Nurses ◽

Cancer Trajectory ◽

Healthcare Interventions ◽

Nurses Perceptions

Background Telephone-based interventions are frequently used to address cancer patient’s needs, often delivered by nurses; however, little is known about nurses’ opinions of such interventions. Purpose The objective of this study was to investigate expert nurses’ perceptions of hemato-oncology patient’s needs, use of telephone interventions providing support and symptom management and intervention acceptability from a service provider perspective. A qualitative study was undertaken with focus group and individual interview. Inductive and deductive data analysis was performed using Framework Analysis and the Theoretical Framework of Acceptability. Results Two themes emerged: (1) perceived needs of haemato-oncology patients across the cancer trajectory – multifactorial influences, dynamic information needs, and continuity of care, (2) acceptability for nurses delivering interventions was determined by identification of need, agreed expectations and organisational support for the intervention. Conclusions Greater understanding of contextual factors for recipients and individuals delivering healthcare interventions may contribute to identification of potential barriers and facilitators to adoption in clinical practice.

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The information needs and behaviour of the Egyptian elderly living in care homes: An exploratory study

IFLA Journal ◽

10.1177/0340035221991563 ◽

2021 ◽

pp. 034003522199156

Author(s):

Essam Mansour

Keyword(s):

Elderly People ◽

Information Seeking ◽

Information Needs ◽

Information Sources ◽

Care Homes ◽

Average Income ◽

Information Awareness ◽

Medical Health ◽

Types Of Information ◽

Elderly Living

The purpose of this study is to investigate the information-seeking behaviour of the Egyptian elderly, including their information needs. A sample of 63 elderly people living in care homes was taken. It was divided into five focus groups. Of the 63 elderly people, 40 were men (63.5%) and 23 women (36.5%). Almost half (47.6%) ranged in aged from 61 to 70. About a quarter (23%) of them held a high school diploma. The highest percentage (28.6%) was labelled as average-income people. The highest percentage (60.3%) was also found to be widows or widowers. The types of information used most by the Egyptian elderly related to physical, medical/health, social, rational and recreational needs. Their information sources varied between formal and informal sources. Nearly two-thirds (63.5%) of them showed that limited knowledge, lack of interest, poor information awareness, aging, loneliness and health problems were the most significant obstacles they faced when seeking information.

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User-centered Requirements for Patient Fluid Intake Monitoring Support

Proceedings of the Human Factors and Ergonomics Society Annual Meeting ◽

10.1177/1071181320641170 ◽

2020 ◽

Vol 64 (1) ◽

pp. 736-740

Author(s):

Ellen J. Bass ◽

Andrew J. Abbate ◽

Yaman Noaiseh ◽

Rose Ann DiMaria-Ghalili

Keyword(s):

Data Analysis ◽

Focus Group ◽

Focus Groups ◽

Real Time ◽

Information Needs ◽

Fluid Intake ◽

Fluid Consumption ◽

Registered Dietitians ◽

Group Data ◽

Focus Group Data

There is a need to support patients with monitoring liquid intake. This work addresses development of requirements for real-time and historical displays and reports with respect to fluid consumption as well as alerts based on critical clinical thresholds. We conducted focus groups with registered nurses and registered dietitians in order to identify the information needs and alerting criteria to support fluid consumption measurement. This paper presents results of the focus group data analysis and the related requirements resulting from the analysis.

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Development of a theory-based HPV vaccine promotion comic book for East African adolescents in the US

BMC Public Health ◽

10.1186/s12889-021-11005-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Isabelle Celentano ◽

Rachel L. Winer ◽

Sou Hyun Jang ◽

Anisa Ibrahim ◽

Farah Bille Mohamed ◽

...

Keyword(s):

Focus Group ◽

Hpv Vaccine ◽

Information Needs ◽

Cultural Beliefs ◽

Comic Book ◽

East African ◽

Step Process ◽

Group Data ◽

The Us ◽

Focus Group Data

Abstract Background Human Papillomavirus (HPV) vaccine uptake is low among East African adolescents in the US. Adolescents’ preferences influence HPV vaccine decisions, yet few interventions exist that address East African adolescents’ beliefs about HPV vaccines. We describe a multi-step process on how to create a theory-based comic book by integrating empirical findings, theory and focus group data from East African parents in the US. Methods Our multi-methods process included conducting focus groups with Somali, Ethiopian, and Eritrean mothers (n = 30) to understand mothers and adolescents socio-cultural beliefs and information needs about the HPV vaccine, creating comic book messages integrating the focus group findings, and assessing the acceptability of the finalized comic book among Somali, Ethiopian, and Eritrean adolescents (n = 134). Results We identified categories around socio-cultural beliefs (such ethnic representation and concerns about pork gelatin in vaccines), HPV vaccine information needs, and diffusion of information. We then mapped the categories to theoretical constructs and operationalized them into the comic book. Finally, we describe the overall acceptability of the comic book and specifics on comic book structure, appeal of characters, and message relevance. Conclusions A rigorous multi-step process that integrates theory and focus group data can help create culturally appropriate health messages that can educate and appeal to the community.

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AN ARTIFICIAL INTELLIGENT APPROACH TO TRAFFIC ACCIDENT ESTIMATION: MODEL DEVELOPMENT AND APPLICATION

Transport ◽

10.3846/1648-4142.2009.24.135-142 ◽

2009 ◽

Vol 24 (2) ◽

pp. 135-142 ◽

Cited By ~ 21

Author(s):

Ali Payıdar Akgüngör ◽

Erdem Doğan

Keyword(s):

Genetic Algorithm ◽

Model Development ◽

Back Propagation ◽

Linear Functions ◽

Model Parameters ◽

Ann Model ◽

Back Propagation Algorithm ◽

Estimation Model ◽

Average Growth ◽

Feed Forward Back Propagation

This study proposes an Artificial Neural Network (ANN) model and a Genetic Algorithm (GA) model to estimate the number of accidents (A), fatalities (F) and injuries (I) in Ankara, Turkey, utilizing the data obtained between 1986 and 2005. For model development, the number of vehicles (N), fatalities, injuries, accidents and population (P) were selected as model parameters. In the ANN model, the sigmoid and linear functions were used as activation functions with the feed forward‐back propagation algorithm. In the GA approach, two forms of genetic algorithm models including a linear and an exponential form of mathematical expressions were developed. The results of the GA model showed that the exponential model form was suitable to estimate the number of accidents and fatalities while the linear form was the most appropriate for predicting the number of injuries. The best fit model with the lowest mean absolute errors (MAE) between the observed and estimated values is selected for future estimations. The comparison of the model results indicated that the performance of the ANN model was better than that of the GA model. To investigate the performance of the ANN model for future estimations, a fifteen year period from 2006 to 2020 with two possible scenarios was employed. In the first scenario, the annual average growth rates of population and the number of vehicles are assumed to be 2.0 % and 7.5%, respectively. In the second scenario, the average number of vehicles per capita is assumed to reach 0.60, which represents approximately two and a half‐fold increase in fifteen years. The results obtained from both scenarios reveal the suitability of the current methods for road safety applications.

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A new ensemble-based statistical methodology to verify changes in weather and climate models

10.5194/egusphere-egu21-4255 ◽

2021 ◽

Author(s):

Christian Zeman ◽

Christoph Schär

Keyword(s):

Climate Models ◽

Climate Model ◽

Numerical Models ◽

Hypothesis Test ◽

Model Development ◽

Atmospheric Model ◽

Statistical Hypothesis ◽

Model Parameters ◽

Rounding Errors ◽

Weather And Climate

Since their first operational application in the 1950s, atmospheric numerical models have become essential tools in weather and climate prediction. As such, they are a constant subject to changes, thanks to advances in computer systems, numerical methods, and the ever increasing knowledge about the atmosphere of Earth. Many of the changes in today's models relate to seemingly unsuspicious modifications, associated with minor code rearrangements, changes in hardware infrastructure, or software upgrades. Such changes are meant to preserve the model formulation, yet the verification of such changes is challenged by the chaotic nature of our atmosphere - any small change, even rounding errors, can have a big impact on individual simulations. Overall this represents a serious challenge to a consistent model development and maintenance framework.Here we propose a new methodology for quantifying and verifying the impacts of minor atmospheric model changes, or its underlying hardware/software system, by using ensemble simulations in combination with a statistical hypothesis test. The methodology can assess effects of model changes on almost any output variable over time, and can also be used with different hypothesis tests.We present first applications of the methodology with the regional weather and climate model COSMO. The changes considered include a major system upgrade of the supercomputer used, the change from double to single precision floating-point representation, changes in the update frequency of the lateral boundary conditions, and tiny changes to selected model parameters. While providing very robust results, the methodology also shows a large sensitivity to more significant model changes, making it a good candidate for an automated tool to guarantee model consistency in the development cycle.

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