Supporting Healthcare Executive Managers’ Decisions Through Dashboards

2016 ◽  
Vol 15 (01) ◽  
pp. 1650005
Author(s):  
Sabri Erdem ◽  
Turan Tolgay Kizilelma ◽  
Ceren Altuntaş Vural
Keyword(s):  
Information Processing ◽  
Conceptual Framework ◽  
Research Design ◽  
Information Needs ◽  
Data Gathering ◽  
Healthcare Management ◽  
Design Data ◽  
Processing Technologies ◽  
Information Visualisation ◽  
Executive Managers

Information visualisation plays an important role for executives in order to drive business effectively and efficiently. Dashboard design, which is one of the best tools of visualization to meet the information needs at adequate levels, is becoming more important parallel to advances in information processing technologies. This study aims to provide a conceptual framework for developing a dashboard for executives. Healthcare management was chosen to demonstrate the methodology of research design, data gathering and visualisation examples. Results show that the study is applicable to other areas as well to meet the information requirements of top and mid-level managers.

Museum Studies

2020 ◽  
pp. 516-537
Author(s):  
Erica L. Tucker
Keyword(s):  
Qualitative Research ◽  
Natural History ◽  
Case Studies ◽  
Research Design ◽  
Museum Studies ◽  
Historic Sites ◽  
Design Data ◽  
Museum Visitors ◽  
Ethnographic Fieldwork ◽  
Data Analyses

This chapter describes and discusses the major qualitative research methods used to study museums. These methods include analyses of visual displays and reconstructions; interviews with museum visitors, professionals, and stakeholders; as well as ethnographic fieldwork in museum settings. The chapter explores how these methods can be adapted to the study of exhibits, galleries, programs, and museums as knowledge-generating institutions from a range of case studies conducted by museum practitioners, anthropologists, historians, and other museum studies scholars at a variety of museums. Case studies are drawn from works that examine ethnographic, natural history, art and community museums as well as historic sites. Approaches to research design, data analyses, and writing up are also examined.

The 6C model for accurately capturing the patient’s medical history

Diagnosis ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Taro Shimizu
Keyword(s):  
Artificial Intelligence ◽  
Differential Diagnosis ◽  
Patient Safety ◽  
Information Processing ◽  
Safety Concern ◽  
Data Gathering ◽  
Diagnostic Errors ◽  
Accurate Diagnosis ◽  
History Taking ◽  
Novel Approach

Abstract Diagnostic errors are an internationally recognized patient safety concern, and leading causes are faulty data gathering and faulty information processing. Obtaining a full and accurate history from the patient is the foundation for timely and accurate diagnosis. A key concept underlying ideal history acquisition is “history clarification,” meaning that the history is clarified to be depicted as clearly as a video, with the chronology being accurately reproduced. A novel approach is presented to improve history-taking, involving six dimensions: Courtesy, Control, Compassion, Curiosity, Clear mind, and Concentration, the ‘6 C’s’. We report a case that illustrates how the 6C approach can improve diagnosis, especially in relation to artificial intelligence tools that assist with differential diagnosis.

Conceptual Framework and Research Design

2020 ◽  
pp. 9-33
Author(s):  
Siegfried Nagel ◽  
Karsten Elmose-Østerlund ◽  
Bjarne Ibsen ◽  
Jeroen Scheerder
Keyword(s):  
Conceptual Framework ◽  
Research Design

scholarly journals Patterns of Family Support in Cervical Cancer Survivors with High Resilience

2019 ◽  
Vol 9 (1) ◽  
pp. 1604-1606
Keyword(s):  
Cervical Cancer ◽  
Qualitative Methods ◽  
Cancer Survivors ◽  
Family Support ◽  
Research Design ◽  
Emotional Support ◽  
Design Data ◽  
Research Results ◽  
Descriptive Research ◽  
Resilience Scale

This study is aimed to explore the patterns of family support in cervical cancer survivors. This study is focused on explaining the kinds of patterns of family support received by cervical cancer survivors who had experienced high-resilience. It implements qualitative methods with descriptive research design. Data is collected by screening using resilience scale and interview. The analysed data include interview results obtained from cervical cancer survivors who had experienced high resilience. Research results showed that high resilience among the three cervical cancer survivors is related to family support. The patterns of family support received by the three participants include closeness, receptors, and durability. The three participants also received at least three out of four patterns of family supports concrete support, emotional support, informative support, and award support. Types of support most needed by the three participants are concrete support and emotional support.

scholarly journals Methodology in the Mirror: a Living, Systematic Review of Works in Quantitative Ethnography

2021 ◽  
Author(s):  
Szilvia Zörgő ◽  
Gjalt - Jorn Ygram Peters ◽  
Clare Porter ◽  
Marcia Moraes ◽  
Savannah Donegan ◽  
...  
Keyword(s):  
Systematic Review ◽  
Data Collection ◽  
Conceptual Framework ◽  
Research Design ◽  
Qualitative Methodology ◽  
Lingua Franca ◽  
Segmentation Analysis ◽  
Shed Light

Quantitative Ethnography is a nascent field now formulating the specifics of its conceptual framework and terminology for a unified, quantitative – qualitative methodology. Our living, systematic review aims to shed light on decisions in research design that the community has made thus far in the domain of data collection, coding & segmentation, analysis, and how Quantitative Ethnography as a methodology is conceptualized. Our analysis intends to spur discussions on these issues within the community and help establish a lingua franca.

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