Empirically supporting school STEM culture—The creation and validation of the STEM Culture Assessment Tool (STEM‐CAT)

185 Background: Cancer Care Ontario’s Drug Formulary is a web-based drug information resource. Patient information is currently provided as single-drug information sheets, with a limited number of multi-drug regimen information sheets (RIS) for breast and lung cancer treatments. Patients identified a need to create additional, high-quality, “user-friendly” RIS. Objectives of this project were to 1) engage patients and caregivers in RIS redesign; 2) evaluate the original vs a redesigned model RIS; and 3) use the model RIS template to create additional RIS across disease sites. Methods: The project team included a patient and family advisor (PFA) and clinical and research experts. This was a qualitative study between August 2017 to May 2019. A focus group (FG) was conducted with 5 PFAs to identify and prioritize drug information needs. A model RIS was designed, incorporating FG input and health literacy best practices. RIS were evaluated through blinded comparative cognitive interviews with 13 PFAs, to assess RIS for usability, understandability and content relevance. Evaluation informed iterative revisions. RIS were also evaluated by clinical and education experts using the Patient Education Materials Assessment Tool (PEMAT). An RIS style guide was developed to inform the creation of future RIS. Ethics approval was obtained from the University of Toronto. Results: The FG prioritized information on regimen details, Dos and Don’ts while on treatment, drug interactions, side effects and contact information. Guidance was provided on simplifying language, highlighting important information and aesthetics. Cognitive interviews consistently reported preference for model RIS over original RIS in most domains. PEMAT scores for original versus model RIS were 64% and 94% respectively (for understandability) and 60% and 82% respectively (for actionability). To date, the style guide has informed the creation of RIS for 10 high-use regimens. Conclusions: PFA and clinician co-design along with health literacy best practices informed measurable improvements in RIS. The style guide will enable the future creation and ongoing evaluation of high-quality RIS to enhance the cancer treatment experience for patients and caregivers.

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Business Intelligence as a Service

Business Intelligence ◽

10.4018/978-1-4666-9562-7.ch101 ◽

2016 ◽

pp. 2030-2048

Author(s):

Marco Spruit ◽

Tim de Boer

Keyword(s):

Cloud Computing ◽

Business Intelligence ◽

Assessment Tool ◽

Geographic Location ◽

Capability Maturity Model ◽

Maturity Model ◽

High Expectations ◽

Capability Maturity ◽

Hype Cycle ◽

The Creation

Demand for business intelligence (BI) applications continues to grow even at a time when demand for most information technology (IT) products is low, showing the importance of BI products for a modern organization. However, globalization changes the way organizations use BI, where geographic location and time independency is becoming more and more important. Gartner's hype-cycle on BI depicts the technology of BI as a Service as being almost on top of the hype cycle, indicating there are high expectations of this new technology. This research advances on existing literature on business intelligence and cloud computing from a development perspective by introducing the concept of business intelligence as a service (BIaaS). The most important deliverable is the BIaaS capability maturity model (CMM) that is introduced here. The BIaaS CMM explains the conceptual model of BIaaS by the creation of the first BIaaS capability model containing key capabilities of BIaaS. The capability model is further enhanced with maturity levels depicting the importance of each BIaaS capability, a maturity matrix suggesting a roadmap for BIaaS solution development, and a BIaaS assessment model introducing a tool for finding problem areas in existing BIaaS solutions. The developed BIaaS CMM ought to support (starting) BIaaS vendors to develop BIaaS solutions by providing an assessment tool for BIaaS solutions. The assessment outcome provides the current maturity of the BIaaS solution and also includes problem areas for solution improvement. The introduction of the CApability Maturity Positioning (CAMP) method for the development of a maturity matrix, which results in the BIaaS maturity model, is significantly different from conventional maturity modeling. To calculate the weight of each capability from the BIaaS capability model, a thorough product review of existing business intelligence and cloud computing products is performed. Analysis of the results and normalizing the outcome of that analysis together with the introduction of a calculation mapping, is input for the creation of the maturity matrix. The maturity matrix is the essential foundation for the developed business intelligence as a Service capability maturity model, which is the main deliverable of this research.

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Business Intelligence as a Service

International Journal of Business Intelligence Research ◽

10.4018/ijbir.2014100103 ◽

2014 ◽

Vol 5 (4) ◽

pp. 26-43 ◽

Cited By ~ 2

Author(s):

Marco Spruit ◽

Tim de Boer

Keyword(s):

Cloud Computing ◽

Business Intelligence ◽

Assessment Tool ◽

Geographic Location ◽

Assessment Model ◽

Capability Maturity Model ◽

Maturity Model ◽

Capability Maturity ◽

Hype Cycle ◽

The Creation

Demand for business intelligence (BI) applications continues to grow even at a time when demand for most information technology (IT) products is low, showing the importance of BI products for a modern organization. However, globalization changes the way organizations use BI, where geographic location and time independency is becoming more and more important. Gartner's hype-cycle on BI depicts the technology of BI as a Service as being almost on top of the hype cycle, indicating there are high expectations of this new technology. This research advances on existing literature on business intelligence and cloud computing from a development perspective by introducing the concept of business intelligence as a service (BIaaS). The most important deliverable is the BIaaS capability maturity model (CMM) that is introduced here. The BIaaS CMM explains the conceptual model of BIaaS by the creation of the first BIaaS capability model containing key capabilities of BIaaS. The capability model is further enhanced with maturity levels depicting the importance of each BIaaS capability, a maturity matrix suggesting a roadmap for BIaaS solution development, and a BIaaS assessment model introducing a tool for finding problem areas in existing BIaaS solutions. The developed BIaaS CMM ought to support (starting) BIaaS vendors to develop BIaaS solutions by providing an assessment tool for BIaaS solutions. The assessment outcome provides the current maturity of the BIaaS solution and also includes problem areas for solution improvement. The introduction of the CApability Maturity Positioning (CAMP) method for the development of a maturity matrix, which results in the BIaaS maturity model, is significantly different from conventional maturity modeling. To calculate the weight of each capability from the BIaaS capability model, a thorough product review of existing business intelligence and cloud computing products is performed. Analysis of the results and normalizing the outcome of that analysis together with the introduction of a calculation mapping, is input for the creation of the maturity matrix. The maturity matrix is the essential foundation for the developed business intelligence as a Service capability maturity model, which is the main deliverable of this research.

Download Full-text