Fast extraction of high-quality framework-specific models from application code

2008 ◽  
Vol 16 (1) ◽  
pp. 101-144 ◽  
Author(s):  
Michał Antkiewicz ◽  
Thiago Tonelli Bartolomei ◽  
Krzysztof Czarnecki
Keyword(s):  
High Quality ◽  
Quality Framework ◽  
Fast Extraction

scholarly journals The use of the Nursing Activities Score in clinical settings: an integrative review

2015 ◽  
Vol 49 (spe) ◽  
pp. 147-156 ◽  
Author(s):  
Joanie Lachance ◽  
Frédéric Douville ◽  
Clémence Dallaire ◽  
Katia Grillo Padilha ◽  
Maria Cecilia Gallani
Keyword(s):  
Health Care ◽  
Health Care Quality ◽  
Care Quality ◽  
Clinical Settings ◽  
Framework Structure ◽  
Inclusion Criteria ◽  
Delivery Method ◽  
Process And Outcome ◽  
Structure Category ◽  
Quality Framework

ABSTRACT Objective analyze how studies have approached the results obtained from the application of the Nursing Activities Score (NAS) based on Donabedian’s model of healthcare organization and delivery. Method CINAHL and PubMed databases were searched for papers published between 2003 and March 2015. Results 36 articles that met the inclusion criteria were reviewed and double-coded by three independent coders and analyzed based on the three elements of Donabedian’s health care quality framework: structure, process and outcome. The most frequently addressed, but not always tested, variables were those that fell into the structure category. Conclusion variables that fell into the process category were used less frequently. Beside NAS, the most frequently used variables in the outcome category were mortality and length of stay. However, no study used a quality framework for healthcare or NAS to evaluate costs, and it is recommended that further research should explore this approach.

scholarly journals Future orientation and fertility: cross-national evidence using Google search

2020 ◽  
Author(s):  
Nicolò Cavalli
Keyword(s):  
Web Search ◽  
Future Orientation ◽  
Fertility Rates ◽  
Fertility Decisions ◽  
Country Level ◽  
The World ◽  
Search Data ◽  
Quality Framework ◽  
Google Search ◽  
Cross National

Using digital traces to investigate demographic behaviours, I leverage in this paper aggregated web search data to develop a Future Orientation Index for 200 countries and territories across the world. This index is expressed as the ratio of Google search volumes for ‘next year’ (e.g., 2021) to search volumes for ‘current year’ (e.g., 2020), adjusted for country-level internet penetration rates. I show that countries with lower levels of future orientation also have higher levels of fertility. Fertility rates decrease quickly as future orientation levels increase; but at the highest levels of future orientation, this correlation flattens out. Theoretically, I reconstruct the role that varying degrees of future orientation might play in fertility decisions by incorporating advances in behavioural economics into a traditional quantity-quality framework à la Becker.

scholarly journals General Doctor's Consultation Work Begins before Entering the Patient and does not End when Patient Comes Out

2020 ◽  
Vol 1 (2) ◽  
pp. 6-14
Author(s):  
Jose Luis Turabian
Keyword(s):  
Health Promotion ◽  
General Practitioner ◽  
Previous History ◽  
General Medicine ◽  
Management Plan ◽  
Case Finding ◽  
Limited Resources ◽  
Technology Skills ◽  
Good Relationship ◽  
Quality Framework

The consultation is the activity of meeting and communication between an individual and the doctor for the knowledge and solution of a health problem. In today's busy world of general medicine, constant demands for the general practitioner (GP) arise: she or he should not only make a diagnosis not only should make a differential diagnosis during consultation, but must also establish a good relationship, explore patient ideas, concerns and expectations and negotiate a management plan, taking into account limited resources, the quality framework and results, having Information technology skills, plus, the need to promote health during any consultation. Normally the GP has only 10 minutes to achieve all that, as well as to manage your own emotions, agendas and uncertainty. In this way, novice doctors may find it difficult to move in this situation of complexity, and they can also observe a gap in the literature that really guides them in practice. Rigorous preparation is the key to success for many endeavours. Some tips to perform an efficient and safe consultation work in general medicine are suggested: 1) Focus on the next patient; 2) Preparing the consultation before entering the patient, memorizing the patient's previous history; 3) Establishing a connection with the patient; 4) Remembering the elements that must be in each consultation (the current reason, update other previous processes, chronic diseases and continued attention, "case finding", health promotion); 5) Striking a balance between empathy and assertiveness; 6) Putting in writing and contextualized the clinical record; and 7) Making reflection-safety questions, learning questions, and preparation questions for the next visit. Rigorous preparation is the key to success for the general practitioner in every consultation. Think about these topics of the consultation before doing it, and after it, prepare the next consultation of that patient. All these things are force multipliers.

scholarly journals Facilitating Harmonized Data Quality Assessments. A Data Quality Framework for Observational Health Research Data Collections With Software Implementations in R

2020 ◽  
Author(s):  
Carsten Schmidt ◽  
Stephan Struckmann ◽  
Cornelia Enzenbach ◽  
Achim Reineke ◽  
Jürgen Stausberg ◽  
...  
Keyword(s):  
Data Quality ◽  
Quality Indicators ◽  
Health Research ◽  
Research Data ◽  
Formal Concept ◽  
Software Implementations ◽  
Quality Framework ◽  
Data Collections ◽  
Quality Assessments ◽  
Data Quality Indicators

Abstract Background No standards exist for the handling and reporting of data quality in health research. This work introduces a data quality framework for observational health research data collections with supporting software implementations to facilitate harmonized data quality assessments. Methods Developments were guided by the evaluation of an existing data quality framework and literature reviews. Functions for the computation of data quality indicators were written in R. The concept and implementations are illustrated based on data from the population-based Study of Health in Pomerania (SHIP).Results The data quality framework comprises 34 data quality indicators. These target three aspects of data quality: compliance with pre-specified structural and technical requirements (Integrity), presence of data values (completeness), and error in the data values (correctness). R functions calculate data quality metrics based on the provided study data and metadata and R Markdown reports are generated. Guidance on the concept and tools is available through a dedicated website. Conclusions The presented data quality framework is the first of its kind for observational health research data collections that links a formal concept to implementations in R. The framework and tools facilitate harmonized data quality assessments in pursue of transparent and reproducible research. Application scenarios comprise data quality monitoring while a study is carried out as well as performing an initial data analysis before starting substantive scientific analyses.

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