ID Consecutivo : 1811

Titulo

serie

Editorial

 

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Paginas Existencias 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Resumen
Competency-based medical education (CBME) is changing the way physicians are educated,1–4 with a heavy emphasis on quantifying and qualifying their performance via robust assessments. The central tenet of CBME is that trainees must demonstrate competence in applying acquired skills during patient care activities,5 and CBME requires assessment strategies that ensure trainees apply their knowledge, skills, and abilities in authentic or simulated environments.6 This necessity for direct observation and assessment of trainees’ performance has resulted in a shift toward workplace-based assessments (WBAs) as a primary method of assessment. There is no single comprehensive WBA assessment tool, and experts have argued that decisions regarding trainees’ progression should be based on aggregates of multiple measures of performance using both qualitative and quantitative methods.6,7 The implementation of WBAs allows educators to identify patterns in the development of knowledge, skills, and performance. While educators and researchers have paid considerable attention to understanding patterns in WBA data, less attention has been paid to missing data. Identifying and understanding potential patterns underlying missing data is an important step in accurately interpreting WBA data. While mechanisms exist to deal with missing data (eg, multiple imputation and maximum likelihood methods), many of these presume that data are missing at random.8 This may not be the case in the context of WBA portfolios. For example, residents may be more likely to complete WBAs for tasks that they enjoy and/or perform well; consequently, there may be missing data for more poorly developed knowledge, skills, and abilities. Similarly, certain WBA tools (eg, multi-source feedback) may be particularly challenging to complete because of the logistics of collecting the data. Nonrandomly missing data could threaten the inherent validity of WBA portfolios. The purpose of this study is twofold. First, we examined whether data are, in fact, missing at random across various competencies within the context of our local WBA system. Second, we assessed whether the amount of missing data correlated with overall resident performance as determined by a panel of faculty from the residency education committee

 

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Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Desarrollo Profesional Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

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Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

Signatura topografica:

ID Consecutivo : 1811

Titulo

Editorial

 

Año de publicación Edición Primera Segunda Tercera Cuarta Quita Sexta Septima Octava Novena Decima Selecione una

Paginas Existencias 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

Resumen
Competency-based medical education (CBME) is changing the way physicians are educated,1–4 with a heavy emphasis on quantifying and qualifying their performance via robust assessments. The central tenet of CBME is that trainees must demonstrate competence in applying acquired skills during patient care activities,5 and CBME requires assessment strategies that ensure trainees apply their knowledge, skills, and abilities in authentic or simulated environments.6 This necessity for direct observation and assessment of trainees’ performance has resulted in a shift toward workplace-based assessments (WBAs) as a primary method of assessment. There is no single comprehensive WBA assessment tool, and experts have argued that decisions regarding trainees’ progression should be based on aggregates of multiple measures of performance using both qualitative and quantitative methods.6,7 The implementation of WBAs allows educators to identify patterns in the development of knowledge, skills, and performance. While educators and researchers have paid considerable attention to understanding patterns in WBA data, less attention has been paid to missing data. Identifying and understanding potential patterns underlying missing data is an important step in accurately interpreting WBA data. While mechanisms exist to deal with missing data (eg, multiple imputation and maximum likelihood methods), many of these presume that data are missing at random.8 This may not be the case in the context of WBA portfolios. For example, residents may be more likely to complete WBAs for tasks that they enjoy and/or perform well; consequently, there may be missing data for more poorly developed knowledge, skills, and abilities. Similarly, certain WBA tools (eg, multi-source feedback) may be particularly challenging to complete because of the logistics of collecting the data. Nonrandomly missing data could threaten the inherent validity of WBA portfolios. The purpose of this study is twofold. First, we examined whether data are, in fact, missing at random across various competencies within the context of our local WBA system. Second, we assessed whether the amount of missing data correlated with overall resident performance as determined by a panel of faculty from the residency education committee

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Desarrollo Profesional Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

Signatura topografica:

ID Consecutivo : 1811

Titulo

Tipo : Ley Decreto Norma Resolucion Circular Directiva

 

Año de publicación

Resumen
Competency-based medical education (CBME) is changing the way physicians are educated,1–4 with a heavy emphasis on quantifying and qualifying their performance via robust assessments. The central tenet of CBME is that trainees must demonstrate competence in applying acquired skills during patient care activities,5 and CBME requires assessment strategies that ensure trainees apply their knowledge, skills, and abilities in authentic or simulated environments.6 This necessity for direct observation and assessment of trainees’ performance has resulted in a shift toward workplace-based assessments (WBAs) as a primary method of assessment. There is no single comprehensive WBA assessment tool, and experts have argued that decisions regarding trainees’ progression should be based on aggregates of multiple measures of performance using both qualitative and quantitative methods.6,7 The implementation of WBAs allows educators to identify patterns in the development of knowledge, skills, and performance. While educators and researchers have paid considerable attention to understanding patterns in WBA data, less attention has been paid to missing data. Identifying and understanding potential patterns underlying missing data is an important step in accurately interpreting WBA data. While mechanisms exist to deal with missing data (eg, multiple imputation and maximum likelihood methods), many of these presume that data are missing at random.8 This may not be the case in the context of WBA portfolios. For example, residents may be more likely to complete WBAs for tasks that they enjoy and/or perform well; consequently, there may be missing data for more poorly developed knowledge, skills, and abilities. Similarly, certain WBA tools (eg, multi-source feedback) may be particularly challenging to complete because of the logistics of collecting the data. Nonrandomly missing data could threaten the inherent validity of WBA portfolios. The purpose of this study is twofold. First, we examined whether data are, in fact, missing at random across various competencies within the context of our local WBA system. Second, we assessed whether the amount of missing data correlated with overall resident performance as determined by a panel of faculty from the residency education committee

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Desarrollo Profesional Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1811

Titulo

Autor como conferencia

Paginas

 

Año de publicación

Resumen
Competency-based medical education (CBME) is changing the way physicians are educated,1–4 with a heavy emphasis on quantifying and qualifying their performance via robust assessments. The central tenet of CBME is that trainees must demonstrate competence in applying acquired skills during patient care activities,5 and CBME requires assessment strategies that ensure trainees apply their knowledge, skills, and abilities in authentic or simulated environments.6 This necessity for direct observation and assessment of trainees’ performance has resulted in a shift toward workplace-based assessments (WBAs) as a primary method of assessment. There is no single comprehensive WBA assessment tool, and experts have argued that decisions regarding trainees’ progression should be based on aggregates of multiple measures of performance using both qualitative and quantitative methods.6,7 The implementation of WBAs allows educators to identify patterns in the development of knowledge, skills, and performance. While educators and researchers have paid considerable attention to understanding patterns in WBA data, less attention has been paid to missing data. Identifying and understanding potential patterns underlying missing data is an important step in accurately interpreting WBA data. While mechanisms exist to deal with missing data (eg, multiple imputation and maximum likelihood methods), many of these presume that data are missing at random.8 This may not be the case in the context of WBA portfolios. For example, residents may be more likely to complete WBAs for tasks that they enjoy and/or perform well; consequently, there may be missing data for more poorly developed knowledge, skills, and abilities. Similarly, certain WBA tools (eg, multi-source feedback) may be particularly challenging to complete because of the logistics of collecting the data. Nonrandomly missing data could threaten the inherent validity of WBA portfolios. The purpose of this study is twofold. First, we examined whether data are, in fact, missing at random across various competencies within the context of our local WBA system. Second, we assessed whether the amount of missing data correlated with overall resident performance as determined by a panel of faculty from the residency education committee

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Desarrollo Profesional Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1811

Titulo

 

Año de publicación

Producción de publicación

Volumen

ISBN

Frecuencia

Resumen
Competency-based medical education (CBME) is changing the way physicians are educated,1–4 with a heavy emphasis on quantifying and qualifying their performance via robust assessments. The central tenet of CBME is that trainees must demonstrate competence in applying acquired skills during patient care activities,5 and CBME requires assessment strategies that ensure trainees apply their knowledge, skills, and abilities in authentic or simulated environments.6 This necessity for direct observation and assessment of trainees’ performance has resulted in a shift toward workplace-based assessments (WBAs) as a primary method of assessment. There is no single comprehensive WBA assessment tool, and experts have argued that decisions regarding trainees’ progression should be based on aggregates of multiple measures of performance using both qualitative and quantitative methods.6,7 The implementation of WBAs allows educators to identify patterns in the development of knowledge, skills, and performance. While educators and researchers have paid considerable attention to understanding patterns in WBA data, less attention has been paid to missing data. Identifying and understanding potential patterns underlying missing data is an important step in accurately interpreting WBA data. While mechanisms exist to deal with missing data (eg, multiple imputation and maximum likelihood methods), many of these presume that data are missing at random.8 This may not be the case in the context of WBA portfolios. For example, residents may be more likely to complete WBAs for tasks that they enjoy and/or perform well; consequently, there may be missing data for more poorly developed knowledge, skills, and abilities. Similarly, certain WBA tools (eg, multi-source feedback) may be particularly challenging to complete because of the logistics of collecting the data. Nonrandomly missing data could threaten the inherent validity of WBA portfolios. The purpose of this study is twofold. First, we examined whether data are, in fact, missing at random across various competencies within the context of our local WBA system. Second, we assessed whether the amount of missing data correlated with overall resident performance as determined by a panel of faculty from the residency education committee

 

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Desarrollo Profesional Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1811

Titulo videos

Año de publicación

Resumen
Competency-based medical education (CBME) is changing the way physicians are educated,1–4 with a heavy emphasis on quantifying and qualifying their performance via robust assessments. The central tenet of CBME is that trainees must demonstrate competence in applying acquired skills during patient care activities,5 and CBME requires assessment strategies that ensure trainees apply their knowledge, skills, and abilities in authentic or simulated environments.6 This necessity for direct observation and assessment of trainees’ performance has resulted in a shift toward workplace-based assessments (WBAs) as a primary method of assessment. There is no single comprehensive WBA assessment tool, and experts have argued that decisions regarding trainees’ progression should be based on aggregates of multiple measures of performance using both qualitative and quantitative methods.6,7 The implementation of WBAs allows educators to identify patterns in the development of knowledge, skills, and performance. While educators and researchers have paid considerable attention to understanding patterns in WBA data, less attention has been paid to missing data. Identifying and understanding potential patterns underlying missing data is an important step in accurately interpreting WBA data. While mechanisms exist to deal with missing data (eg, multiple imputation and maximum likelihood methods), many of these presume that data are missing at random.8 This may not be the case in the context of WBA portfolios. For example, residents may be more likely to complete WBAs for tasks that they enjoy and/or perform well; consequently, there may be missing data for more poorly developed knowledge, skills, and abilities. Similarly, certain WBA tools (eg, multi-source feedback) may be particularly challenging to complete because of the logistics of collecting the data. Nonrandomly missing data could threaten the inherent validity of WBA portfolios. The purpose of this study is twofold. First, we examined whether data are, in fact, missing at random across various competencies within the context of our local WBA system. Second, we assessed whether the amount of missing data correlated with overall resident performance as determined by a panel of faculty from the residency education committee

 

Adjunte la Imagen del Video

 

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Desarrollo Profesional Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5180525/

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores

 

ID Consecutivo : 1811

Titulo

Titulo Revista

ISSN

Año de publicación Suplemento

Numero: Volumen

Pagina Inicial Pagina Final

Resumen
Competency-based medical education (CBME) is changing the way physicians are educated,1–4 with a heavy emphasis on quantifying and qualifying their performance via robust assessments. The central tenet of CBME is that trainees must demonstrate competence in applying acquired skills during patient care activities,5 and CBME requires assessment strategies that ensure trainees apply their knowledge, skills, and abilities in authentic or simulated environments.6 This necessity for direct observation and assessment of trainees’ performance has resulted in a shift toward workplace-based assessments (WBAs) as a primary method of assessment. There is no single comprehensive WBA assessment tool, and experts have argued that decisions regarding trainees’ progression should be based on aggregates of multiple measures of performance using both qualitative and quantitative methods.6,7 The implementation of WBAs allows educators to identify patterns in the development of knowledge, skills, and performance. While educators and researchers have paid considerable attention to understanding patterns in WBA data, less attention has been paid to missing data. Identifying and understanding potential patterns underlying missing data is an important step in accurately interpreting WBA data. While mechanisms exist to deal with missing data (eg, multiple imputation and maximum likelihood methods), many of these presume that data are missing at random.8 This may not be the case in the context of WBA portfolios. For example, residents may be more likely to complete WBAs for tasks that they enjoy and/or perform well; consequently, there may be missing data for more poorly developed knowledge, skills, and abilities. Similarly, certain WBA tools (eg, multi-source feedback) may be particularly challenging to complete because of the logistics of collecting the data. Nonrandomly missing data could threaten the inherent validity of WBA portfolios. The purpose of this study is twofold. First, we examined whether data are, in fact, missing at random across various competencies within the context of our local WBA system. Second, we assessed whether the amount of missing data correlated with overall resident performance as determined by a panel of faculty from the residency education committee

 

Base de datos bibliográfica Base de datos bibliográfica Seleccione una Access Medicine Biblioteca VirtualenSalud(BVS) Cochrane Central Dialnet Lilacs-Literatura Latinoamericana en Ciencias de la Salud Medline-PubMed Redalyc ScienceDirect SciELO-Scientific Electronic Library Online WHOLIS Otra

Imagen de portada

Adjunte la portada del libro Si no tiene una imagen, descargue aqui la imagen de Ascofame

 

Idioma Español Inglés Portugués Francés Alemán

 

Tipo de Acceso

Restringido(ASCOFAME)

Libre

Registrado

Palabras clave

Coleccion ASCOFAME: Desarrollo Profesional Desarrollo Profesional continuo Gestion curricular Calidad y acreditacion Evaluacion Investigacion Desarrollo Profesional

Disponibilidad:	Digital	Físico	Físico y Digital	Link Externo

Cargue el Documento

Ingrese el Link: ejemplo: http://www.google.com.co

 

Publico	Pregrado	Posgrado	Decanatura
Objetivo:	Docentes	Médicos	Investigadores
	Clínicos	Educadores Médicos	Otros profesionales de la salud
	Evaluadores