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1. The HEART score in predicting major adverse cardiac events in patients presenting to the emergency department with possible acute coronary syndrome: protocol for a systematic review and meta-analysis

Author

Christopher Byrne, Cristian Toarta, Barbra Backus, and Tim Holt

Subjects
Emergency department, Acute coronary syndrome, HEART score, Major adverse cardiac events, Prognosis, Medicine
Abstract

Abstract Background Acute coronary syndrome (ACS) is a common, sometimes difficult to diagnose spectrum of diseases occurring after abrupt reduction in blood flow through a coronary artery. Given the diagnostic challenge, it is sensible for emergency physicians to have an approach to prognosticate patients with possible ACS. Multiple prediction models have been developed to help identify patients at increased risk of adverse outcomes. The HEART score is the first model to be derived, validated, and undergo clinical impact studies in emergency department (ED) patients with possible ACS. Objective To develop a protocol for a prognostic systematic review of the literature evaluating the HEART score as a predictor of major adverse cardiac events (MACE) in patients presenting to the ED with possible ACS. Methods/design This protocol is reported according to the PRISMA-P statement and is registered on PROSPERO. All methodological tools to be used are endorsed by the Cochrane Prognosis Methods Group. Pre-defined eligibility criteria are provided. Multiple strategies will be used to identify potentially relevant studies. Studies will be selected and data extracted using standardised forms based on the CHARMS checklist. The QUIPS tool will be used to assess the risk of bias within individual studies. Outcome measures will include prevalence, risk ratio, and absolute risk reduction for MACE within 6 weeks of ED evaluation, comparing HEART scores 0–3 versus 4–10. HEART score prognostic performance will be evaluated with the concordance (C) statistic (model discrimination), observed to expected events ratio (model calibration), and a decision curve analysis. Reporting biases and methodological, clinical, and statistical heterogeneity will be scrutinised. Unless deemed inappropriate, a meta-analysis and pre-defined subgroup and sensitivity analyses will be performed. Overall judgements about evidence quality and strength of recommendations will be summarised using the GRADE approach. Discussion This review will identify, select, and appraise studies evaluating the prognostic performance of the HEART score, producing results of interest to emergency physicians. These results may encourage shared clinical decision-making in the ED by facilitating risk communication with patients and health care providers. Systematic review registration PROSPERO 2017 CRD42017084400.

Published
2018
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5. The revised Approved Instructional Resources score: An improved quality evaluation tool for online educational resources

Author

Nadim Lalani, Shelaina Anderson, Jonas Wilmer, Marina Roure, Kristen Weersink, Katherine A. Stuart, Brent Benavides, Wisarut Bunchit, Colleen Sweeney, Robert R. Ehrman, Richard Tang, Kelvin Tran, Gregory Wanner, Drew Kalnow, Christine Roh, Kinjal Patel, Bill Fraser, Therese Mead, Stephen Carroll, Paul Schofield, Caley Flynn, Lindy Buzikievich, Lucy Chen, Tara Stratton, Jan Hansel, Hector C. Singson, Tanner Gronowski, Ali Jamal, Adeeb Saleh, Todd Taylor, Rayan Delbani, Phil Griffith, Michael J. Ward, Miranda Wan, Ashley Kilp, Anna Whalen-Browne, Logan Mills, Ali S. Raja, Perry Menzies, Christine Patterson, Sandra Viggers, Brendan Devine, Vanessa Rogers, Braeden Beaumont, Jennifer Baird, Paula Sneath, Natasha Chatham-Zvelebil, Brandon Herb, Harry Liu, Marie Decock, Sarah Mott, Elise Lovell, Mohammad Ali Jamil, Ken Edwards, Victor Jansen, Maia Dorsett, Jaasmit Khurana, Salim R. Rezaie, Alexander Hart, Fareen Zaver, Manpreet Singh, Ching-Hsing Lee, Suzanne Rannazzisi, Mike McDonnell, Loice Swisher, Rob Carey, Joe Walter, Andrew D. D’Alessandro, Bob Stuntz, James Stempien, Preston Fedor, Kelly Lien, Parisa Shahrabadi, Shauna Regan, Alan Taylor, Nilantha Lenora, Scott Anderson, Calvin H. Yeh, Jason Trickovic, David Calcara, Werner Oberholzer, Catherine Patocka, James Fukakusa, T. Oyedokun, Ivy Liu, Regina Hammock, Steve Liu, Kevin Cullison, Chris Belcher, Teresa Dunphy, Alexis Pelletier-Bui, Zander Laurie, Ashley Lubberdink, James Pearlman, James Huffman, Nikhil Tambe, Carolyn McQuarrie, Gerhard Tiwald, Gregor Prosen, David Lowe, Henry Swoboda, Jennifer Weekes, Kimberly Connors, Aaron Tyagi, Anali Maneshi, Patrick M. Lank, Emina Hajdinjak, Levi Johnston, Eric Chen, Abdulaziz S. Almehlisi, Zach Jarou, Noorin Walji, Alvin Chin, Tanis Quaife, Nikytha Antony, Lawrence Yau, Alexander Zozula, Gregory Costello, Louise Rang, John Mayo, Evan S. Schwarz, Victoria Brazil, P. Mukherj, Taylor Duda, Jaime Jordan, Susan McLellan, Alim Pardhan, Jared Baylis, Allan Mix, Cathy Grossman, Sean Dyer, Emily House, Eric Shappell, Colin Andrews, Mark Woodcroft, William D.T. Kent, Anthony Bryson, Nelson Wong, Pawan Gupta, Diptesh Aryal, Owen Scheirer, Morgan Oakland, Patrick Vallance, Brendan Moore, Mary R C Haas, Kenn Ghaffarian, Steve Montag, Elyse Berger Pelletier, Julianna Deutscher, Nina House, Keith Rosenberg, Sushant Chhabra, Viktor Gawlik, Michael Benham, Andrew Baker, Brent Thoma, Ernest Leber, Larissa Hattin, Casey Lyons, Timothy Chaplin, Kamini Premkumar, Shahbaz Syed, Ivanna Kruhlak, Stephanie Louka, Haakon Lenes, Rene Verbeek, SueLin Hilbert, Joshua Rudner, Julia Nood, Kelly van Diepen, Brian Whiteside, Karthryn T. Eastley, Julia Sheffield, Damjan Gaco, Sam Smith, Quinten S. Paterson, Teresa M. Chan, Jeremy Christensen, Jocelyn Andruko, Youness Elkhalidy, Cory Meeuwisse, Sheena Nandalal, Cara Weessies, Scott Knapp, Sheng Hsiang Ma, Meagan Fu, Veronica Coppersmith, William Denq, Vivian Jia, Kristina Lea, Hugh MacLeod, Simon Huang, Yingchun Lin, Wyatt Warawa, Will Sanderson, Brian Ficiur, Jessica G.Y. Luc, Taylor Nikel, Jessica Yee, Tina Choudhri, Patricia Van den Berg, Andrew Grock, Samantha Lam, Andrew Guy, Keeth Krishnan, Taku Taira, Eric Funk, Rachel Taylor, Ali Mulla, Sebastian Kohler, Kyle Kelson, Nicholas Bouchard, Stanislaw Haciski, Jesse Leontowicz, Paul Trinquero, Charlie Inboriboon, Justin Dueweke, Julian Botta, Emily Brumfield, Kat Butler, Patrick Meloy, Laleh Gharahbaghian, Andrew K. Hall, Maria Rosa Carrillo, Aubrey Powell, Louise Cassidy, Jesse May, Isabelle N. Colmers-Gray, Evelyn Tran, Sarah Batty, Vishal Puri, Randi Ramunno, Luis Vargas, Stephen Miazga, Justin Morgenstern, Michelle Lin, Andrew Griffith, Michael Susalla, Charlotte Alexander, Alex Ireland, Kerstin de Wit, Marcia L. Edmonds, Robert Sobehart, Rob Woods, Kirsty Challen, Dave Slessor, Abby Cosgrove, Eric Chochi, Onyeka Otugo, Amy F. Ho, Alexandra Gustafson, Zlata Vlodaver, Kerry Spearing, Ryan Raffel, Milan L Ridderikhof, Barbra Backus, Saeed Alqahtani, Paul Schunk, Anne Messman, Seth Kelly, Puneet Kapur, Andrew Little, Kathryn Chan, Sean Nugent, Rishi Khakhkhar, Mohammed Alkhalifah, Rachel Wang, Jesse Hill, Marc Phan, Jaroslaw Gucwa, Nick Mancuso, Paxton Ting, Matthew Wagner, Zafrina Poonja, Elisha Targonsky, Britni Sternard, Katherine Yurkiw, Manrique Umana, Jeff Hill, Matthew Willis, and Sherri L. Rudinsky

Subjects
Medical education, education.field_of_study, Intraclass correlation, business.industry, Best practice, Population, MEDLINE, Context (language use), Usability, Original Contribution, Emergency Nursing, Education, Emergency Medicine, Thematic analysis, education, business, Psychology, Quality assurance
Abstract

Background Free Open-Access Medical education (FOAM) use among residents continues to rise. However, it often lacks quality assurance processes and residents receive little guidance on quality assessment. The Academic Life in Emergency Medicine Approved Instructional Resources tool (AAT) was created for FOAM appraisal by and for expert educators and has demonstrated validity in this context. It has yet to be evaluated in other populations. Objectives We assessed the AAT's usability in a diverse population of practicing emergency medicine (EM) physicians, residents, and medical students; solicited feedback; and developed a revised tool. Methods As part of the Medical Education Translational Resources: Impact and Quality (METRIQ) study, we recruited medical students, EM residents, and EM attendings to evaluate five FOAM posts with the AAT and provide quantitative and qualitative feedback via an online survey. Two independent analysts performed a qualitative thematic analysis with discrepancies resolved through discussion and negotiated consensus. This analysis informed development of an initial revised AAT, which was then further refined after pilot testing among the author group. The final tool was reassessed for reliability. Results Of 330 recruited international participants, 309 completed all ratings. The Best Evidence in Emergency Medicine (BEEM) score was the component most frequently reported as difficult to use. Several themes emerged from the qualitative analysis: for ease of use-understandable, logically structured, concise, and aligned with educational value. Limitations include deviation from questionnaire best practices, validity concerns, and challenges assessing evidence-based medicine. Themes supporting its use include evaluative utility and usability. The author group pilot tested the initial revised AAT, revealing a total score average measure intraclass correlation coefficient (ICC) of moderate reliability (ICC = 0.68, 95% confidence interval [CI] = 0 to 0.962). The final AAT's average measure ICC was 0.88 (95% CI = 0.77 to 0.95). Conclusions We developed the final revised AAT from usability feedback. The new score has significantly increased usability, but will need to be reassessed for reliability in a broad population.

Published
2021
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6. The HEART score in predicting major adverse cardiac events in patients presenting to the emergency department with possible acute coronary syndrome: protocol for a systematic review and meta-analysis

Author

Tim Holt, Cristian Toarta, Barbra Backus, and Christopher Byrne

Subjects
Acute coronary syndrome, medicine.medical_specialty, Time Factors, Concordance, Clinical Decision-Making, lcsh:Medicine, Medicine (miscellaneous), 030204 cardiovascular system & hematology, Risk Assessment, HEART score, 03 medical and health sciences, 0302 clinical medicine, Protocol, medicine, Humans, 030212 general & internal medicine, Major adverse cardiac events, Intensive care medicine, Emergency department, business.industry, lcsh:R, Absolute risk reduction, Prognosis, medicine.disease, Study heterogeneity, Meta-analysis, Relative risk, Emergency Service, Hospital, business, Mace
Abstract

Background Acute coronary syndrome (ACS) is a common, sometimes difficult to diagnose spectrum of diseases occurring after abrupt reduction in blood flow through a coronary artery. Given the diagnostic challenge, it is sensible for emergency physicians to have an approach to prognosticate patients with possible ACS. Multiple prediction models have been developed to help identify patients at increased risk of adverse outcomes. The HEART score is the first model to be derived, validated, and undergo clinical impact studies in emergency department (ED) patients with possible ACS. Objective To develop a protocol for a prognostic systematic review of the literature evaluating the HEART score as a predictor of major adverse cardiac events (MACE) in patients presenting to the ED with possible ACS. Methods/design This protocol is reported according to the PRISMA-P statement and is registered on PROSPERO. All methodological tools to be used are endorsed by the Cochrane Prognosis Methods Group. Pre-defined eligibility criteria are provided. Multiple strategies will be used to identify potentially relevant studies. Studies will be selected and data extracted using standardised forms based on the CHARMS checklist. The QUIPS tool will be used to assess the risk of bias within individual studies. Outcome measures will include prevalence, risk ratio, and absolute risk reduction for MACE within 6 weeks of ED evaluation, comparing HEART scores 0–3 versus 4–10. HEART score prognostic performance will be evaluated with the concordance (C) statistic (model discrimination), observed to expected events ratio (model calibration), and a decision curve analysis. Reporting biases and methodological, clinical, and statistical heterogeneity will be scrutinised. Unless deemed inappropriate, a meta-analysis and pre-defined subgroup and sensitivity analyses will be performed. Overall judgements about evidence quality and strength of recommendations will be summarised using the GRADE approach. Discussion This review will identify, select, and appraise studies evaluating the prognostic performance of the HEART score, producing results of interest to emergency physicians. These results may encourage shared clinical decision-making in the ED by facilitating risk communication with patients and health care providers. Systematic review registration PROSPERO 2017 CRD42017084400. Electronic supplementary material The online version of this article (10.1186/s13643-018-0816-4) contains supplementary material, which is available to authorized users.

Published
2018
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7. The Social Media Index as an Indicator of Quality for Emergency Medicine Blogs: A METRIQ Study

Author

Brent Thoma, Teresa M. Chan, Puneet Kapur, Derek Sifford, Marshall Siemens, Michael Paddock, Felix Ankel, Andy Grock, Michelle Lin, Charlotte Alexander, Mohammed Alkhalifah, Abdulaziz S. Almehlisi, Saeed Alqahtani, Scott Anderson, Shelaina Anderson, Colin Andrews, Jocelyn Andruko, Nikytha Antony, Diptesh Aryal, Barbra Backus, Jennifer Baird, Andrew Baker, Sarah Batty, Jared Baylis, Braeden Beaumont, Chris Belcher, Brent Benavides, Michael Benham, Julian Botta, Nicholas Bouchard, Victoria Brazil, Emily Brumfield, Anthony Bryson, Wisarut Bunchit, Kat Butler, Lindy Buzikievich, David Calcara, Rob Carey, Stephen Carroll, Louise Cassidy, Kirsty Challen, Kathryn Chan, Tim Chaplin, Natasha Chatham-Zvelebil, Eric Chen, Lucy Chen, Sushant Chhabra, Alvin Chin, Eric Chochi, Tina Choudhri, Jeremy Christensen, Isabelle Colmers-Gray, Kimberly Connors, Veronica Coppersmith, Abby Cosgrove, Gregory Costello, Kevin Cullison, Andrew D'Alessandro, Kerstin de Wit, Marie Decock, Rayan Delbani, William Denq, Julianna Deutscher, Brendan Devine, Maia Dorsett, Taylor Duda, Justin Dueweke, Teresa Dunphy, Sean Dyer, Karthryn T Eastley, Marcia Edmonds, Ken Edwards, Robert Ehrman, Youness Elkhalidy, Preston Fedor, Brian Ficiur, Caley Flynn, Bill Fraser, Meagan Fu, James Fukakusa, Eric Funk, Damjan Gaco, Viktor Gawlik, Kenn Ghaffarian, Laleh Gharahbaghian, Phil Griffith, Andrew Griffith, Andrew Grock, Tanner Gronowski, Cathy Grossman, Jaroslaw Gucwa, Pawan Gupta, Alexandra Gustafson, Andrew Guy, Mary Haas, Stanislaw Haciski, Emina Hajdinjak, Andrew K. Hall, Regina Hammock, Jan Hansel, Alexander Hart, Larissa Hattin, Brandon Herb, SueLin Hilbert, Jesse Hill, Jeff Hill, Amy Ho, Emily House, Nina House, James Huffman, Charlie Inboriboon, Alex Ireland, Ali Jamal, Mohammad Ali Jamil, Victor Jansen, Zach Jarou, Vivian Jia, Levi Johnston, Drew Kalnow, Seth Kelly, Kyle Kelson, William Kent, Rishi Khakhkhar, Jaasmit Khurana, Ashley Kilp, Scott Knapp, Sebastian Kohler, Ivanna Kruhlak, Nadim Lalani, Samantha Lam, Patrick Lank, Zander Laurie, Kristina Lea, Ernest Leber, Ching-Hsing Lee, Haakon Lenes, Nilantha Lenora, Jesse Leontowicz, Kelly Lien, Yingchun Lin, Andrew Little, Ivy Liu, Harry Liu, Steve Liu, Stephanie Louka, Elise Lovell, David Lowe, Ashley Lubberdink, Jessica Luc, Casey Lyons, Sheng-Hsiang Ma, Hugh MacLeod, Nick Mancuso, Anali Maneshi, Jesse May, John Mayo, Mike McDonnell, Susan McLellan, Carolyn McQuarrie, Julia Nood, Therese Mead, Cory Meeuwisse, Patrick Meloy, Perry Menzies, Anne Messman, Stephen Miazga, Logan Mills, Ken Milne, Allan Mix, Steve Montag, Brendan Moore, Justin Morgenstern, Sarah Mott, P. Mukherj, Ali Mulla, Sheena Nandalal, Taylor Nikel, Sean Nugent, Morgan Oakland, Werner Oberholzer, Onyeka Otugo, Taofiq Segun Oyedokun, Mike Paddock, Alim Pardhan, Kinjal Patel, Quinten Paterson, Catherine Patocka, Christine Patterson, James Pearlman, Elyse Berger Pelletier, Alexis Pelletier-Bui, Marc Phan, Zafrina Poonja, Aubrey Powell, Kamini Premkumar, Gregor Prosen, Vishal Puri, Tanis Quaife, Ryan Raffel, Ali Raja, Randi Ramunno, Louise Rang, Suzanne Rannazzisi, Shauna Regan, Salim R. Rezaie, Milan Ridderikhof, Vanessa Rogers, Christine Roh, Dra. Maria Rosa Carrillo, Keith Rosenberg, Marina Roure, Sherri Rudinsky, Joshua Rudner, Adeeb Saleh, Will Sanderson, Owen Scheirer, Paul Schofield, Paul Schunk, Evan Schwarz, Parisa Shahrabadi, Eric Shappell, Julia Sheffield, Jonathan Sherbino, Manpreet Singh, Hector C Singson, Dave Slessor, Sam Smith, Paula Sneath, Robert Sobehart, Kerry Spearing, James Stempien, Britni Sternard, Tara Stratton, Katherine Stuart, Bob Stuntz, Michael Susalla, Colleen Sweeney, Loice Swisher, Henry Swoboda, Shahbaz Syed, Taku Taira, Nikhil Tambe, Richard Tang, Elisha Targonsky, Rachel Taylor, Alan Taylor, Todd Taylor, Paxton Ting, Gerhard Tiwald, Kelvin Tran, Evelyn Tran, Jason Trickovic, Paul Trinquero, Seth Trueger, Aaron Tyagi, Manrique Umana, Patrick Vallance, Patricia Van den Berg, Luis Vargas, Rene Verbeek, Sandra Viggers, Zlata Vlodaver, Matthew Wagner, Noorin Walji, Joe Walter, Miranda Wan, Rachel Wang, Gregory Wanner, Wyatt Warawa, Mike Ward, Jennifer Weekes, Kristen Weersink, Cara Weessies, Anna Whalen-Browne, Brian Whiteside, Matthew Willis, Jonas Wilmer, Nelson Wong, Mark Woodcroft, Rob Woods, Lawrence Yau, Jessica Yee, Calvin Yeh, Simon York Ming Huang, Katherine Yurkiw, Fareen Zaver, Alexander Zozula, Emergency Department, Graduate School, ACS - Heart failure & arrhythmias, and ACS - Diabetes & metabolism

Subjects
Adult, Male, medicine.medical_specialty, Index (economics), Blogging, Cross-sectional study, media_common.quotation_subject, education, MEDLINE, 03 medical and health sciences, 0302 clinical medicine, Medicine, Humans, Social media, Quality (business), 030212 general & internal medicine, media_common, Web site, business.industry, 030208 emergency & critical care medicine, Critical appraisal, Cross-Sectional Studies, Emergency medicine, Emergency Medicine, Gestalt psychology, Female, business, Social Media
Abstract

Study objective Online educational resources such as blogs are increasingly used for education by emergency medicine clinicians. The Social Media Index was developed to quantify their relative impact. The Medical Education Translational Resources: Indicators of Quality (METRIQ) study was conducted in part to determine the association between the Social Media Index score and quality as measured by gestalt and previously derived quality instruments. Methods Ten blogs were randomly selected from a list of emergency medicine and critical care Web sites. The 2 most recent clinically oriented blog posts published on these blogs were evaluated with gestalt, the Academic Life in Emergency Medicine Approved Instructional Resources (ALiEM AIR) score, and the METRIQ-8 score. Volunteer raters (including medical students, emergency medicine residents, and emergency medicine attending physicians) were identified with a multimodal recruitment methodology. The Social Media Index was calculated in February 2016, November 2016, April 2017, and December 2017. Pearson's correlations were calculated between the Social Media Index and the average rater gestalt, ALiEM AIR score, and METRIQ-8 score. Results A total of 309 of 330 raters completed all ratings (93.6%). The Social Media Index correlated moderately to strongly with the mean rater gestalt ratings (range 0.69 to 0.76) and moderately with the mean rater ALiEM AIR score (range 0.55 to 0.61) and METRIQ-8 score (range 0.53 to 0.57) during the month of the blog post's selection and for 2 years after. Conclusion The Social Media Index's correlation with multiple quality evaluation instruments over time supports the hypothesis that it is associated with overall Web site quality. It can play a role in guiding individuals to high-quality resources that can be reviewed with critical appraisal techniques.

Published
2018

8. Individual Gestalt Is Unreliable for the Evaluation of Quality in Medical Education Blogs: A METRIQ Study

Author

Brent Thoma, Stefanie S. Sebok-Syer, Keeth Krishnan, Marshall Siemens, N. Seth Trueger, Isabelle Colmers-Gray, Rob Woods, Emil Petrusa, Teresa Chan, Charlotte Alexander, Mohammed Alkhalifah, Saeed Alqahtani, Scott Anderson, Shelaina Anderson, Colin Andrews, Jocelyn Andruko, Felix Ankel, Nikytha Antony, Diptesh Aryal, Barbra Backus, Jennifer Baird, Andrew Baker, Sarah Batty, Jared Baylis, Braeden Beaumont, Chris Belcher, Brent Benavides, Michael Benham, Elyse Berger Pelletier, Julian Botta, Nicholas Bouchard, Victoria Brazil, Emily Brumfield, Anthony Bryson, Wisarut Bunchit, Kat Butler, Lindy Buzikievich, David Calcara, Rob Carey, Stephen Carroll, Casey Lyons, Louise Cassidy, Kirsty Challen, Tim Chaplin, Natasha Chatham-Zvelebil, Eric Chen, Lucy Chen, Sushant Chhabra, Alvin Chin, Eric Chochi, Tina Choudhri, Jeremy Christensen, Kimberly Connors, Veronica Coppersmith, Abby Cosgrove, Gregory Costello, Kevin Cullison, Andrew D'Alessandro, Kerstin de Wit, Marie Decock, Rayan Delbani, William Denq, Julianna Deutscher, Brendan Devine, Maia Dorsett, Taylor Duda, Justin Dueweke, Teresa Dunphy, Sean Dyer, Kathryn T. Eastley, Marcia Edmonds, Ken Edwards, Robert Ehrman, Youness Elkhalidy, Preston Fedor, Brian Ficiur, Caley Flynn, Bill Fraser, Meagan Fu, James Fukakusa, Eric Funk, Damjan Gaco, Viktor Gawlik, Kenn Ghaffarian, Laleh Gharahbaghian, Phil Griffith, Andrew Griffith, Andrew Grock, Tanner Gronowski, Cathy Grossman, Jaroslaw Gucwa, Pawan Gupta, Alexandra Gustafson, Andrew Guy, Mary Haas, Stanislaw Haciski, Emina Hajdinjak, Andrew K. Hall, Regina Hammock, Jan Hansel, Alexander Hart, Larissa Hattin, Brandon Herb, SueLin Hilbert, Jesse Hill, Jeff Hill, Amy Ho, Emily House, Nina House, James Huffman, Charlie Inboriboon, Alex Ireland, Mohammed Ali Jamal, Victor Jansen, Zach Jarou, Vivian Jia, Levi Johnston, Drew Kalnow, Puneet Kapur, Seth Kelly, Kyle Kelson, William Kent, Rishi Khakhkhar, Jaasmit Khurana, Ashley Kilp, Scott Knapp, Sebastian Kohler, Ivanna Kruhlak, Nadim Lalani, Samantha Lam, Patrick Lank, Zander Laurie, Kristina Lea, Ernest Leber, Ching-Hsing Lee, Haakon Lenes, Nilantha Lenora, Jesse Leontowicz, Kelly Lien, Yingchun Lin, Michelle Lin, Andrew Little, Ivy Liu, Harry Liu, Steve Liu, Stephanie Louka, Elise Lovell, David Lowe, Ashley Lubberdink, Jessica Luc, Sheng-Hsiang Ma, Hugh MacLeod, Nick Mancuso, Anali Maneshi, Dra. Maria Rosa Carrillo, Jesse May, John Mayo, Mike McDonnell, Susan McLellan, Carolyn McQuarrie, Julia Nood, Therese Mead, Cory Meeuwisse, Patrick Meloy, Perry Menzies, Anne Messman, Stephen Miazga, Logan Mills, Ken Milne, Allan Mix, Steve Montag, Brendon Moore, Justin Morgenstern, Sarah Mott, P. Mukherj, Ali Mulla, Sheena Nandalal, Taylor Nikel, Sean Nugent, Morgan Oakland, Werner Oberholzer, Onyeka Otugo, Taofiq Segun Oyedokun, Mike Paddock, Alim Pardhan, Kinjal Patel, Quinten Paterson, Catherine Patocka, Christine Patterson, James Pearlman, Alexis Pelletier-Bui, Marc Phan, Zafrina Poonja, Aubrey Powell, Kamini Premkumar, Gregor Prosen, Vishal Puri, Tanis Quaife, Ryan Raffel, Ali Raja, Randi Ramunno, Louise Rang, Suzanne Rannazzisi, Shauna Regan, Milan Ridderikhof, Vanessa Rogers, Christine Roh, Keith Rosenberg, Marina Roure, Sherri Rudinsky, Joshua Rudner, Adeeb Saleh, Will Sanderson, Owen Scheirer, Paul Schofield, Paul Schunk, Evan Schwarz, Parisa Shahrabadi, Eric Shappell, Julia Sheffield, Jonathan Sherbino, Manpreet Singh, Hector C. Singson, Dave Slessor, Sam Smith, Paula Sneath, Robert Sobehart, Kerry Spearing, James Stempien, Britni Sternard, Tara Stratton, Katherine Stuart, Bob Stuntz, Michael Susalla, Colleen Sweeney, Loice Swisher, Henry Swoboda, Shahbaz Syed, Taku Taira, Nikhil Tambe, Richard Tang, Elisha Targonsky, Rachel Taylor, Alan Taylor, Todd Taylor, Paxton Ting, Gerhard Tiwald, Kelvin Tran, Evelyn Tran, Jason Trickovic, Paul Trinquero, Seth Trueger, Aaron Tyagi, Manrique Umana, Patrick Vallance, Patricia Van den Berg, Luis Vargas, Rene Verbeek, Sandra Viggers, Zlata Vlodaver, Matthew Wagner, Noorin Walji, Joe Walter, Miranda Wan, Rachel Wang, Gregory Wanner, Wyatt Warawa, Mike Ward, Jennifer Weekes, Kristen Weersink, Cara Weessies, Anna Whalen-Browne, Brian Whiteside, Matthew Willis, Jonas Wilmer, Nelson Wong, Mark Woodcroft, Lawrence Yau, Jessica Yee, Calvin Yeh, Simon York Ming Huang, Katherine Yurkiw, Fareen Zaver, Alexander Zozula, Graduate School, Emergency Department, ACS - Heart failure & arrhythmias, and ACS - Diabetes & metabolism

Subjects
Adult, Male, Students, Medical, Blogging, Intraclass correlation, media_common.quotation_subject, education, MEDLINE, Likert scale, 03 medical and health sciences, 0302 clinical medicine, Evaluation methods, Medicine, Humans, Quality (business), Generalizability theory, 030212 general & internal medicine, Reliability (statistics), media_common, Medical education, Education, Medical, business.industry, Internship and Residency, Reproducibility of Results, 030208 emergency & critical care medicine, Gestalt Theory, Emergency Medicine, Gestalt psychology, Female, Clinical Competence, Educational Measurement, business, Social Media
Abstract

Study objective Open educational resources such as blogs are increasingly used for medical education. Gestalt is generally the evaluation method used for these resources; however, little information has been published on it. We aim to evaluate the reliability of gestalt in the assessment of emergency medicine blogs. Methods We identified 60 English-language emergency medicine Web sites that posted clinically oriented blogs between January 1, 2016, and February 24, 2016. Ten Web sites were selected with a random-number generator. Medical students, emergency medicine residents, and emergency medicine attending physicians evaluated the 2 most recent clinical blog posts from each site for quality, using a 7-point Likert scale. The mean gestalt scores of each blog post were compared between groups with Pearson's correlations. Single and average measure intraclass correlation coefficients were calculated within groups. A generalizability study evaluated variance within gestalt and a decision study calculated the number of raters required to reliably (>0.8) estimate quality. Results One hundred twenty-one medical students, 88 residents, and 100 attending physicians (93.6% of enrolled participants) evaluated all 20 blog posts. Single-measure intraclass correlation coefficients within groups were fair to poor (0.36 to 0.40). Average-measure intraclass correlation coefficients were more reliable (0.811 to 0.840). Mean gestalt ratings by attending physicians correlated strongly with those by medical students (r=0.92) and residents (r=0.99). The generalizability coefficient was 0.91 for the complete data set. The decision study found that 42 gestalt ratings were required to reliably evaluate quality (>0.8). Conclusion The mean gestalt quality ratings of blog posts between medical students, residents, and attending physicians correlate strongly, but individual ratings are unreliable. With sufficient raters, mean gestalt ratings provide a community standard for assessment.

Published
2016

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