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Viren Kaul, MD

Blogger:
Viren Kaul, MD
Twitter handle @virenkaul

About the blogger: 
Viren Kaul is a Pulmonary & Critical Care Medicine Fellow at Mount Sinai School of Medicine / Elmhurst Hospital Center. His research interests include medical education, sepsis and palliative care in the critically ill. His focus in medical education is on simulation based performance improvement and inter-professional education.

Citation: 
Silkens, Milou EWM, et al. "From good to excellent: Improving clinical departments’ learning climate in residency training." Medical teacher (2017): 1-7.

Link:  https://bit.ly/2HdXsgo

Article:  From good to excellent: Improving clinical departments’ learning climate in residency training.

Summary: 
The authors used the Dutch Residency Education Climate Test (D-RECT), one of the most researched evaluation tools to assess strength and weaknesses of 211 training programs’ learning climate to identify learning climate groups across various residency training departments. They acquired data on individual teaching qualities of the faculty using the Systems for Evaluating Teaching Performance (SETQ). Using latent profile analysis of responses from 1730 residents they classified the programs into four groups according to their learning climate: substandard (19% of programs), adequate (43%), good (33%) and excellent performers (5%). The teaching status of the program (academic vs clinical), departmental SETQ score and percentage of time spent on educational activities by faculty were significant predictors of the total mean score on D-RECT.

Why this article:
The learning climate of a training program is a complicated construct. The authors were able to distinctly place training programs into 4 groups, thereby allowing analysis of what was being done well at high performing centers from a resident’s perspective. Departments scoring high on one domain on the D-RECT were likely to score highly in all domains, however, latent profile analysis including the whole range of D-RECT scores in determining the underlying structure of the data. Some domains of the score were found to be of higher value in determining learning culture, such as resident peer collaboration and accessibility of supervisors. The authors accordingly offer advice. They recommend a continuous improvement model of learning climates as opposed to quality assurance, including learning climate performance indicators during program accreditation reviews and striking a balance between optimal learning versus climates that allow for safe patient care.