Validity evidence for Quality Improvement Knowledge Application Tool Revised (QIKAT-R) scores: consequences of rater number and type using neurology cases

• Published in: BMJ quality & safety Vol. 28; no. 11; pp. 925 - 933
• Main Authors: Kassardjian, Charles, Park, Yoon Soo, Braksick, Sherri, Cutsforth-Gregory, Jeremy, Robertson, Carrie, Young, Nathan, Leep Hunderfund, Andrea
• Format: Journal Article
• Language: English
• Published: England BMJ Publishing Group LTD 01.11.2019
• Subjects: Accreditation; Health administration; Knowledge; Licensing examinations; Medical education; Neurology; Quality; Quality control; Quality improvement; Validity; New York; United States > US; Minnesota; graduate medical education; medical education; quality improvement
• ISSN: 2044-5415; 2044-5423
• DOI: 10.1136/bmjqs-2018-008689

ObjectivesTo develop neurology scenarios for use with the Quality Improvement Knowledge Application Tool Revised (QIKAT-R), gather and evaluate validity evidence, and project the impact of scenario number, rater number and rater type on score reliability.MethodsSix neurological case scenarios were developed. Residents were randomly assigned three scenarios before and after a quality improvement (QI) course in 2015 and 2016. For each scenario, residents crafted an aim statement, selected a measure and proposed a change to address a quality gap. Responses were scored by six faculty raters (two with and four without QI expertise) using the QIKAT-R. Validity evidence from content, response process, internal structure, relations to other variables and consequences was collected. A generalisability (G) study examined sources of score variability, and decision analyses estimated projected reliability for different numbers of raters and scenarios and raters with and without QI expertise.ResultsRaters scored 163 responses from 28 residents. The mean QIKAT-R score was 5.69 (SD 1.06). G-coefficient and Phi-coefficient were 0.65 and 0.60, respectively. Interrater reliability was fair for raters without QI expertise (intraclass correlation = 0.53, 95% CI 0.30 to 0.72) and acceptable for raters with QI expertise (intraclass correlation = 0.66, 95% CI 0.02 to 0.88). Postcourse scores were significantly higher than precourse scores (6.05, SD 1.48 vs 5.22, SD 1.5; p < 0.001). Sufficient reliability for formative assessment (G-coefficient > 0.60) could be achieved by three raters scoring six scenarios or two raters scoring eight scenarios, regardless of rater QI expertise.ConclusionsValidity evidence was sufficient to support the use of the QIKAT-R with multiple scenarios and raters to assess resident QI knowledge application for formative or low-stakes summative purposes. The results provide practical information for educators to guide implementation decisions.