Objective: Health care quality improvement (QI) efforts commonly use self-assessment to measure compliance with quality standards. This study investigates the validity of self-assessment of quality indicators.
Design: Cross sectional.
Setting: A maternal and newborn care improvement collaborative intervention conducted in health facilities in Ecuador in 2005.
Participants: Four external evaluators were trained in abstracting medical records to calculate six indicators reflecting compliance with treatment standards.
Interventions: About 30 medical records per month were examined at 12 participating health facilities for a total of 1875 records. The same records had already been reviewed by QI teams at these facilities (self-assessment).
Main Outcome Measures: Overall compliance, agreement (using the Kappa statistic), sensitivity and specificity were analyzed. We also examined patterns of disagreement and the effect of facility characteristics on levels of agreement.
Results: External evaluators reported compliance of 69-90%, while self-assessors reported 71-92%, with raw agreement of 71-95% and Kappa statistics ranging from fair to almost perfect agreement. Considering external evaluators as the gold standard, sensitivity of self-assessment ranged from 90 to 99% and specificity from 48 to 86%. Simpler indicators had fewer disagreements. When disagreements occurred between self-assessment and external valuators, the former tended to report more positive findings in five of six indicators, but this tendency was not of a magnitude to change program actions. Team leadership, understanding of the tools and facility size had no overall impact on the level of agreement.
Conclusions: When compared with external evaluation (gold standard), self-assessment was found to be sufficiently valid for tracking QI team performance. Sensitivity was generally higher than specificity. Simplifying indicators may improve validity.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1093/intqhc/mzr057 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!