OBJECTIVE: To test the hypothesis that surgical services combining relatively high levels of feedback and programming approaches to the coordination of surgical staff would have better quality of care than surgical services using low levels of both coordination approaches as well as those surgical service using low levels of either coordination approach. STUDY SETTING: A study sample of 44 academically affiliated surgical services that are part of the Department of Veterans Affairs. STUDY DESIGN: In a cross-sectional analysis, surgical services were assigned to one of three groups based on their scores on feedback and programming coordination measures: high on both measures; high on one measure, low on the other; and low on both. Univariate and multivariate analyses were used to assess differences among these groups with respect to three quality indicators: risk-adjusted mortality, risk-adjusted morbidity, and staff perceptions of quality. DATA COLLECTION/EXTRACTION METHODS: Risk-adjusted mortality and morbidity came from an outcomes reporting program within the Department of Veterans Affairs that entails the prospective collection of clinical data from patient charts. Data on coordination practices and perceived quality came from a survey of surgical staff at each of the 44 participating surgical services. PRINCIPAL FINDINGS: The group of surgical services using high feedback and high programming had the best perceived quality. This group also had the lowest morbidity, but the difference was statistically significant with respect to only one of the two other groups: the group with low feedback and low programming. No significant group differences were found for mortality. CONCLUSIONS: Study results provide partial support for the hypothesis that high levels of feedback and programming should be combined for optimal quality of care. Study results also suggest that staff coordination is more important for improving morbidity than mortality in surgical services.
OBJECTIVE: To test the hypothesis that surgical services combining relatively high levels of feedback and programming approaches to the coordination of surgical staff would have better quality of care than surgical services using low levels of both coordination approaches as well as those surgical service using low levels of either coordination approach. STUDY SETTING: A study sample of 44 academically affiliated surgical services that are part of the Department of Veterans Affairs. STUDY DESIGN: In a cross-sectional analysis, surgical services were assigned to one of three groups based on their scores on feedback and programming coordination measures: high on both measures; high on one measure, low on the other; and low on both. Univariate and multivariate analyses were used to assess differences among these groups with respect to three quality indicators: risk-adjusted mortality, risk-adjusted morbidity, and staff perceptions of quality. DATA COLLECTION/EXTRACTION METHODS: Risk-adjusted mortality and morbidity came from an outcomes reporting program within the Department of Veterans Affairs that entails the prospective collection of clinical data from patient charts. Data on coordination practices and perceived quality came from a survey of surgical staff at each of the 44 participating surgical services. PRINCIPAL FINDINGS: The group of surgical services using high feedback and high programming had the best perceived quality. This group also had the lowest morbidity, but the difference was statistically significant with respect to only one of the two other groups: the group with low feedback and low programming. No significant group differences were found for mortality. CONCLUSIONS: Study results provide partial support for the hypothesis that high levels of feedback and programming should be combined for optimal quality of care. Study results also suggest that staff coordination is more important for improving morbidity than mortality in surgical services.
Authors: A J Hartz; H Krakauer; E M Kuhn; M Young; S J Jacobsen; G Gay; L Muenz; M Katzoff; R C Bailey; A A Rimm Journal: N Engl J Med Date: 1989-12-21 Impact factor: 91.245
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Authors: Kathryn M McDonald; Sara J Singer; Sherri Sheinfeld Gorin; David A Haggstrom; Denise M Hynes; Martin P Charns; Elizabeth M Yano; Michelle A Lucatorto; Donna M Zulman; Michael K Ong; R Neal Axon; Donna Vogel; Mark Upton Journal: J Gen Intern Med Date: 2019-05 Impact factor: 5.128