OBJECTIVE: We sought to develop a method to adjust for case mix diversity and allow comparison of adverse outcome rates among practitioners in pediatric and congenital cardiac catheterization. PATIENTS AND METHODS: A single institutional database that captured demographic and procedural data was used to identify patient and procedural characteristics associated with adverse events (AE) and any high severity event classified as preventable or possibly preventable (P/PP). Diagnostic and procedural risk groups were created and indicators of hemodynamic vulnerability were defined. Expected event rates by the practitioners adjusting for case mix were calculated. Standardized adverse event ratios (SAER), defined as the observed rate divided by the expected rate for each practitioner were calculated with 95% confidence intervals. RESULTS: The database included 1727 hemodynamic (30%) and interventional (70%) cases performed by seven practitioners in 18 months. During 147 cases, at least one P/PP AE occurred; among the seven practitioners observed, event rates ranged from 3.2 to 14.2%. In multivariable analysis, risk factors for all P/PP events included highest procedure risk group (odds ratio [OR] 2.1 for group 2, and 2.8 for group 3, relative to group 1, P = .001 and P < .001, respectively) and weight less than 4 kg (OR 2.8, P < .001). High severity P/PP events occurred in 67 cases with rates ranging from 2.0 to 6.6% by the practitioners. For these events, risk factors included: highest procedure risk group (OR 4.5 for group 2, and 4.9 for group 3, both P < .001) and an indicator of hemodynamic vulnerability (OR 1.8, P = .026). For the seven practitioners, the SAER ranged from 0.41 to 1.32 for any P/PP AE and from 0.69 to 1.44 for P/PP high severity events. In this cohort, we did not identify any statistically significant performance differences. CONCLUSION: Despite wide variations in case mix complexity in pediatric and congenital cardiac catheterization, this study demonstrates a method for risk adjustment which allows equitable comparisons among practitioners at a single institution.
OBJECTIVE: We sought to develop a method to adjust for case mix diversity and allow comparison of adverse outcome rates among practitioners in pediatric and congenital cardiac catheterization. PATIENTS AND METHODS: A single institutional database that captured demographic and procedural data was used to identify patient and procedural characteristics associated with adverse events (AE) and any high severity event classified as preventable or possibly preventable (P/PP). Diagnostic and procedural risk groups were created and indicators of hemodynamic vulnerability were defined. Expected event rates by the practitioners adjusting for case mix were calculated. Standardized adverse event ratios (SAER), defined as the observed rate divided by the expected rate for each practitioner were calculated with 95% confidence intervals. RESULTS: The database included 1727 hemodynamic (30%) and interventional (70%) cases performed by seven practitioners in 18 months. During 147 cases, at least one P/PP AE occurred; among the seven practitioners observed, event rates ranged from 3.2 to 14.2%. In multivariable analysis, risk factors for all P/PP events included highest procedure risk group (odds ratio [OR] 2.1 for group 2, and 2.8 for group 3, relative to group 1, P = .001 and P < .001, respectively) and weight less than 4 kg (OR 2.8, P < .001). High severity P/PP events occurred in 67 cases with rates ranging from 2.0 to 6.6% by the practitioners. For these events, risk factors included: highest procedure risk group (OR 4.5 for group 2, and 4.9 for group 3, both P < .001) and an indicator of hemodynamic vulnerability (OR 1.8, P = .026). For the seven practitioners, the SAER ranged from 0.41 to 1.32 for any P/PP AE and from 0.69 to 1.44 for P/PP high severity events. In this cohort, we did not identify any statistically significant performance differences. CONCLUSION: Despite wide variations in case mix complexity in pediatric and congenital cardiac catheterization, this study demonstrates a method for risk adjustment which allows equitable comparisons among practitioners at a single institution.
Authors: Natalie Jayaram; Robert H Beekman; Lee Benson; Ralf Holzer; Kathy Jenkins; Kevin F Kennedy; Gerard R Martin; John W Moore; Richard Ringel; Jonathan Rome; John A Spertus; Robert Vincent; Lisa Bergersen Journal: Circulation Date: 2015-10-19 Impact factor: 29.690
Authors: Michael L O'Byrne; Andrew C Glatz; Russell T Shinohara; Natalie Jayaram; Matthew J Gillespie; Yoav Dori; Jonathan J Rome; Steven Kawut Journal: Am Heart J Date: 2015-03-03 Impact factor: 4.749
Authors: Michael L O'Byrne; Andrew C Glatz; Brian D Hanna; Russell T Shinohara; Matthew J Gillespie; Yoav Dori; Jonathan J Rome; Steven M Kawut Journal: J Am Coll Cardiol Date: 2015-09-15 Impact factor: 24.094
Authors: Natalie Jayaram; John A Spertus; Kevin F Kennedy; Robert Vincent; Gerard R Martin; Jeptha P Curtis; David Nykanen; Phillip M Moore; Lisa Bergersen Journal: Circulation Date: 2017-09-07 Impact factor: 29.690
Authors: C Huie Lin; Sanjeet Hegde; Audrey C Marshall; Diego Porras; Kimberlee Gauvreau; David T Balzer; Robert H Beekman; Alejandro Torres; Julie A Vincent; John W Moore; Ralf Holzer; Laurie Armsby; Lisa Bergersen Journal: Pediatr Cardiol Date: 2013-07-31 Impact factor: 1.655
Authors: Michael L O'Byrne; Kevin F Kennedy; Natalie Jayaram; Lisa J Bergersen; Matthew J Gillespie; Yoav Dori; Jeffrey H Silber; Steven M Kawut; Jonathan J Rome; Andrew C Glatz Journal: J Am Heart Assoc Date: 2019-10-17 Impact factor: 5.501