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Background: "Wrong surgery" is defined as wrong site, wrong operation, or wrong patient, with estimated incidence up to 1 per 5,000 cases. Responding to national attention on wrong surgery, our objective was to create a care redesign intervention to minimize the rate of wrong surgery.Methods: The authors created an electronic system using existing intraoperative electronic documentation to present a time-out checklist on large in-room displays. Time-out was dynamically interposed as a forced-function documentation step between "patient-in-operating room" and "incision." Time to complete documentation was obtained from audit logs. The authors measured the postimplementation wrong surgery rate and used Bayesian methods to compare the pre- and postimplementation rates at our institution. Previous probabilities were selected using wrong surgery rate estimates from the observed performance reported in the literature to generate previous probabilities (4.24 wrong surgeries per 100,000 cases).Results: No documentation times exceeded 5 min; 97% of documentation tasks were completed within 2 min. The authors performed 243,939 operations over 5 yr using the system, with zero wrong surgeries, compared with 253,838 operations over 6 yr with two wrong surgeries before implementation. Bayesian analysis suggests an 84% probability that the postimplementation wrong rate is lower than baseline. However, given the rarity of wrong surgery in our sample, there is substantial uncertainty. The total system-development cost was $34,000, roughly half the published cost of one weighted median settlement for wrong surgery.Conclusion: Implementation of a forced-completion electronically mediated time-out process before incision is feasible, but it is unclear whether true performance improvements occur. [ABSTRACT FROM AUTHOR]

Background: Assessment of clinical competence is essential for residency programs and should be guided by valid, reliable measurements. We implemented Baker's Z-score system, which produces measures of traditional core competency assessments and clinical performance summative scores. Our goal was to validate use of summative scores and estimate the number of evaluations needed for reliable measures.Methods: We performed generalizability studies to estimate the variance components of raw and Z-transformed absolute and peer-relative scores and decision studies to estimate the evaluations needed to produce at least 90% reliable measures for classification and for high-stakes decisions. A subset of evaluations was selected representing residents who were evaluated frequently by faculty who provided the majority of evaluations. Variance components were estimated using ANOVA.Results: Principal component extraction from 8,754 complete evaluations demonstrated that a single factor explained 91 and 85% of variance for absolute and peer-relative scores, respectively. In total, 1,200 evaluations were selected for generalizability and decision studies. The major variance component for all scores was resident interaction with measurement occasions. Variance due to the resident component was strongest with raw scores, where 30 evaluation occasions produced 90% reliable measurements with absolute scores and 58 for peer-relative scores. For Z-transformed scores, 57 evaluation occasions produced 90% reliable measurements with absolute scores and 55 for peer-relative scores. The results were similar for high-stakes decisions.Conclusions: The Baker system produced moderately reliable measures at our institution, suggesting that it may be generalizable to other training programs. Raw absolute scores required few assessment occasions to achieve 90% reliable measurements. [ABSTRACT FROM AUTHOR]

Extensive evidence demonstrates that medical record modernization and a vast amount of available data have not overcome the gap between recommended and delivered care. This study aimed to evaluate the use of clinical decision support (CDS) in conjunction with feedback (post-hoc reporting) to improve PONV medication administration compliance and postoperative nausea and vomiting (PONV) outcomes. Single center, prospective observational study between January 1, 2015, and June 30, 2017. Perioperative care at a university-affiliated tertiary care center. 57,401 adult patients who received general anesthesia in a non-emergency setting. A multi-phased intervention that consisted of post-hoc reporting for individual providers by email about PONV occurrences in their patients, followed by directive CDS through preoperative daily case emails that provided therapeutic PONV prophylaxis recommendations based on patients' PONV risk scores. Compliance with PONV medication recommendations, as well as hospital rates of PONV were measured. Over the study period, there was a 5.5% (95% CI, 4.2% to 6.4%; p < 0.001) improvement in the compliance of PONV medication administration along with an 8.7% (95% CI, 7.1% to 10.2%, p < 0.001) reduction in PONV rescue medication administration in the PACU. However, there was no statistically or clinically significant reduction in the prevalence of PONV in the PACU. The prevalence of PONV rescue medication administration decreased during the Intervention Rollout Period (odds ratio 0.95 [per month]; 95% CI, 0.91 to 0.99; p = 0.017), and during the Feedback with CDS Recommendation Period (odds ratio, 0.96 [per month]; 95% CI, 0.94 to 0.99; p = 0.013). PONV medication administration compliance modestly improves with CDS in conjunction with post-hoc reporting; however, no improvement in PACU rates of PONV occurred. • Audit and feedback, combined with a clinical decision support tool, modestly improves compliance with PONV recommendations. • Audit and feedback, combined with a clinical decision support tool, did not reduce the prevalence of PONV in the PACU. • Audit and feedback, alone, do not improve compliance with PONV prophylaxis recommendations. • Compliance with PONV recommendations improved by 5.5%; there was an 8.7% reduction in rescue medication use in the PACU. [ABSTRACT FROM AUTHOR]

Background: Diabetic patients receiving insulin should have periodic intraoperative glucose measurement. The authors conducted a care redesign effort to improve intraoperative glucose monitoring.Methods: With approval from Vanderbilt University Human Research Protection Program (Nashville, Tennessee), the authors created an automatic system to identify diabetic patients, detect insulin administration, check for recent glucose measurement, and remind clinicians to check intraoperative glucose. Interrupted time series and propensity score matching were used to quantify pre- and postintervention impact on outcomes. Chi-square/likelihood ratio tests were used to compare surgical site infections at patient follow-up.Results: The authors analyzed 15,895 cases (3,994 preintervention and 11,901 postintervention; similar patient characteristics between groups). Intraoperative glucose monitoring rose from 61.6 to 87.3% in cases after intervention (P = 0.0001). Recovery room entry hyperglycemia (fraction of initial postoperative glucose readings greater than 250) fell from 11.0 to 7.2% after intervention (P = 0.0019), while hypoglycemia (fraction of initial postoperative glucose readings less than 75) was unchanged (0.6 vs. 0.9%; P = 0.2155). Eighty-seven percent of patients had follow-up care. After intervention the unadjusted surgical site infection rate fell from 1.5 to 1.0% (P = 0.0061), a 55.4% relative risk reduction. Interrupted time series analysis confirmed a statistically significant surgical site infection rate reduction (P = 0.01). Propensity score matching to adjust for confounders generated a cohort of 7,604 well-matched patients and confirmed a statistically significant surgical site infection rate reduction (P = 0.02).Conclusions: Anesthesiologists add healthcare value by improving perioperative systems. The authors leveraged the one-time cost of programming to improve reliability of intraoperative glucose management and observed improved glucose monitoring, increased insulin administration, reduced recovery room hyperglycemia, and fewer surgical site infections. Their analysis is limited by its applied quasiexperimental design. [ABSTRACT FROM AUTHOR]