Evaluating the Impact of Operative Team Familiarity on Cardiac Surgery Outcomes: A Retrospective Cohort Study of Medicare Beneficiaries.

OBJECTIVE: To associate surgeon-anesthesiologist team familiarity (TF) with cardiac surgery outcomes. BACKGROUND: TF, a measure of repeated team member collaborations, has been associated with improved operative efficiency; however, examination of its relationship to clinical outcomes has been limited. METHODS: This retrospective cohort study included Medicare beneficiaries undergoing coronary artery bypass grafting (CABG), surgical aortic valve replacement (SAVR), or both (CABG+SAVR) between January 1, 2017, and September 30, 2018. TF was defined as the number of shared procedures between the cardiac surgeon and anesthesiologist within 6 months of each operation. Primary outcomes were 30- and 90-day mortality, composite morbidity, and 30-day mortality or composite morbidity, assessed before and after risk adjustment using multivariable logistic regression. RESULTS: The cohort included 113,020 patients (84,397 CABG; 15,939 SAVR; 12,684 CABG+SAVR). Surgeon-anesthesiologist dyads in the highest [31631 patients, TF median (interquartile range)=8 (6, 11)] and lowest [44,307 patients, TF=0 (0, 1)] TF terciles were termed familiar and unfamiliar, respectively. The rates of observed outcomes were lower among familiar versus unfamiliar teams: 30-day mortality (2.8% vs 3.1%, P =0.001), 90-day mortality (4.2% vs 4.5%, P =0.023), composite morbidity (57.4% vs 60.6%, P <0.001), and 30-day mortality or composite morbidity (57.9% vs 61.1%, P <0.001). Familiar teams had lower overall risk-adjusted odds of 30-day mortality or composite morbidity [adjusted odds ratio (aOR) 0.894 (0.868, 0.922), P <0.001], and for SAVR significantly lower 30-day mortality [aOR 0.724 (0.547, 0.959), P =0.024], 90-day mortality [aOR 0.779 (0.620, 0.978), P =0.031], and 30-day mortality or composite morbidity [aOR 0.856 (0.791, 0.927), P <0.001]. CONCLUSIONS: Given its relationship with improved 30-day cardiac surgical outcomes, increasing TF should be considered among strategies to advance patient outcomes.

Predictors of Discharge Home Without Opioids After Cardiac Surgery: A Multicenter Analysis.

BACKGROUND: Whether all patients will require an opioid prescription after cardiac surgery is unknown. We performed a multicenter analysis to identify patient predictors of not receiving an opioid prescription at the time of discharge home after cardiac surgery. METHODS: Opioid-naïve patients undergoing coronary artery bypass grafting and/or valve surgery through a sternotomy at 10 centers from January to December 2019 were identified retrospectively from a prospectively maintained data set. Opioid-naïve was defined as not taking opioids at the time of admission. The primary outcome was discharge without an opioid prescription. Mixed-effects logistic regression was performed to identify predictors of discharge without an opioid prescription, and postdischarge opioid prescribing was monitored to assess patient tolerance of discharge without an opioid prescription. RESULTS: Among 1924 eligible opioid-naïve patients, mean age was 64 ± 11 years, and 25% were women. In total, 28% of all patients were discharged without an opioid prescription. On multivariable analysis, older age, longer length of hospital stay, and undergoing surgery during the last 3 months of the study were independent predictors of discharge without an opioid prescription, whereas depression, non-Black and non-White race, and using more opioid pills on the day before discharge were independent predictors of receiving an opioid prescription. Among patients discharged without an opioid prescription, 1.8% (10 of 547) were subsequently prescribed an opioid. CONCLUSIONS: Discharging select patients without an opioid prescription after cardiac surgery appears well tolerated, with a low incidence of postdischarge opioid prescriptions. Increasing the number of patients discharged without an opioid prescription may be an area for quality improvement.

Establishment and Implementation of Evidence-Based Opioid Prescribing Guidelines in Cardiac Surgery.

BACKGROUND: Despite the risk of new persistent opioid use after cardiac surgery, postdischarge opioid use has not been quantified and evidence-based prescribing guidelines have not been established. METHODS: Opioid-naive patients undergoing primary cardiac surgery via median sternotomy between January and December 2019 at 10 hospitals participating in a statewide collaborative were selected. Clinical data were linked to patient-reported outcomes collected at 30-day follow-up. An opioid prescribing recommendation stratified by inpatient opioid use on the day before discharge (0, 1-3, or ≥4 pills) was implemented in July 2019. Interrupted time-series analyses were performed for prescription size and postdischarge opioid use before (January to June) and after (July to December) guideline implementation. RESULTS: Among 1495 patients (729 prerecommendation and 766 postrecommendation), median prescription size decreased from 20 pills to 12 pills after recommendation release (P < .001), while opioid use decreased from 3 pills to 0 pills (P < .001). Change in prescription size over time was +0.6 pill/month before and -0.8 pill/month after the recommendation (difference = -1.4 pills/month; P = .036). Change in patient use was +0.6 pill/month before and -0.4 pill/month after the recommendation (difference = -1.0 pills/month; P = .017). Pain levels during the first week after surgery and refills were unchanged. Patients using 0 pills before discharge (n = 710) were prescribed a median of 0 pills and used 0 pills, while those using 1 to 3 pills (n = 536) were prescribed 20 pills and used 7 pills, and those using greater than or equal to 4 pills (n = 249) were prescribed 32 pills and used 24 pills. CONCLUSIONS: An opioid prescribing recommendation was effective, and prescribing after cardiac surgery should be guided by inpatient use.

Determinants of Value in Coronary Artery Bypass Grafting.

Background Over 180 000 coronary artery bypass grafting (CABG) procedures are performed annually, accounting for $7 to $10 billion in episode expenditures. Assessing tradeoffs between spending and quality contributing to value during 90-day episodes has not been conducted but is essential for success in bundled reimbursement models. We, therefore, identified determinants of variability in hospital 90-day episode value for CABG. Methods Medicare and private payor admissions for isolated CABG from 2014 to 2016 were retrospectively linked to clinical registry data for 33 nonfederal hospitals in Michigan. Hospital composite risk-adjusted complication rates (≥1 National Quality Forum-endorsed, Society of Thoracic Surgeons measure: deep sternal wound infection, renal failure, prolonged ventilation >24 hours, stroke, re-exploration, and operative mortality) and 90-day risk-adjusted, price-standardized episode payments were used to categorize hospitals by value by defining the intersection between complications and spending. Results Among 2573 total patients, those at low- versus high-value hospitals had a higher percentage of prolonged length of stay >14 days (9.3% versus 2.4%, P=0.006), prolonged ventilation (17.6% versus 4.8%, P<0.001), and operative mortality (4.8% versus 0.6%, P=0.001). Mean total episode payments were $51 509 at low-compared with $45 526 at high-value hospitals (P<0.001), driven by higher readmission ($3675 versus $2177, P=0.005), professional ($7462 versus $6090, P<0.001), postacute care ($7315 versus $5947, P=0.031), and index hospitalization payments ($33 474 versus $30 800, P<0.001). Among patients not experiencing a complication or 30-day readmission (1923/2573, 74.7%), low-value hospitals had higher inpatient evaluation and management payments ($1405 versus $752, P<0.001) and higher utilization of inpatient rehabilitation (7% versus 2%, P<0.001), but lower utilization of home health (66% versus 73%, P=0.016) and emergency department services (13% versus 17%, P=0.034). Conclusions To succeed in emerging bundled reimbursement programs for CABG, hospitals and physicians should identify strategies to minimize complications while optimizing inpatient evaluation and management spending and use of inpatient rehabilitation, home health, and emergency department services.

Evaluating the Impact of Pneumonia Prevention Recommendations After Cardiac Surgery.

BACKGROUND: Pneumonia is the most prevalent healthcare-associated infection after coronary artery bypass grafting (CABG), but the relative effectiveness of strategies to reduce its incidence remains unclear. We evaluated the relationship between healthcare-associated infection recommendations and risk of pneumonia after CABG. METHODS: Pneumonia prevention practice recommendations were developed based on literature review and analysis of semistructured interviews with key health care personnel across centers with low (<5.9%), medium (5.9%-6.1%), and high (>6.1%) rates of pneumonia. These practices were implemented among 2482 patients undergoing CABG from 2016 to 2017 across 18 centers. The independent effect of each practice in reducing pneumonia was assessed using multivariable logistic regression, adjusting for baseline risk and center. A composite (bundle) score was calculated as the number of practices (0 to 4) each patient received. RESULTS: Recommended pneumonia prevention practices included lung protective ventilation management, early extubation, progressive ambulation, and avoidance of postoperative bronchodilator therapy. Pneumonia occurred in 2.4% of patients. Lung protective ventilation (adjusted odds ratio [ORadj], 0.45; 95% confidence interval [CI], 0.22-0.92), ambulation (ORadj, 0.08; 95% CI, 0.04-0.17), and postoperative ventilation of less than 6 hours (ORadj, 0.47; 95% CI, 0.26-0.87) were significantly associated with lower odds of pneumonia. Postoperative bronchodilator therapy (ORadj, 4.83; 95% CI, 2.20-10.7) was significantly associated with higher odds. Risk-adjusted rates of pneumonia, operative mortality, and intensive care unit length of stay were lower in patients with higher bundle scores (all P-trend < .01). CONCLUSIONS: These pneumonia prevention recommendations may serve as effective targets for avoiding postoperative healthcare-associated infections.

Collaborative Quality Improvement Reduces Postoperative Pneumonia After Isolated Coronary Artery Bypass Grafting Surgery.

BACKGROUND: To date, studies evaluating outcome improvements associated with participation in physician-led collaboratives have been limited by the absence of a contemporaneous control group. We examined post cardiac surgery pneumonia rates associated with participation in a statewide, quality improvement collaborative relative to a national physician reporting program. METHODS AND RESULTS: We evaluated 911 754 coronary artery bypass operations (July 1, 2011, to June 30, 2017) performed across 1198 hospitals participating in a voluntary national physician reporting program (Society of Thoracic Surgeons [STS]), including 33 that participated in a Michigan-based collaborative (MI-Collaborative). Unlike STS hospitals not participating in the MI-Collaborative (i.e., STSnonMI) that solely received blinded reports, MI-Collaborative hospitals received a multi-faceted intervention starting November 2012 (quarterly in-person meetings showcasing unblinded data, webinars, site visits). Eighteen of the MI-Collaborative hospitals received additional support to implement recommended pneumonia prevention practices ("MI-CollaborativePlus"), whereas 15 did not ("MI-CollaborativeOnly"). We evaluated rates of postoperative pneumonia, adjusting for patient mix and hospital effects. Baseline patient characteristics were qualitatively similar between groups and time. During the preintervention period (Q3/2011 through Q3/2012), there was no statistically significant difference in the adjusted odds of pneumonia for STS hospitals participating in the MI-Collaborative compared to the STS non-MI hospitals. However, during the intervention period (Q4/2012 through Q2/2017), there was a significant 2% reduction per quarter in the adjusted odds of pneumonia for MI-Collaborative hospitals (n=33) relative to the STS-nonMI hospitals. There was a significant 3% per quarter reduction in the adjusted odds of pneumonia for the MI-CollaborativeOnly (n=15) hospitals relative to the STS-nonMI hospitals. Over the course of the overall study period, the STS-nonMI hospitals had a 1.96% reduction in risk-adjusted pneumonia (pre- vs. intervention periods), which was less than the MI-Collaborative (3.23%, P=0.011). Over the same time period, the MI-CollaborativePlus (n=18) reduced adjusted pneumonia rates by 10.29%, P=0.001. CONCLUSIONS: Participation in a physician-led collaborative was associated with significant reductions in pneumonia relative to a national quality reporting program. Interventions including collaborative learning may yield superior outcomes relative to solely using physician feedback reporting. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT02068716.

Association Between Postoperative Pneumonia and 90-Day Episode Payments and Outcomes Among Medicare Beneficiaries Undergoing Cardiac Surgery.

Background Postoperative pneumonia is the most common healthcare-associated infection in cardiac surgical patients, yet their impact across a 90-day episode of care remains unknown. Our objective was to examine the relationship between pneumonia and 90-day episode payments and outcomes among Medicare beneficiaries undergoing cardiac surgery. Methods and Results Medicare claims were used to identify beneficiaries with episodes of coronary artery bypass grafting (CABG; n=56 728) and valve surgery (n=56 377) across 1045 centers between April 2014 and March 2015. Using a published diagnosis code-based algorithm, we identified pneumonia in 6.4% CABG episodes and 6.6% of valve surgery episodes. We compared price-standardized 90-day episode payments and outcome measures (postoperative length of stay, discharge to postacute care, mortality, and readmission) between beneficiaries with and without pneumonia using hierarchical regression models, adjusting for patient factors and hospital random effects. Pneumonia was associated with 24.5% higher episode payments for CABG ($46 723 versus $37 496; P<0.001) and 26.5% higher episode payments for valve surgery ($61 544 versus $48 549; P<0.001). For both cohorts, pneumonia was significantly associated with longer postoperative length of stay (CABG: +4.1 days, valve: +5.6 days), more frequent discharge to postacute care (CABG: odds ratio [OR]=1.99, valve: OR=2.17), and higher rates of 30-day mortality (CABG: OR=2.42, valve: OR=2.57) and 90-day readmission (CABG: OR=1.20, valve: OR=1.25), all P<0.001. We compared episode payments and outcomes across terciles of pneumonia rates and found that high pneumonia rate hospitals had higher episode payments and poorer outcomes compared with episodes at low pneumonia rate hospitals in both CABG and valve surgery cohorts. Conclusions Postoperative pneumonia was associated with significantly higher 90-day episode payments and inferior outcomes at the patient and hospital level. Future work should examine whether reducing pneumonia after cardiac surgery reduces episode spending and improves outcomes, which could facilitate hospital success in value-based reimbursement programs.

Determinants of Variation in Pneumonia Rates After Coronary Artery Bypass Grafting.

BACKGROUND: Although conventional wisdom suggests that differences in patient risk profiles drive variability in postoperative pneumonia rates after coronary artery bypass grafting (CABG), this teaching has yet to be empirically tested. We determined to what extent patient risk factors account for hospital variation in pneumonia rates. METHODS: We studied 324,085 patients undergoing CABG between July 1, 2011, and December 31, 2013, across 998 hospitals using The Society of Thoracic Surgeons Adult Cardiac Database. We developed 5 models to estimate our incremental ability to explain hospital variation in pneumonia rates. Model 1 contained patient demographic characteristics and admission status, while Model 2 added patient risk factors. Model 3 added measures of pulmonary function, Model 4 added measures of cardiac anatomy and function and medications, and Model 5 further added measures of intraoperative and postoperative care. RESULTS: Although 9,175 patients (2.83%) experienced pneumonia, the median estimated distribution of pneumonia rates across hospitals was 2.5% (25th to 75th percentile: 1.5% to 4.0%). Wide variability in pneumonia rates was evident, with some hospitals having rates more than 6 times higher than others (10th to 90th percentile: 1.0% to 6.1%). Among all five models, Model 2 accounted for the most variability at 4.24%. In total, 2.05% of hospital variation in pneumonia rates was explained collectively by traditional patient factors, leaving 97.95% of variation unexplained. CONCLUSIONS: Our findings suggest that patient risk profiles only account for a fraction of hospital variation in pneumonia rates; enhanced understanding of other contributory factors (eg, processes of care) is required to lessen the likelihood of such nosocomial infections.

Prediction of Transfusions After Isolated Coronary Artery Bypass Grafting Surgical Procedures.

BACKGROUND: Although blood transfusions are common and have been associated with adverse sequelae after cardiac surgical procedures, few contemporaneous models exist to support clinical decision making. This study developed a preoperative clinical decision support tool to predict perioperative red blood cell transfusions in the setting of isolated coronary artery bypass grafting. METHODS: We performed a multicenter, observational study of 20,377 patients undergoing isolated coronary artery bypass grafting among patients at 39 hospitals participating in the Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative's PERFusion measures and outcomes (PERForm) registry between 2011 and 2015. Candidates' preoperative risk factors were identified based on previous work and clinical input. The study population was randomly divided into a 70% development sample and a 30% validation sample. A generalized linear mixed-effect model was developed to predict perioperative red blood cell transfusion. The model's performance was assessed for calibration and discrimination. Sensitivity analysis was performed to assess the robustness of the model in different clinical subgroups. RESULTS: Transfusions occurred in 36.8% of patients. The final regression model included 16 preoperative variables. The correlation between the observed and expected transfusions was 1.0. The risk prediction model discriminated well (receiver operator characteristic [ROC]development, 0.81; ROCvalidation, 0.82) and had satisfactory calibration (correlation between observed and expected rates was r = 1.00). The model performance was confirmed across medical centers and clinical subgroups. CONCLUSIONS: Our risk prediction model uses 16 readily obtainable preoperative variables. This model, which provides a patient-specific estimate of the need for transfusion, offers clinicians a guide for decision making and evaluating the effectiveness of blood management strategies.

A Preoperative Risk Model for Postoperative Pneumonia After Coronary Artery Bypass Grafting.

BACKGROUND: Postoperative pneumonia is the most prevalent of all hospital-acquired infections after isolated coronary artery bypass graft surgery (CABG). Accurate prediction of a patient's risk of this morbid complication is hindered by its low relative incidence. In an effort to support clinical decision making and quality improvement, we developed a preoperative prediction model for postoperative pneumonia after CABG. METHODS: We undertook an observational study of 16,084 patients undergoing CABG between the third quarter of 2011 and the second quarter of 2014 across 33 institutions participating in the Michigan Society of Thoracic and Cardiovascular Surgeons Quality Collaborative. Variables related to patient demographics, medical history, admission status, comorbid disease, cardiac anatomy, and the institution performing the procedure were investigated. Logistic regression through forward stepwise selection (p < 0.05 threshold) was utilized to develop a risk prediction model for estimating the occurrence of pneumonia. Traditional methods were used to assess the model's performance. RESULTS: Postoperative pneumonia occurred in 3.30% of patients. Multivariable analysis identified 17 preoperative factors, including demographics, laboratory values, comorbid disease, pulmonary and cardiac function, and operative status. The final model significantly predicted the occurrence of pneumonia, and performed well (C-statistic: 0.74). These findings were confirmed through sensitivity analyses by center and clinically important subgroups. CONCLUSIONS: We identified 17 readily obtainable preoperative variables associated with postoperative pneumonia. This model may be used to provide individualized risk estimation and to identify opportunities to reduce a patient's preoperative risk of pneumonia through prehabilitation.

Sources of Variation in Hospital-Level Infection Rates After Coronary Artery Bypass Grafting: An Analysis of The Society of Thoracic Surgeons Adult Heart Surgery Database.

BACKGROUND: Patients undergoing coronary artery bypass grafting (CABG) are at risk for a variety of infections. Investigators have focused on predictors of these adverse sequelae, but less attention has been focused on characterizing hospital-level variability in these outcomes. METHODS: Between July 2011 and December 2013, The Society of Thoracic Surgeons Adult Cardiac Surgery Database shows 365,686 patients underwent isolated CABG in 1,084 hospitals. Hospital-acquired infections (HAIs) were defined as pneumonia, sepsis/septicemia, deep sternal wound infection/mediastinitis, vein harvest/cannulation site infection, or thoracotomy infection. Hospitals were ranked by their HAI rate as low (≤ 10th percentile), medium (10th to 90th percentile), and high (>90th percentile). Differences in perioperative factors and composite morbidity and mortality end points across these groups were determined using the Wilcoxon rank sum and χ(2) tests. RESULTS: HAIs occurred among 3.97% of patients overall, but rates varied across hospital groups (low: <0.84%, medium: 0.84% to 8.41%, high: >8.41%). Pneumonia (2.98%) was the most common HAI, followed by sepsis/septicemia (0.84%). Patients at high-rate hospitals more often smoked, had diabetes, chronic lung disease, New York Heart Association Functional Classification III to IV, and received blood products (p < 0.001); however, they less often were prescribed the appropriate antibiotics (p < 0.001). Major morbidity and mortality occurred among 12.3% of patients, although this varied by hospital group (low: 8.6%, medium: 12.3%, high: 17.9%; p < 0.001). CONCLUSIONS: Substantial hospital-level variation exists in postoperative HAIs among patients undergoing CABG, driven predominantly by pneumonia. Given the relatively small absolute differences in comorbidities across hospital groups, our findings suggest factors other than case mix may explain the observed variation in HAI rates.

Red Blood Cell Transfusions Impact Pneumonia Rates After Coronary Artery Bypass Grafting.

BACKGROUND: Pneumonia, a known complication of coronary artery bypass grafting (CABG), significantly increases a patient's risk of morbidity and mortality. Although not well characterized, red blood cell (RBC) transfusions may increase a patient's risk of pneumonia. We describe the relationship between RBC transfusion and postoperative pneumonia after CABG. METHODS: A total of 16,182 consecutive patients underwent isolated CABG between 2011 and 2013 at 1 of 33 hospitals in the state of Michigan. We used multivariable logistic regression to estimate the relative odds of pneumonia associated with the use or number of RBC units (0, 1, 2, 3, 4, 5, and ≥ 6). We adjusted for predicted risk of mortality, preoperative hematocrit values, history of pneumonia, cardiopulmonary bypass duration, and medical center. We confirmed the strength and direction of these relationships among selected clinical subgroups in a secondary analysis. RESULTS: Five hundred seventy-six (3.6%) patients had pneumonia and 6,451 (39.9%) received RBC transfusions. There was a significant association between any RBC transfusion and pneumonia (adjusted odds ratio [ORadj], 3.4; p < 0.001). There was a dose response between number of units and odds of pneumonia, with a ptrend less than 0.001. Patients receiving only 2 units of RBCs had a 2-fold (ORadj, 2.1; p < 0.001) increased odds of developing pneumonia. These findings were consistent across clinical subgroups. CONCLUSIONS: We found a significant volume-dependent association between an increasing number of RBCs and the odds of pneumonia, which persisted after risk adjustment. Clinical teams should explore opportunities for preventing a patient's risk of RBC transfusions, including reducing hemodilution or adopting a lower transfusion threshold in a stable patient.

Center-level variation in infection rates after coronary artery bypass grafting.

BACKGROUND: Health-care-acquired infections (HAIs) are a leading cause of morbidity and mortality after cardiac surgery. Prior work has identified several patient-related risk factors associated with HAIs. We hypothesized that rates of HAIs would differ across institutions, in part attributed to differences in case mix. METHODS AND RESULTS: We analyzed 20 896 patients undergoing isolated coronary artery bypass grafting surgery at 33 medical centers in Michigan between January 1, 2009, and June 30, 2012. Overall HAIs included pneumonia, sepsis/septicemia, and surgical site infections, including deep sternal wound, thoracotomy, and harvest/cannulation site infections. We excluded patients presenting with endocarditis. Predicted rates of HAIs were estimated using multivariable logistic regression. Overall rate of HAI was 5.1% (1071 of 20 896; isolated pneumonia, 3.1% [n=644]; isolated sepsis/septicemia, 0.5% [n=99]; isolated deep sternal wound infection, 0.5% [n=96]; isolated harvest/cannulation site, 0.5% [n=97]; isolated thoracotomy, 0.02% [n=5]; multiple infections, 0.6% [n=130]). HAI subtypes differed across strata of center-level HAI rates. Although predicted risk of HAI differed in absolute terms by 2.8% across centers (3.9-6.7%; min:max), observed rates varied by 18.2% (0.9-19.1%). CONCLUSIONS: There was a 18.2% difference in observed HAI rates across medical centers among patients undergoing isolated coronary artery bypass grafting surgery. This variability could not be explained by patient case mix. Future work should focus on the impact of other factors (eg, organizational and systems of clinical care) on risk of HAIs.