Application of a complication screening method to congenital heart surgery admissions: a preliminary report

Morbidity During Adult Congenital Heart Surgery Admissions

The frequency of complications during Adult Congenital Heart Disease (ACHD) surgery admissions and their association to patient outcome is not well known. Our study objectives are to (1) define the frequency of complications during ACHD surgery admissions, (2) identify their risk factors, and (3) explore their association with death and resource use. We identified ACHD surgery admissions ages 18 to 49 during the years 2005-2009 from the Nationwide Inpatient Sample database. Complications were defined according to the Society of Thoracic Surgeons Short List of Complications for congenital heart surgery. We identified 16,841 ACHD surgery admissions, of which 46.9% had at least one complication. Cardiac (19.4%), respiratory (18.2%), infectious (14.1%), and acute kidney injury (6.8%) were the most common. Admissions with a complication had a longer length of stay (10 days vs. 5 days; p < 0.001), increased charges ($139,522 vs. $84,672; p < 0.001), and higher mortality (4.6% vs. 0.9%; p < 0.001). Adjusted risk factors for complications included non-White race (AOR 1.17, p = 0.003), government insurance AOR 1.39, high surgical complexity RACHS-1 category 3 + AOR 1.81, non-elective admission OR 2.18, chronic kidney disease AOR 2.79, chronic liver disease AOR 2.47, and CHF AOR 1.40; all p < 0.001. Complications were independently associated with death AOR 2.49, p < 0.001. Complications occur frequently during ACHD surgery admissions and are associated with increased resource use and are a risk factor for death. Identification of preventable morbidity may improve the outcomes of these complex patients.

Readmissions Following Congenital Heart Surgery in Infants and Children

Thirty-day readmission after congenital heart surgery (CHS) is an important outcome given the vulnerability of pediatric patients. We hypothesized that readmissions after pediatric CHS are common and identifiable risk factors exist. We obtained State Inpatient Databases for Washington, New York, Florida, and California and selected CHS admissions age < 19 years. The main outcome was readmission defined as non-elective hospitalization < 31 days of discharge from index CHS admission. In multivariable analyses using generalized estimating equations, we examined associations of patient-level characteristics (age, sex, race, household income, insurance status, genetic syndromes, co-morbidities, RACHS-1 surgical risk category and complication) and admission characteristics [weekend admission, urgent/emergent admission, and high resource use (HRU)] with 30-day pediatric readmission after adjusting for case mix. Among 8585 index admissions we identified 967 readmissions (11.3%). Median length of stay for readmissions was 5 days, median total charge of $31,973, and mortality rate 1.8%. Among readmissions, 1.7% underwent another CHS of which 44% were HRU, complication rate 88% and mortality 6.25%. In multivariable analysis, age 1 month-1 year AOR 1.3 p = 0.01; Hispanic ethnicity AOR 1.2 p = 0.03; government-insurance AOR 1.3 p = 0.01; RACHS-1 3 complexity AOR 2.4 p < 0.001; RACHS-1 4 + complexity 2.0 p = 0.001; HRU AOR 1.4 p = 0.02; complications AOR 1.1 p = 0.04; and emergent index admission AOR 2.0 p < 0.001 were risk factors for readmission. Over 11% of pediatric CHS admissions result in an unplanned readmission. Hispanic ethnicity, government insurance, HRU admissions, higher case complexity, complications, and emergent index admission are risk factors for readmission.

Congenital Heart Surgical Admissions in Patients with Trisomy 13 and 18: Frequency, Morbidity, and Mortality

Congenital heart defects are common among patients with trisomy 13 and 18; surgical repair has been controversial and rarely studied. We aimed to assess the frequency of cardiac surgery among admissions with trisomy 13 and 18, and evaluate their associations with resource use, complications, and mortality compared to admissions without these diagnoses. We evaluated congenital heart surgery admissions of ages < 18 years in the 1997, 2000, 2003, 2006, and 2009 Kids' Inpatient Database. Bivariate and multivariate analyses examined the adjusted association of trisomy 13 and 18 on resource use, complications, and inpatient death following congenital heart surgery. Among the 73,107 congenital heart surgery admissions, trisomy 13 represented 0.03% (n = 22) and trisomy 18 represented 0.08% (n = 58). Trisomy 13 and 18 admissions were longer; trisomy 13: 27 days vs. 8 days, p = 0.003; trisomy 18: 16 days vs. 8 days, p = 0.001. Hospital charges were higher for trisomy 13 and 18 admissions; trisomy 13: $160,890 vs. $87,007, p = 0.010; trisomy 18: $160,616 vs. $86,999, p < 0.001. Trisomy 18 had a higher complication rate: 52% vs. 34%, p < 0.006. For all cardiac surgery admissions, mortality was 4.5%; trisomy 13: 14% and trisomy 18: 12%. In multivariate analysis, trisomy 18 was an independent predictor of death: OR 4.16, 95% CI 1.35-12.82, p = 0.013. Patients with trisomy 13 and 18 represent 0.11% of pediatric congenital heart surgery admissions. These patients have a 2- to 3.4-fold longer hospital stay and double hospital charges. Patients with trisomy 18 have more complications and four times greater adjusted odds for inpatient death.

Development and Validation of an Agency for Healthcare Research and Quality Indicator for Mortality After Congenital Heart Surgery Harmonized With Risk Adjustment for Congenital Heart Surgery (RACHS-1) Methodology

BACKGROUND

The National Quality Forum previously approved a quality indicator for mortality after congenital heart surgery developed by the Agency for Healthcare Research and Quality (AHRQ). Several parameters of the validated Risk Adjustment for Congenital Heart Surgery (RACHS-1) method were included, but others differed. As part of the National Quality Forum endorsement maintenance process, developers were asked to harmonize the 2 methodologies.

METHODS AND RESULTS

Parameters that were identical between the 2 methods were retained. AHRQ's Healthcare Cost and Utilization Project State Inpatient Databases (SID) 2008 were used to select optimal parameters where differences existed, with a goal to maximize model performance and face validity. Inclusion criteria were not changed and included all discharges for patients <18 years with International Classification of Diseases, Ninth Revision, Clinical Modification procedure codes for congenital heart surgery or nonspecific heart surgery combined with congenital heart disease diagnosis codes. The final model includes procedure risk group, age (0-28 days, 29-90 days, 91-364 days, 1-17 years), low birth weight (500-2499 g), other congenital anomalies (Clinical Classifications Software 217, except for 758.xx), multiple procedures, and transfer-in status. Among 17 945 eligible cases in the SID 2008, the c statistic for model performance was 0.82. In the SID 2013 validation data set, the c statistic was 0.82. Risk-adjusted mortality rates by center ranged from 0.9% to 4.1% (5th-95th percentile).

CONCLUSIONS

Congenital heart surgery programs can now obtain national benchmarking reports by applying AHRQ Quality Indicator software to hospital administrative data, based on the harmonized RACHS-1 method, with high discrimination and face validity.

Intraoperative adverse events can be compensated by technical performance in neonates and infants after cardiac surgery: a prospective study

OBJECTIVE

Our objective was to define the relationship between surgical technical performance score, intraoperative adverse events, and major postoperative adverse events in complex pediatric cardiac repairs.

METHOD

Infants younger than 6 months were prospectively followed up until discharge from the hospital. Technical performance scores were graded as optimal, adequate, or inadequate based on discharge echocardiograms and need for reintervention after initial surgery. Case complexity was determined by Risk Adjustment in Congenital Heart Surgery (RACHS-1) category, and preoperative illness severity was assessed by Pediatric Risk of Mortality (PRISM) III score. Intraoperative adverse events were prospectively monitored. Outcomes were analyzed using nonparametric methods and a logistic regression model.

RESULTS

A total of 166 patients (RACHS 4-6 [49%]), neonates [50%]) were observed. Sixty-one (37%) had at least 1 intraoperative adverse event, and 47 (28.3%) had at least 1 major postoperative adverse event. There was no correlation between intraoperative adverse events and RACHS, preoperative PRISM III, technical performance score, or postoperative adverse events on multivariate analysis. For the entire cohort, better technical performance score resulted in lower postoperative adverse events, lower postoperative PRISM, and lower length of stay and ventilation time (P < .001). Patients requiring intraoperative revisions fared as well as patients without, provided the technical score was at least adequate.

CONCLUSIONS

In neonatal and infant open heart repairs, technical performance score is one of the main predictors of postoperative morbidity. Outcomes are not affected by intraoperative adverse events, including surgical revisions, provided technical performance score is at least adequate.

Diagnostic errors in pediatric echocardiography: development of taxonomy and identification of risk factors

BACKGROUND

Despite increased interest in complications within pediatric cardiology, the domain of imaging-related diagnostic errors has received little attention. We developed a new taxonomy for diagnostic errors within pediatric echocardiography that categorizes errors by severity, preventability, and primary contributor. Our objectives were to examine its findings when applied to diagnostic error cases and to identify risk factors for preventable or possibly preventable diagnostic errors.

METHODS AND RESULTS

Diagnostic errors were identified at a high-volume academic pediatric cardiac center from December 2004 to August 2007. Demographic, clinical, and situational variables were collected from these cases and controls. During the study period, approximately 50,660 echocardiograms were performed. Among the 87 diagnostic error cases identified, 70% affected clinical management or the patient was at risk of or experienced an adverse event. One third of the errors were preventable and 46% were possibly preventable; 69% of preventable errors were of moderate severity or greater. Univariate analysis demonstrated that preventable or possibly preventable errors were more likely to involve younger patients, lower body weight, study location, sedated/anesthetized patients, studies performed and interpreted at night, uncommon diagnoses, and greater anatomic complexity than controls. Multivariate analysis identified the following risk factors: rare or very rare diagnoses (adjusted odds ratio [AOR], 9.2; P<0.001), study location in the recovery room (AOR, 7.9; P<0.001), moderate anatomic complexity (AOR, 3.5; P=0.004), and patient weight <5 kg (AOR, 3.5; P=0.031).

CONCLUSIONS

A diagnostic error taxonomy and knowledge of risk factors can assist in identification of targets for quality improvement initiatives that aim to decrease diagnostic error in pediatric echocardiography.