A method to account for variation in congenital heart surgery charges

Interhospital Variation in the Costs of Pediatric/Congenital Cardiac Catheterization Laboratory Procedures: Analysis of Data From the Pediatric Health Information Systems Database

Background

Cardiac catheterization is an important but costly component of health care for young patients with cardiac disease. Measurement of variation in their cost between hospitals and identification of the reasons for this variation may help reduce cost without compromising quality.

Methods and Results

Using data from Pediatric Health Information Systems Database from January 2007 to December 2015, the costs of 9 procedures were measured. Mixed‐effects multivariable models were used to generate case‐mix–adjusted estimates of each hospital's cost for each procedure and measure interhospital variation. Procedures (n=35 637) from 43 hospitals were studied. Median costs varied from $8249 (diagnostic catheterization after orthotopic heart transplantation) to $38 909 (transcatheter pulmonary valve replacement). There was marked variation in the cost of procedures between hospitals with 3.5‐ to 8.9‐fold differences in the case‐mix–adjusted cost between the most and least expensive hospitals. No significant correlation was found between hospitals’ procedure‐specific mortality rates and costs. Higher procedure volume was not associated with lower cost except for diagnostic procedures in heart transplant patients and pulmonary artery angioplasty. At the hospital level, the proportion of cases that were outliers (>95th percentile) was significantly associated with rank in terms of cost (Spearman's ρ ranging from 0.37 to 0.89, P<0.01).

Conclusions

Large‐magnitude hospital variation in cost was not explained by case‐mix or volume. Further research is necessary to determine the degree to which variation in cost is the result of differences in the efficiency of the delivery of healthcare services and the rate of catastrophic adverse outcomes and resultant protracted and expensive hospitalizations.

Predictors of Extended Length of Hospital Stay Following Surgical Repair of Congenital Heart Diseases

The purpose of this study is to evaluate post-operative length of stay (LOS) following surgical repair of congenital heart defects (CHD) and to investigate baseline pre-operative factors and predictors of post-operative LOS (pLOS). Retrospective chart review of all cases of corrective surgery for CHD performed at the Pediatric Cardiology Unit, King Abdulaziz University Hospital, Jeddah during January 2013-December 2016. Baseline demographics, clinical factors, pre-operative, intra-operative, post-operative cardiac and extra-cardiac complications were analyzed as independent factors of pLOS using stepwise linear regression. Kaplan-Meier (KM) survival analysis was used to analyze the correlation of pLOS (in days) with the independent variables and estimate the probability to exceeding a given pLOS. A total 191 patients (52.4% male, 49.7% aged ≤ 1 year) were included with a median [range] LOS = 10 [3, 158] days. Several baseline clinical factors were associated with longer pLOS such as complex CHD types (tetralogy of Fallot, transposition of great arteries, etc.), high-risk RACHS categories and low weight at surgery. Independent risk factors of pLOS included pre-operative hemoglobin level (unstandardized regression coefficient: B = 2.96, p = 0.036) as the only pre-operative predictor of LOS, besides intra-operative complications (B = 11.72, p = 0.009) and posto-perative factors including MV duration (B = 9.39, p < 0.001), diet/feeding problems (B = 10.27, p = 0.001) and drain tube stay (B = 3.82, p = 0.003). KM survival curves confirmed that these factors increased the probability for longer LOS. Post-operative LOS was associated with several baseline and peri-operative factors; however, it was independently predicted by abnormal baseline hemoglobin level, the occurrence of intra-operative complications, besides post-operative feeding problems, chest drain stay, and MV duration.

Accurate Prediction of Congenital Heart Surgical Length of Stay Incorporating a Procedure-Based Categorical Variable

OBJECTIVES

There is increasing demand for the limited resource of Cardiac ICU care. In this setting, there is an expectation to optimize hospital resource use without restricting care delivery. We developed methodology to predict extended cardiac ICU length of stay following surgery for congenital heart disease.

DESIGN

Retrospective analysis by multivariable logistic regression of important predictive factors for outcome of postoperative ICU length of stay greater than 7 days.

SETTING

Cardiac ICU at Boston Children's Hospital, a large, pediatric cardiac surgical referral center.

PATIENTS

All patients undergoing congenital heart surgery at Boston Children's Hospital from January 1, 2010, to December 31, 2015.

INTERVENTIONS

No study interventions.

MEASUREMENTS AND MAIN RESULTS

The patient population was identified. Clinical variables and Congenital Heart Surgical Stay categories were recorded based on surgical intervention performed. A model was built to predict the outcome postoperative ICU length of stay greater than 7 days at the time of surgical intervention. The development cohort included 4,029 cases categorized into five Congenital Heart Surgical Stay categories with a C statistic of 0.78 for the outcome ICU length of stay greater than 7 days. Explanatory value increased with inclusion of patient preoperative status as determined by age, ventilator dependence, and admission status (C statistic = 0.84). A second model was optimized with inclusion of intraoperative factors available at the time of postoperative ICU admission, including cardiopulmonary bypass time and chest left open (C statistic 0.87). Each model was tested in a validation cohort (n = 1,008) with equivalent C statistics.

CONCLUSIONS

Using a model comprised of basic patient characteristics, we developed a robust prediction tool for patients who will remain in the ICU longer than 7 days after cardiac surgery, at the time of postoperative ICU admission. This model may assist in patient counseling, case scheduling, and capacity management. Further examination in external settings is needed to establish generalizability.

Three-dimensional printing: changing clinical care or just a passing fad?

PURPOSE OF REVIEW

Advances in medical imaging and three-dimensional (3D) reconstruction software have enabled a proliferation of 3D modeling and 3D printing for clinical applications. In particular, 3D printing has garnered an extraordinary media presence over the past few years. There is growing optimism that 3D printing can address patient specificity and complexity for improved interventional and surgical planning. Will this relatively untested technology bring about a paradigm shift in the clinical environment, or is it just a transient fad?

RECENT FINDINGS

Case studies and series centered around 3D printing are omnipresent in clinical and engineering journals. These primarily qualitative studies support the potential efficacy of the emerging technology. Few studies analyze the value of 3D printing, weighing its potential benefits against increasing costs (e.g., institutional overhead, labor, and materials).

SUMMARY

Clinical integration of 3D printing is growing rapidly, and its adoption into clinical practice presents unique workflow challenges. There are numerous clinical trials on the horizon that will finally help to elucidate the measured impact of 3D printing on clinical outcomes through quantitative analyses of clinical and economic metrics. The contrived integration of 3D printing into clinical practice seems all but certain as the value of this technology becomes more and more evident.

A Method to Account for Variation in Congenital Heart Surgery Length of Stay

OBJECTIVES

We sought to develop a risk-adjustment methodology for length of stay in congenital heart surgery, as none exist.

DESIGN

Prospective cohort analysis combined with previously obtained retrospective cohort analysis of a Department of Cardiovascular Surgery clinical database.

PATIENTS

Patients discharged from Boston Children's Hospital between October 1, 2006, and May 31, 2014, that underwent a congenital heart surgery procedure(s) linked to one of 103 surgical procedure types.

MEASUREMENTS AND MAIN RESULTS

Six thousand two hundred nine discharges during the reporting period at Boston Children's Hospital comprised the cohort. Seven Surgical Length Categories were developed to group surgical procedure types. A multivariable model for outcome length of stay was built using a derivation cohort consisting of a 75% random sample, starting with Surgical Length Categories and considering additional a priori factors. Postoperative factors were then added to improve predictive performance. The remaining 25% of the cohort was used to validate the multivariable models. The coefficient of determination (R) was used to estimate the variability in length of stay explained by each factor. The Surgical Length Categories yielded an R of 42%. Model performance increased when the a priori factors preoperative status, noncardiac abnormality, genetic anomaly, preoperative catheterization during episode of care, weight less than 3 kg, and preoperative vasoactive support medication were introduced to the model (R = 60.8%). Model performance further improved when postoperative ventilation greater than 7 days, operating room time, postoperative catheterization during episode of care, postoperative reintubation, number of postoperative vasoactive support medications, postoperative ICU infection, and greater than or equal to one secondary surgical procedure were added (R = 76.7%). The validation cohort yielded an R of 76.5%.

CONCLUSIONS

We developed a statistically valid procedure-based categorical variable and multivariable model for length of stay of congenital heart surgeries. The Surgical Length Categories and important a priori and postoperative factors may be used to pursue a predictive tool for length of stay to inform scheduling and bed management practices.