Keywords

Introduction

Although significant progress has been made in the care of patients with pediatric and congenital cardiac disease, complications and death still occur. As a result, optimization of outcomes remains a constant goal. Substantial efforts has been devoted to advancing the science of assessing the outcomes and improving the quality of care associated with the treatment of patients with pediatric and congenital cardiac disease [1–227]. The importance of these efforts is supported by the fact that congenital heart defects are the most common birth anomalies, with moderate to severe variants occurring in approximately 6 per 1,000 live births [228].

In order to perform meaningful multi-institutional outcomes analyses and quality improvement, any database must incorporate the following seven essential elements:

  1. 1.

    Use of a common language and nomenclature [1–52, 54, 55, 62–64, 66–71, 75, 77, 79, 81, 82, 87, 88, 93, 94, 96, 100, 103, 104, 110–112, 114–116, 128–140, 148, 152, 155, 162, 167–169, 171, 172, 178, 179, 188, 191, 200–202, 209, 210, 213, 216, 218, 221]

  2. 2.

    Use of a database with an established uniform core dataset for collection of information [1–23, 55, 58–60, 63, 64, 71, 77, 79–82, 87, 88, 90, 93, 95, 98, 100, 104–106, 110–113, 115, 117–123, 145, 146, 148, 152–155, 161, 163, 164, 171, 172, 174, 178, 179, 185, 188, 189, 204, 207, 210, 212, 214, 216, 220–227]

  3. 3.

    Incorporation of a mechanism of evaluating case complexity [56, 57, 61, 65, 72–74, 76–79, 81–84, 88–91, 97–102, 104, 106, 107, 110–112, 124, 125, 141, 142, 147–150, 152, 178, 179, 188, 204, 215–217, 221]

  4. 4.

    Availability of a mechanism to assure and verify the completeness and accuracy of the data collected [77, 81, 85, 86, 88, 100, 104, 110–112, 126, 148, 152, 178, 179, 188, 216, 221]

  5. 5.

    Collaboration between medical and surgical subspecialties [81, 100, 104, 110–140, 148, 152, 178, 179, 188, 216, 221]

  6. 6.

    Standardization of protocols for life-long follow-up [104, 109–112, 127, 145, 146, 152, 164, 173, 178, 179, 184, 188, 189, 214, 216, 221]

  7. 7.

    Incorporation of strategies for quality assessment and quality improvement [108, 110, 115, 143–148, 151, 152, 154, 156–160, 165–167, 170, 175–183, 186–188, 190, 192–199, 203, 205, 206, 208, 210, 211, 216, 219, 221, 222]

The foundation of these seven elements is the use of a common language and nomenclature. The remaining six elements are all dependent on this nomenclature; and therefore, quality improvement in the domain of congenital cardiac disease depends on a solid understanding of cardiac morphology and nomenclature.

Events at Bristol, England [229], Denver, Colorado, United States of America [230–236], Winnipeg, Canada [237], Mid Staffordshire, England [238] and Lexington, Kentucky, United States of America [239] have clearly demonstrated the importance of clinically driven analysis of outcomes. For example, the Bristol Report presents the results of the inquiry into the management of the care of children receiving complex cardiac surgical services at the Bristol Royal Infirmary between 1984 and 1995 and relevant related issues. Approximately 200 recommendations are made, many of which relate to the need for accurate multi-institutional outcomes databases to quantitate outcomes of care rendered to patients with congenital cardiac disease. Perhaps less well-known than the Bristol Report, the Report of the Manitoba Pediatric Cardiac Surgery Inquest presents data from an inquest involving 12 children who died while undergoing, or soon after having undergone, cardiac surgery at the Winnipeg Health Sciences Centre in 1994. Clearly, these events demonstrate the importance of a meaningful and fair method of multi-institutional analysis of outcomes for congenital cardiac surgery.

Nomenclature

Substantial effort has been devoted to the standardization of nomenclature and definitions related to surgery for pediatric and congenital cardiac disease. During the 1990s, both The European Association for Cardio-Thoracic Surgery (EACTS) and The Society of Thoracic Surgeons (STS) created databases to assess the outcomes of congenital cardiac surgery. Beginning in 1998, these two organizations collaborated to create the International Congenital Heart Surgery Nomenclature and Database Project. By 2000, a common nomenclature and a common core minimal dataset were adopted by EACTS and STS and published in the Annals of Thoracic Surgery [21]. In 2000, The International Nomenclature Committee for Pediatric and Congenital Heart Disease was established. This committee eventually evolved into the International Society for Nomenclature of Paediatric and Congenital Heart Disease (ISNPCHD). By 2005, members of the ISNPCHD crossmapped the nomenclature of the International Congenital Heart Surgery Nomenclature and Database Project of the EACTS and STS with the European Paediatric Cardiac Code (EPCC) of the Association for European Paediatric Cardiology (AEPC), and therefore created the International Pediatric and Congenital Cardiac Code (IPCCC) [114], which is available for free download from the internet at [http://www.IPCCC.NET].

Most international databases of patients with pediatric and congenital cardiac disease use the IPCCC as their foundation. Two versions of the IPCCC are used in the overwhelming majority of multi-institutional databases throughout the world:

  1. 1.

    The version of the IPCCC derived from the nomenclature of the International Congenital Heart Surgery Nomenclature and Database Project of the EACTS and the STS

  2. 2.

    The version of the IPCCC derived from the nomenclature of the EPCC of the AEPC

These two versions of the IPCCC are also often referred to with the following abbreviated short names:

  1. 1.

    EACTS-STS derived version of the IPCCC

  2. 2.

    AEPC derived version of the IPCCC

The STS Congenital Heart Surgery Database, the EACTS Congenital Heart Surgery Database, and The Japan Congenital Cardiovascular Surgery Database (JCCVSD) all use the EACTS-STS derived version of the IPCCC.

The ISNPCHD has published review articles which provide a unified and comprehensive classification, with definitions, for several complex congenital cardiac malformations: the functionally univentricular heart [92], hypoplastic left heart syndrome [94], discordant atrioventricular connections [96] and cardiac structures in the setting of heterotaxy [103]. These review articles include definitions and a complete listing of the relevant codes and terms in both versions of the IPCCC.

In collaboration with the World Health Organization (WHO), the ISNPCHD is developing the pediatric and congenital cardiac nomenclature that will be used in the eleventh version of the International Classification of Diseases (ICD-11). With a grant funded by The Children’s Heart Foundation [http://www.childrensheartfoundation.org/], the ISNPCHD has also linked images and videos to the IPCCC. These images and videos are acquired from cardiac morphologic specimens and imaging modalities such as echocardiography, angiography, computerized axial tomography, and magnetic resonance imaging, as well as intraoperative images and videos [162, 191, 200–202, 209, 213, 218]. These images and videos are available for free download from the internet at [http://www.IPCCC-awg.NET]. The IPCCC itself is available for free download from the internet at [http://www.IPCCC.NET].

The EACTS-STS derived version of the IPCCC [110, 112, 114], and the common minimum database data set created by the International Congenital Heart Surgery Nomenclature and Database Project [208], are now utilized by the STS Congenital Heart Surgery Database, the EACTS Congenital Heart Surgery Database, and the JCCVSD. Between 1998 and January 1, 2014 inclusive, this nomenclature and database was used by STS, EACTS, and JCCVSD to analyze outcomes of 479,000 operations.

Several studies have examined the relative utility of clinical and administrative nomenclature for the evaluation of quality of care for patients undergoing treatment for pediatric and congenital cardiac disease. Evidence from four recent investigations suggests that the validity of coding of lesions seen in the congenitally malformed heart via 9th ICD Revision of the International Classification of Diseases (ICD-9) as used currently in administrative databases in the United States of America is poor [116, 210, 240, 241]. First, in a series of 373 infants with congenital cardiac defects at Children’s Hospital of Wisconsin, investigators reported that only 52 % of the cardiac diagnoses in the medical records had a corresponding code from the ICD-9 in the hospital discharge database [240]. Second, the Hennepin County Medical Center discharge database in Minnesota identified all infants born during 2001 with a code for congenital cardiac disease using ICD-9. A review of these 66 medical records by physicians was able to confirm only 41 % of the codes contained in the administrative database from ICD-9 [241]. Third, the Metropolitan Atlanta Congenital Defect Program of the Birth Defect Branch of the Centers for Disease Control and Prevention of the United States government carried out surveillance of infants and fetuses with cardiac defects delivered to mothers residing in Atlanta during the years 1988 through 2003 [116]. These records were reviewed and classified using both administrative coding and the clinical nomenclature used in the Society of Thoracic Surgeons Congenital Heart Surgery Database. This study concluded that analyses based on the codes available in ICD-9 are likely to “have substantial misclassification” of congenital cardiac disease. Fourth, a study was performed using linked patient data (2004–2010) from the Society of Thoracic Surgeons Congenital Heart Surgery (STS-CHS) Database (clinical registry) and the Pediatric Health Information Systems (PHIS) database (administrative database) from hospitals participating in both in order to evaluate differential coding/classification of operations between datasets and subsequent impact on outcomes assessment [210]. The cohort included 59,820 patients from 33 centers. There was a greater than 10 % difference in the number of cases identified between data sources for half of the benchmark operations. The negative predictive value (NPV) of the administrative (versus clinical) data was high (98.8–99.9 %); the positive predictive value (PPV) was lower (56.7–88.0 %). These differences translated into significant differences in outcomes assessment, ranging from an underestimation of mortality associated with truncus arteriosus repair by 25.7 % in the administrative versus clinical data (7.01 % versus 9.43 %; p = 0.001) to an overestimation of mortality associated with ventricular septal defect (VSD) repair by 31.0 % (0.78 % versus 0.60 %; p = 0.1). This study demonstrates differences in case ascertainment between administrative and clinical registry data for children undergoing cardiac operations, which translated into important differences in outcomes assessment.

Several potential reasons can explain the poor diagnostic accuracy of administrative databases and codes from ICD-9:

  • Accidental miscoding

  • Coding performed by medical records clerks who have never seen the actual patient

  • Contradictory or poorly described information in the medical record

  • Lack of diagnostic specificity for congenital cardiac disease in the codes of ICD-9

  • Inadequately trained medical coders.

Although one might anticipate some improvement in diagnostic specificity with the planned adoption of ICD-10 by the United States, it is likely to still be far short from that currently achieved with clinical registries. (ICD-9 has only 29 congenital cardiac codes and ICD-10 has 73 possible congenital cardiac terms.) It will not be until there is implementation of the pediatric and congenital cardiac components of ICD-11 that harmonization of clinical and administrative nomenclature will be achieved with the resolution, therefore, of many of these challenging issues.

Database

The STS Congenital Heart Surgery Database is the largest database in North America dealing with congenital cardiac malformations [117, 152]. It has grown annually since its inception, both in terms of the number of participating centers submitting data, and the number of operations analyzed (Figs. 8.1, 8.2 and 8.3). As of January 1, 2014, the STS Congenital Heart Surgery Database currently has 111 Participating Centers representing 120 hospitals performing pediatric and congenital cardiac surgery in North America: 117 out of an estimated 125 centers from the United States of America that perform pediatric and congenital heart surgery and 3 out of centers 8 from Canada that perform pediatric and congenital heart surgery [95, 174]. (The Report of the 2005 STS Congenital Heart Surgery Practice and Manpower Survey, undertaken by the STS Workforce on Congenital Heart Surgery, documented that 122 centers in the United States of America perform pediatric and congenital heart surgery and 8 centers in Canada perform pediatric and congenital heart surgery [95]. The Report of the 2010 STS Congenital Heart Surgery Practice and Manpower Survey, undertaken by the STS Workforce on Congenital Heart Surgery, documented that 125 centers in the United States of America perform pediatric and congenital heart surgery and 8 centers in Canada perform pediatric and congenital heart surgery [174].)

Fig. 8.1
figure 1

The graph documents the annual growth of the STS Congenital Heart Surgery Database by number of participating centers submitting data. The aggregate report from the Fall 2013 Harvest of the STS Congenital Heart Surgery Database [19] includes data from 111 North American Congenital Database Participants representing 120 Congenital Heart Surgery hospitals in the North America, 117 in the United States of America and 3 in Canada

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Fig. 8.2
figure 2

The graph documents the annual growth of the STS Congenital Heart Surgery Database by the number of operations per averaged 4 year data collection cycle. The aggregate report from the Fall 2013 Harvest of the STS Congenital Heart Surgery Database [19] includes 136,617 operations performed in the 4 year period of July 1, 2009–June 30, 2013, inclusive, submitted from 120 hospitals in North America, 117 in the United States of America and 3 in Canada

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Fig. 8.3
figure 3

The graph documents the annual growth of the STS Congenital Heart Surgery Database by the cumulative number of operations over time. As of January 1, 2014, the number of cumulative total operations in the STS Congenital Heart Surgery Database is 292,828. The aggregate report from the Fall 2013 Harvest of the STS Congenital Heart Surgery Database [19] includes 136,617 operations performed in the 4 year period of July 1, 2009–June 30, 2013, inclusive, submitted from 120 hospitals in North America, 117 in the United States of America and 3 in Canada

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The STS Congenital Heart Surgery Database therefore contains data from an estimated 93.6 % of hospitals (117 out of 125) performing pediatric cardiac surgery in the United States. With penetrance of over 90 %, the data in the STS Congenital Heart Surgery Database is representative of pediatric and congenital heart surgery in the United States of America. As of January 1, 2014, the number of cumulative total operations in the STS Congenital Heart Surgery Database is 292,828 [19]. The aggregate Participant Feedback Report from the Fall 2013 Harvest of the STS Congenital Heart Surgery Database includes 136,617 operations performed in the 4 year analytic window of July 1, 2009 to June 30, 2013, inclusive, submitted from 120 hospitals in North America, 117 in the United States of America and 3 in Canada. In collaboration with EACTS, the STS has developed standardized methodology for tracking mortality and morbidity associated with the treatment of patients with congenital and pediatric cardiac disease [93, 105].

The EACTS Congenital Heart Surgery Database is the largest database in Europe dealing with congenital cardiac malformations (Fig. 8.4) [112, 117]. As of May 2013, the EACTS Congenital Heart Surgery Database contained 157,772 operations performed in 130,534 patients. As of May, 2013, the EACTS Congenital Heart Surgery Database had 348 Centers from 76 countries registered, with 173 active Centers from 46 countries submitting data.

Fig. 8.4
figure 4

The graph documents the annual growth in The European Association for Cardio-Thoracic Surgery Congenital Database by both number of patients and number of operations. As of May 2013, the EACTS Congenital Heart Surgery Database contained 157,772 operations performed in 130,534 patients. As of May, 2013, the EACTS Congenital Heart Surgery Database had 348 Centers from 76 countries registered, with 173 active Centers from 46 countries submitting data (This graph is provided courtesy of Bohdan Maruszewski of the Children’s Memorial Health Institute in Warsaw, Poland, Director of The European Association for Cardio-Thoracic Surgery Congenital Database, and President of The European Congenital Heart Surgeons Association (ECHSA))

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The JCCVSD has recently been operationalized based on identical nomenclature and database standards as that used by EACTS and STS [117]. The JCCVSD began enrolling patients in 2008. By December 2011, over 100 hospitals were submitting data, and by April 2013, over 29,000 operations were entered into the JCCVSD, in just under 5 years of data collection (Fig. 8.5). In Japan, it is mandatory for specialists to enroll in this benchmarking project in order to objectively examine their own performance and make efforts for continuous improvement. In the future, certification in Japan is to be performed solely on the basis of empirical data registered by the project. The developers of the JCCVSD hope to collaborate with their colleagues across Asia to create an Asian Congenital Heart Surgery Database.

Fig. 8.5
figure 5

The graph documents the initial growth of The Japan Congenital Cardiovascular Surgery Database (JCCVSD). The JCCVSD has recently been operationalized based on identical nomenclature and database standards as that used by EACTS and STS. The JCCVSD began enrolling patients in 2008. By December 2011, over 100 hospitals were submitting data, and by April 2013, over 29,000 operations were entered into the JCCVSD, in just under five years of data collection. The developers of the JCCVSD hope to collaborate with their colleagues across Asia to create an Asian Congenital Heart Surgery Database (This graph is provided courtesy of Arata Murakami, MD of The University of Tokyo in Tokyo, Japan)

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In the United Kingdom, the United Kingdom Central Cardiac Audit Database (UKCCAD) uses the AEPC derived version of the IPCCC as the basis for its national, comprehensive, validated, and benchmark-driven audit of all pediatric surgical and transcatheter procedures undertaken since 2000 [152]. All 13 tertiary centers in the United Kingdom performing cardiac surgery or therapeutic cardiac catheterization in children with congenital cardiac disease submit data to the UKCCAD. Data about mortality is obtained from both results volunteered from the hospital databases, and by independently validated records of deaths obtained by the Office for National Statistics, using the patient’s unique National Health Service number, or the general register offices of Scotland and Northern Ireland. Efforts are underway to link the UKCCAD to The EACTS Congenital Heart Surgery Database. Linkage of the UKCCAD to The EACTS Congenital Heart Surgery Database will require use of the crossmap of the AEPC derived version of the IPCCC (used by the UKCCAD) to the EACTS-STS derived version of the IPCCC (used by the EACTS, STS, and JCCVSD).

As of January 1, 2014, the STS Congenital Heart Surgery Database contains data from 292,828 operations, the EACTS Congenital Heart Surgery Database contains data from over 157,772 operations, and the JCCVSD contains data from over 29,000 operations. Therefore, the combined dataset of the STS Congenital Heart Surgery Database, the EACTS Congenital Heart Surgery Database, and the JCCVSD, contains data from over 479,000 operations, all coded with the EACTS-STS derived version of the IPCCC [100, 110, 112, 114], and all coded with identical data specifications [208].

Complexity Stratification

The importance of measurement of complexity derives from the fact that analysis of outcomes using raw measurements of mortality, without adjustment for complexity, is inadequate. The mix of cases can vary greatly from program to program. Without stratification of complexity, the analysis of outcomes will be flawed [56, 61, 73, 74, 76, 82, 106, 149, 150].

The analysis of outcomes after surgery requires a reliable method of estimating the risk of adverse events. However, formal risk modeling is challenging for rare operations. Complexity stratification provides an alternative methodology that can facilitate the analysis of outcomes of rare operations. Complexity stratification is a method of analysis in which the data are divided into relatively homogeneous groups (called strata). The data are analyzed within each stratum.

Three major multi-institutional efforts have attempted to measure the complexity of congenital cardiac surgical operations:

  1. 1.

    Risk Adjustment in Congenital Heart Surgery-1 methodology (RACHS-1 method) [56, 73, 149]

  2. 2.

    Aristotle Basic Complexity Score (ABC Score) [61, 74, 76, 82, 106, 149]

  3. 3.

    STS-EACTS Congenital Heart Surgery Mortality Categories (STS-EACTS Mortality Categories) (STAT Mortality Categories) [150].

RACHS-1 and the ABC Score were developed at a time when limited multi-institutional clinical data were available and were therefore based in a large part on subjective probability (expert opinion). The STAT Mortality Categories are a tool for complexity stratification that was developed from an analysis of 77,294 operations entered into the EACTS Congenital Heart Surgery Database (33,360 operations) and the STS Congenital Heart Surgery Database (43,934 patients) between 2002 and 2007. Procedure-specific mortality rate estimates were calculated using a Bayesian model that adjusted for small denominators. Operations were sorted by increasing risk and grouped into five categories (the STS–EACTS Congenital Heart Surgery Mortality Categories) that were designed to be optimal with respect to minimizing within-category variation and maximizing between-category variation.

Table 8.1 compares RACHS-1, the ABC Score, and the STS-EACTS Mortality Categories. Table 8.2 shows the application in the STS Congenital Heart Surgery Database of the STAT Congenital Heart Surgery Mortality Categories [198]. STS and EACTS have transitioned from the primary use of Aristotle and RACHS-1 to the primary use of the STAT Mortality Categories because of three reasons:

Table 8.1 Method of modeling procedures. Shows the results of comparing the STS–EACTS Categories (2009) to the RACHS-1 Categories and the Aristotle Basic Complexity Score using an independent validation sample of 27,700 operations performed in 2007 and 2008. In the subset of procedures for which STS–EACTS Category, RACHS-1 Category, and Aristotle Basic Complexity Score are defined, discrimination was highest for the STS–EACTS categories (C-index = 0.778), followed by RACHS-1 categories (C-index = 0.745), and Aristotle Basic Complexity scores (C-index = 0.687)
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Table 8.2 Shows the discharge mortality in an analysis of patients in the STS Congenital Heart Surgery Database who underwent surgery between January 1, 2005 and December 31, 2009, inclusive [198], stratified by STAT Mortality Categories (STS–EACTS Congenital Heart Surgery Mortality Categories)
Full size table
  1. 1.

    STAT Score was developed primarily based on objective data while RACHS-1 and Aristotle were developed primarily on expert opinion (Subjective probability)

  2. 2.

    STAT Score allows for classification of more operations than RACHS-1 or Aristotle

  3. 3.

    STAT Score has a higher c-statistic than RACHS-1 or Aristotle.

Meaningful evaluation and comparison of outcomes require consideration of both mortality and morbidity, but the latter is much harder to measure. The STAT Mortality Categories provide an empirically based tool for analyzing mortality associated with operations for congenital heart disease [150]. STS has developed the STAT Morbidity Categories [215] based on major postoperative complications and postoperative length of stay. Both major postoperative complications and postoperative length of stay were used because models that assume a perfect one to one relationship between postoperative complications and postoperative length of stay are not likely to fit the data well. Incorporation of both major postoperative complications and postoperative length of stay allows creation of a much more informative model. The STAT Morbidity Categories provide an empirically based tool for analyzing morbidity associated with operations for congenital heart disease [215].

Data Verification

Collaborative efforts involving EACTS and STS aim to enhance mechanisms to verify the completeness and accuracy of the data in the databases [21, 126]. A combination of three strategies may ultimately be required to allow for optimal verification of data:

  1. 1.

    Intrinsic data verification (designed to rectify inconsistencies of data and missing elements of data)

  2. 2.

    Site visits with “Source Data Verification” (in other words, verification of the data at the primary source of the data)

  3. 3.

    External verification of the data from independent databases or registries (such as governmental death registries)

Data quality in the STS Congenital Heart Surgery Database is evaluated through intrinsic data verification by Duke Clinical Research Institute (DCRI) (including identification and correction of missing/out of range values and inconsistencies across fields). DCRI is the data warehouse and analytic center of the STS Congenital Heart Surgery Database.

In addition to intrinsic data verification by DCRI, each year, approximately 10 % of participants are randomly selected for audits of their center, in accordance with their STS Congenital Heart Surgery Database Participation Agreement. The audit is designed to complement the internal quality controls, with an overall objective of maximizing the integrity of the data in the STS Congenital Heart Surgery Database by examining the accuracy, consistency, and completeness of the data. STS has selected Telligen to perform an independent, external audit of the STS Congenital Heart Surgery Database. As the state of Iowa’s Medicare Quality Improvement Organization (QIO), Telligen partners with health care professionals to assure high quality, cost effective health care. As a Quality Improvement Organization, Telligen is compliant with the Health Insurance Portability and Accountability Act of 1996 of the United States of America (HIPAA) and performs audits adhering to strict security policies. Additionally, an STS congenital heart surgeon volunteer leader participates in the audit.

In the STS Congenital Heart Surgery Database, the audit process includes:

  • Completion of the STS Data Collection Questionnaire and review of responses with the primary data contact, data manager, and/or other relevant personnel

  • Review of the data collection process and documentation to determine case eligibility for submittal to the STS Congenital Heart Surgery Database

  • Comparison of facility operative case logs with cases submitted to the STS Congenital Heart Surgery Database

  • Data abstraction (from original source documents) of congenital heart surgery records randomly selected by DCRI and all operative mortality cases for the preceding calendar year.

  • A summary conference with the surgeon representative, primary data contact, data manager, and/or other relevant personnel to discuss general trends in data collection and submission processes.

In 2013, the audit of the STS Congenital Heart Surgery Database included the following documentation of rates of completeness and accuracy for the specified fields of data:

  • Primary Diagnosis (Completeness = 100 %, Accuracy = 96.2 %),

  • Primary Procedure (Completeness = 100 %, Accuracy = 98.7 %),

  • Mortality Status at Hospital Discharge (Completeness = 100 %, Accuracy = 98.8 %)

In 2014, 11 Participants in the STS Congenital Heart Surgery Database will be audited.

Subspecialty Collaboration

Under the leadership of The MultiSocietal Database Committee for Pediatric and Congenital Heart Disease [110–112], further collaborative efforts are ongoing between congenital and pediatric cardiac surgeons and other subspecialties, including

  1. 1.

    Pediatric cardiac anesthesiologists, via The Congenital Cardiac Anesthesia Society [105, 119, 139, 207],

  2. 2.

    Pediatric cardiac intensivists, via The Pediatric Cardiac Intensive Care Society [190], and

  3. 3.

    Pediatric cardiologists, via the Joint Council on Congenital Heart Disease, the American College of Cardiology, and The Association for European Paediatric Cardiology [118].

Strategies have been developed to link together databases [109, 164, 189, 193, 194, 210, 219]. By linking together different databases, one can capitalize on the strengths and mitigate some of the weaknesses of these databases and therefore allow analyses not possible with either dataset alone. Linked databases have facilitated both comparative effectiveness research [193, 194, 219] and longitudinal follow-up [145, 146, 173, 214]. Under the leadership of The MultiSocietal Database Committee for Pediatric and Congenital Heart Disease [110–112], further collaborative efforts are ongoing between congenital and pediatric cardiac surgeons and other subspecialties.

The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease has held ten annual meetings, each lasting 1 or 2 days, in 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, and 2014. The 11th Multi-Societal Meeting has already been scheduled for 2015 in Prague, the Czech Republic:

  1. 1.

    The First Annual Meeting of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease. Chicago, Illinois, Chicago Hilton, Thursday August 25, 2005 and Friday August 26, 2005. (At the inception of this first meeting, the meeting was named the “VPS/STS/PCICS Combined Database Meeting”. VPS=The Virtual Pediatric Intensive Care Unit Systems, STS=The Society of Thoracic Surgeons, PCICS=The Pediatric Cardiac Intensive Care Society.)

  2. 2.

    The Second Annual Meeting of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease. Chicago, Illinois, Thursday August 17, 2006 and Friday, August 18, 2006.

  3. 3.

    The Third Annual Meeting of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease. Hotel George in Washington, DC, Thursday September 27, 2007 and Friday, September 28, 2007.

  4. 4.

    The Fourth Annual Meeting of The Multi- Societal Database Committee for Pediatric and Congenital Heart Disease. Omni Mount-Royal Hotel, Montreal, Canada, Saturday October 4, 2008 and Sunday October 5, 2008.

  5. 5.

    The Fifth Annual Meeting of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease of The Global Organization for Pediatric and Congenital Heart Disease: “The Transition from Outcomes Analysis to Quality Improvement”. The Emory Conference Center, Atlanta, Georgia, Wednesday September 16, 2009 and Thursday, September 17, 2009.

  6. 6.

    The Sixth Annual Meeting of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease of The Global Organization for Pediatric and Congenital Heart Disease: “Creating a Multidisciplinary Strategy for Improving the Quality of HealthCare Delivered to Patients with Pediatric and Congenital Heart Disease”. The Emory Conference Center, Atlanta, Georgia, Thursday, August 26, 2010 and Friday, August 27, 2010.

  7. 7.

    The Seventh Annual Meeting of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease: “The relationship between (1) Outcomes Analysis, (2) Quality Improvement, and (3) Patient Safety”. University of Cambridge, Cambridge, United Kingdom, Tuesday, September 20, 2011 and Wednesday, September 21, 2011.

  8. 8.

    The Eighth Annual Meeting of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease: “New Initiatives in Outcomes and Quality”. Chair: Jeffrey P. Jacobs, MD, Local Hosts: Robert Campbell, MD and Robert Vincent, MD. The Emory Conference Center, Atlanta, Georgia (404) 712–6000. Thursday, August 23, 2012 and Friday, August 24, 2012.

  9. 9.

    The Ninth Annual Meeting of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease: “Bridging the Gap from Outcomes to Quality”. Chair: Jeffrey P. Jacobs, Local Host: Shakeel Qureshi, President, The Association for European Paediatric and Congenital Cardiology, Meeting held at the 47th Annual Meeting of The Association for European Paediatric and Congenital Cardiology (AEPC), London, England, United Kingdom, Thursday, May 23, 2013.

  10. 10.

    The Tenth Annual Meeting of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease: “Dashboards for Pediatric and Congenital Cardiac Care”. Chair: Jeffrey P. Jacobs, MD, Local Hosts: Robert Campbell, MD and Robert Vincent, MD. The Emory Conference Center, Atlanta, Georgia (404) 712–6000. Thursday, September 4, 2014 and Friday, September 5, 2014.

  11. 11.

    The Eleventh Annual Meeting of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease: “Improving the quality of congenital cardiology healthcare by harmonizing international databases”. Chair: Jeffrey P. Jacobs, MD, Robert Vincent, MD, and Rodney Franklin, MD. Meeting held at the 49th Annual Meeting of The Association for European Paediatric and Congenital Cardiology (AEPC), Prague, the Czech Republic, Wednesday, May 20, 2015.

The various organizations and Societies whose members have participated in the meetings and activities of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease as well as the various participants themselves have previously been published [111], although the group continues to grow and involve multiple professional medical and nursing societies as well as multiple governmental and nongovernmental agencies. Some notable accomplishments of this multidisciplinary group are worth brief mention. At the first meeting of the Multi-Societal Database Committee, initial discussions took place about the possibility of linking together the various databases of the subspecialties of pediatric cardiac surgery, pediatric cardiology, pediatric cardiac anesthesia, and pediatric critical care. The Multi-Societal Database Committee rapidly realized that it would be essential to collaborate in multiple areas:

  1. 1.

    Use of a common language and nomenclature

  2. 2.

    Use of a database with an established uniform core dataset for collection of information

  3. 3.

    Incorporation of a mechanism of evaluating case complexity

  4. 4.

    Availability of a mechanism to assure verification of the completeness and accuracy of the data collected

  5. 5.

    Collaboration between medical and surgical subspecialties,

  6. 6.

    Standardization of protocols for life-long longitudinal follow-up.

Each of these six areas is discussed in detail in the following 530 page Supplement published in Cardiology in the Young by the Multi-Societal Database Committee for Pediatric and Congenital Heart Disease [110]. Initial discussions of the Multi-Societal Database Committee identified that it was essential for the various subspecialty databases to use identical nomenclature in order to allow them to communicate with each other with meaning. Various lists of terminology would need to be harmonized:

  1. 1.

    Diagnoses

  2. 2.

    Procedures

  3. 3.

    Complications

  4. 4.

    Preoperative Factors

The Multi-Societal Database Committee agreed to use The International Pediatric and Congenital Cardiac Code (IPCCC) (http://www.ipccc.net/) as the basis of communication. Mature and well developed Short Lists and Long Lists of Diagnoses and Procedures are available via The International Pediatric and Congenital Cardiac Code, and these diagnostic and procedural lists have been incorporated into the various subspecialty databases and harmonized.

At the second meeting of The Multi-Societal Database Committee, the diagnostic and procedural lists of nomenclature were harmonized across the multiple databases of pediatric cardiac surgery, pediatric cardiology, pediatric cardiac anesthesia, and pediatric critical care. These harmonized lists were based on the IPCCC. Because the diagnostic and procedural lists in The International Pediatric and Congenital Cardiac Code are matured and functional, the Multi-Societal Database Committee adopted these lists and harmonized them across their databases. The Multi-Societal Database Committee then elected to focus on developing a mature list of Complications and defining these complications [110–140].

At the third and fourth meeting of The Multi-Societal Database Committee, the topic of complications associated with the treatment of patients with pediatric and congenital cardiac disease was discussed in detail. The Multi-Societal Database Committee ultimately developed and published a Long List of Complications [110, 140] and a Short List of Complications [110–112], with consensus-based definitions provided in each List:

  1. 1.

    The Long List of Complications contains and defines 2,836 terms and is named: “The Long List of Complications of The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease”, with the abbreviated short name: “Multi-Societal Long List of Complications”. Although the act of navigating a list with 2,836 terms can initially seem quite daunting, it can become quite simple and enjoyable with the aid of computerized navigation tools designed to support the hierarchal structure of the list.

  2. 2.

    The Short List of Complications contains and defines 56 terms.

At the fifth meeting of The Multi-Societal Database Committee, the Committee transitioned from collaborative efforts related to databases to collaborative initiatives related to quality improvement. The sixth meeting of The Multi-Societal Database Committee focused on “Creating a Multidisciplinary Strategy for Improving the Quality of HealthCare Delivered to Patients with Pediatric and Congenital Heart Disease”. The first and second meetings were organized and hosted by the VPS Database, and the National Association of Children’s Hospitals and Related Institutions (NACHRI). The third and fourth meetings were organized and hosted by the Society of Thoracic Surgeons (STS), and the fifth, sixth, eighth, and tenth meetings were organized and hosted by Emory University. The seventh meeting was hosted the Pediatric Cardiac Intensive Care Society. The ninth meeting was hosted by The Association for European Paediatric and Congenital Cardiology (AEPC), and the AEPC will host the eleventh meeting. The Multi-Societal Database Committee for Pediatric and Congenital Heart Disease is a platform that facilitates the ability for databases in the domain of pediatric cardiac care to span conventional subspecialty and temporal boundaries.

Longitudinal Follow-Up

The transformation of the STS Database to a platform for longitudinal follow-up will ultimately result in higher quality of care for all cardiothoracic surgical patients by facilitating longitudinal comparative effectiveness research on a national level [127, 173, 184, 214]. Several potential strategies will allow longitudinal follow-up with the STS Database, including the development of clinical longitudinal follow-up modules within the STS Database itself, and linking the STS Database to other clinical registries, administrative databases, and national death registries:

  1. 1.

    Using probabilistic matching with shared indirect identifiers, the STS Database can be linked to administrative claims databases (such as the CMS Medicare Database [145, 146] and the Pediatric Health Information System (PHIS) database [109, 164, 189, 193, 194, 210, 219]) and become a valuable source of information about long-term mortality, rates of re-hospitalization, long-term morbidity, and cost [208].

  2. 2.

    Using deterministic matching with shared unique direct identifiers, the STS Database can be linked to national death registries like the Social Security Death Master File (SSDMF) and the National Death Index (NDI) in order to verify life-status over time [127, 173, 184, 214].

  3. 3.

    Through either probabilistic matching or deterministic matching [184], the STS Database can link to multiple other clinical registries, such as the National Cardiovascular Data Registry (NCDR) of the American College of Cardiology (ACC), in order to provide enhanced clinical follow-up.

  4. 4.

    The STS Database can develop clinical longitudinal follow-up modules of its own to provide detailed clinical follow-up [109, 127, 173, 184, 214].

Quality Assessment and Quality Improvement

The STS Database is increasingly used to document variation in outcomes [182, 198] and measure quality [179, 186]. Funnel plots may be used to demonstrate this variation in outcome and to facilitate the identification of centers that are outliers in performance (Fig. 8.6). Quality improvement initiatives can be initiated in “low performing centers” and best practices can be obtained from “high performing centers”.

Fig. 8.6
figure 6

In this graph, data about mortality is displayed as a funnel plot for STAT Category five operations [198]. The horizontal dashed line depicts aggregate STS mortality before discharge. Dashed lines depicting exact 95 % binomial prediction limits were overlaid to make a funnel plot. Squares represent the number of cases and mortality before discharge for individual STS Congenital Heart Surgery Database participants (centers). This analysis includes patients undergoing surgery during the 5 year analytic window of 2005 –2009, inclusive, and includes 70 STS centers in the STS Congenital Heart Surgery Database and 2,707 operations. Centers that were identified as outliers represented 18.6 % of participating centers (13 out of 60): 10 % (7 out of 70) were “high-performing outliers” and 8.6 % (6 out of 70) were “low-performing outliers”. Quality improvement initiatives can be initiated in “low performing centers” and best practices can be obtained from “high performing centers”. (STS-EACTS Congenital Heart Surgery Mortality Categories = STS-EACTS Mortality Categories = STAT Mortality Categories [150], STS The Society of Thoracic Surgeons, EACTS European Association for Cardio-Thoracic Surgery)

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STS has collaborated with the Congenital Heart Surgeons’ Society (CHSS) to develop and endorse metrics to assess the quality of care delivered to patients with pediatric and congenital cardiac disease [186]. Tables 8.3, 8.4, and 8.5 presents 21 “Quality Measures for Congenital and Pediatric Cardiac Surgery” that were developed and approved by the Society of Thoracic Surgeons (STS) and endorsed by the Congenital Heart Surgeons’ Society (CHSS). These Quality Measures are organized according to Donabedian’s Triad of Structure, Process, and Outcome [242]. It is hoped that these quality measures can aid in congenital and pediatric cardiac surgical quality assessment and quality improvement initiatives. These initiatives will take on added importance as the public reporting of cardiac surgery performance becomes more common [143, 176, 177].

Table 8.3 Quality measures for congenital and pediatric cardiac surgery
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Table 8.4 Definitions of quality measures for congenital and pediatric cardiac surgery
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Table 8.5 Consensus definitions of the morbidities
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Summary: Bridging the Gap Form Analysis of Outcomes to Improvement of Quality

Clinical registries represent a foundational tool in the following inter-related process:

  1. 1.

    Measuring the outcomes of medical and surgical practices,

  2. 2.

    Developing evidence for best medical and surgical practices,

  3. 3.

    Providing actionable feedback to clinicians, and

  4. 4.

    Improving the quality of care and outcomes.

Clinical registries are the best tool for measuring the outcomes of the processes of care [220, 221]. As described in this chapter, the ability to measure clinical outcomes properly requires using standardized clinical nomenclature, uniform standards for defining elements of data and collecting these data, strategies to adjust for the complexity of patients, techniques to verify the completeness and accuracy of data, and collaboration across medical and surgical subspecialties. All of these elements exist in the ideal clinical registry.

Clinical registries can be used as a platform for developing evidence for best medical practices and performing comparative effectiveness research. The NIH-funded linkage of the STS Congenital Heart Surgery Database to the Pediatric Health Information System (PHIS) Database exemplifies this approach [164, 189, 193, 194, 210, 219]. This linkage of clinical and administrative data facilitated comparative effectiveness research in the domains of perioperative methylprednisolone and outcome in neonates undergoing heart surgery [193] and antifibrinolytic medications in pediatric heart surgery [194]. Similarly, The NIH-funded ASCERT trial (American College of Cardiology Foundation—Society of Thoracic Surgeons Collaboration on the Comparative Effectiveness of Revascularization sTrategies trial) also used linked clinical and administrative data to compare surgical and transcatheter strategies of coronary revascularization [243, 244]. Although randomized trials have been considered by many to be the gold standard of comparative effectiveness research, recent efforts have examined the possibility of using a clinical registry as a platform for randomized trials [245, 246], potentially accomplishing the dual objectives of decreasing the cost of the trial and increasing the generalizability of the patients enrolled.

Clinical registries can provide actionable feedback to clinicians and therefore aid in initiatives to improve quality. Clinical registries can provide practitioners with accurate and timely feedback of their own outcomes and can benchmark these outcomes to regional, national, or even international aggregate data [182, 198, 247–249].

The ultimate goal of clinical registries is to improve quality of care and outcomes. Clinical registries have been used to create standardized measures of quality that have been endorsed by multiple professional medical societies and the National Quality Forum [186, 250]. Compliance with these measures and the public reporting of these measures should lead to improvements in the overall quality of care delivered to our patients [143, 176, 177].

Figure 8.7 is a Venn Diagram that demonstrates the close and overlapping relationships between the three domains of this textbook: Outcomes Analysis, Quality Improvement, and Patient Safety. These relationships compose the underlying theme of this textbook and are fundamental to improving the state of the art of pediatric and congenital cardiac care.

Fig. 8.7
figure 7

This Venn Diagram demonstrates the close and overlapping relationships between the three domains of this textbook: outcomes analysis, quality improvement, and patient care. These relationships compose the underlying theme of this textbook and are fundamental to improving the state of the art of pediatric and congenital cardiac care

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