The Impact of Differential Case Ascertainment in Clinical Registry Versus Administrative Data on Assessment of Resource Utilization in Pediatric Heart Surgery

Positive Predictive Value of International Classification of Diseases, Ninth Revision, Clinical Modification, and International Classification of Diseases, Tenth Revision, Clinical Modification, Codes for Identification of Congenital Heart Defects

Background Administrative data permit analysis of large cohorts but rely on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM), and International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes that may not reflect true congenital heart defects (CHDs). Methods and Results CHDs in 1497 cases with at least 1 encounter between January 1, 2010 and December 31, 2019 in 2 health care systems, identified by at least 1 of 87 ICD-9-CM/ICD-10-CM CHD codes were validated through medical record review for the presence of CHD and CHD native anatomy. Interobserver and intraobserver reliability averaged >95%. Positive predictive value (PPV) of ICD-9-CM/ICD-10-CM codes for CHD was 68.1% (1020/1497) overall, 94.6% (123/130) for cases identified in both health care systems, 95.8% (249/260) for severe codes, 52.6% (370/703) for shunt codes, 75.9% (243/320) for valve codes, 73.5% (119/162) for shunt and valve codes, and 75.0% (39/52) for "other CHD" (7 ICD-9-CM/ICD-10-CM codes). PPV for cases with >1 unique CHD code was 85.4% (503/589) versus 56.3% (498/884) for 1 CHD code. Of cases with secundum atrial septal defect ICD-9-CM/ICD-10-CM codes 745.5/Q21.1 in isolation, PPV was 30.9% (123/398). Patent foramen ovale was present in 66.2% (316/477) of false positives. True positives had younger mean age at first encounter with a CHD code than false positives (22.4 versus 26.3 years; P=0.0017). Conclusions CHD ICD-9-CM/ICD-10-CM codes have modest PPV and may not represent true CHD cases. PPV was improved by selecting certain features, but most true cases did not have these characteristics. The development of algorithms to improve accuracy may improve accuracy of electronic health records for CHD surveillance.

Variation in hospital costs and resource utilisation after congenital heart surgery

BACKGROUND

Children undergoing cardiac surgery have overall improving survival, though they consume substantial resources. Nationwide inpatient cost estimates and costs at longitudinal follow-up are lacking.

METHODS

Retrospective cohort study of children <19 years of age admitted to Pediatric Health Information System administrative database with an International Classification of Diseases diagnosis code undergoing cardiac surgery. Patients were grouped into neonates (≤30 days of age), infants (31-365 days of age), and children (>1 year) at index procedure. Primary and secondary outcomes included hospital stay and hospital costs at index surgical admission and 1- and 5-year follow-up.

RESULTS

Of the 99,670 cohort patients, neonates comprised 27% and had the highest total hospital costs, though daily hospital costs were lower. Mortality declined (5.6% in 2004 versus 2.5% in 2015, p < 0.0001) while inpatient costs rose (5% increase/year, p < 0.0001). Neonates had greater index diagnosis complexity, greater inpatient costs, required the greatest ICU resources, pharmacotherapy, and respiratory therapy. We found no relationship between hospital surgical volume, mortality, and hospital costs. Neonates had higher cumulative hospital costs at 1- and 5-year follow-up compared to infants and children.

CONCLUSIONS

Inpatient hospital costs rose during the study period, driven primarily by longer stay. Neonates had greater complexity index diagnosis, required greater hospital resources, and have higher hospital costs at 1 and 5 years compared to older children. Surgical volume and in-hospital mortality were not associated with costs. Further analyses comprising merged clinical and administrative data are necessary to identify longer stay and cost drivers after paediatric cardiac surgery.

Nomenclature for Pediatric and Congenital Cardiac Care: Unification of Clinical and Administrative Nomenclature - The 2021 International Paediatric and Congenital Cardiac Code (IPCCC) and the Eleventh Revision of the International Classification of Diseases (ICD-11)

Substantial progress has been made in the standardization of nomenclature for paediatric and congenital cardiac care. In 1936, Maude Abbott published her Atlas of Congenital Cardiac Disease, which was the first formal attempt to classify congenital heart disease. The International Paediatric and Congenital Cardiac Code (IPCCC) is now utilized worldwide and has most recently become the paediatric and congenital cardiac component of the Eleventh Revision of the International Classification of Diseases (ICD-11). The most recent publication of the IPCCC was in 2017. This manuscript provides an updated 2021 version of the IPCCC. The International Society for Nomenclature of Paediatric and Congenital Heart Disease (ISNPCHD), in collaboration with the World Health Organization (WHO), developed the paediatric and congenital cardiac nomenclature that is now within the eleventh version of the International Classification of Diseases (ICD-11). This unification of IPCCC and ICD-11 is the IPCCC ICD-11 Nomenclature and is the first time that the clinical nomenclature for paediatric and congenital cardiac care and the administrative nomenclature for paediatric and congenital cardiac care are harmonized. The resultant congenital cardiac component of ICD-11 was increased from 29 congenital cardiac codes in ICD-9 and 73 congenital cardiac codes in ICD-10 to 318 codes submitted by ISNPCHD through 2018 for incorporation into ICD-11. After these 318 terms were incorporated into ICD-11 in 2018, the WHO ICD-11 team added an additional 49 terms, some of which are acceptable legacy terms from ICD-10, while others provide greater granularity than the ISNPCHD thought was originally acceptable. Thus, the total number of paediatric and congenital cardiac terms in ICD-11 is 367. In this manuscript, we describe and review the terminology, hierarchy, and definitions of the IPCCC ICD-11 Nomenclature. This article, therefore, presents a global system of nomenclature for paediatric and congenital cardiac care that unifies clinical and administrative nomenclature.The members of ISNPCHD realize that the nomenclature published in this manuscript will continue to evolve. The version of the IPCCC that was published in 2017 has evolved and changed, and it is now replaced by this 2021 version. In the future, ISNPCHD will again publish updated versions of IPCCC, as IPCCC continues to evolve.

Nomenclature for Pediatric and Congenital Cardiac Care: Unification of Clinical and Administrative Nomenclature - The 2021 International Paediatric and Congenital Cardiac Code (IPCCC) and the Eleventh Revision of the International Classification of Diseases (ICD-11)

Substantial progress has been made in the standardization of nomenclature for paediatric and congenital cardiac care. In 1936, Maude Abbott published her Atlas of Congenital Cardiac Disease, which was the first formal attempt to classify congenital heart disease. The International Paediatric and Congenital Cardiac Code (IPCCC) is now utilized worldwide and has most recently become the paediatric and congenital cardiac component of the Eleventh Revision of the International Classification of Diseases (ICD-11). The most recent publication of the IPCCC was in 2017. This manuscript provides an updated 2021 version of the IPCCC.The International Society for Nomenclature of Paediatric and Congenital Heart Disease (ISNPCHD), in collaboration with the World Health Organization (WHO), developed the paediatric and congenital cardiac nomenclature that is now within the eleventh version of the International Classification of Diseases (ICD-11). This unification of IPCCC and ICD-11 is the IPCCC ICD-11 Nomenclature and is the first time that the clinical nomenclature for paediatric and congenital cardiac care and the administrative nomenclature for paediatric and congenital cardiac care are harmonized. The resultant congenital cardiac component of ICD-11 was increased from 29 congenital cardiac codes in ICD-9 and 73 congenital cardiac codes in ICD-10 to 318 codes submitted by ISNPCHD through 2018 for incorporation into ICD-11. After these 318 terms were incorporated into ICD-11 in 2018, the WHO ICD-11 team added an additional 49 terms, some of which are acceptable legacy terms from ICD-10, while others provide greater granularity than the ISNPCHD thought was originally acceptable. Thus, the total number of paediatric and congenital cardiac terms in ICD-11 is 367. In this manuscript, we describe and review the terminology, hierarchy, and definitions of the IPCCC ICD-11 Nomenclature. This article, therefore, presents a global system of nomenclature for paediatric and congenital cardiac care that unifies clinical and administrative nomenclature.The members of ISNPCHD realize that the nomenclature published in this manuscript will continue to evolve. The version of the IPCCC that was published in 2017 has evolved and changed, and it is now replaced by this 2021 version. In the future, ISNPCHD will again publish updated versions of IPCCC, as IPCCC continues to evolve.

Need of informatics in designing interoperable clinical registries

Clinical registries are designed to collect information relating to a particular condition for research or quality improvement. Intuitively, informatics in the area of data management and extraction plays a central role in clinical registries. Due to various reasons such as lack of informatics awareness or expertise, there may be little informatics involvement in designing clinical registries. In this paper, we studied a clinical registry from two critical perspectives, data quality and interoperability, where informatics can play a role. We evaluated these two aspects of an existing registry, Gynecology Surgery Registry, by mapping data elements and value sets, used in the registry, to a standardized terminology, SNOMED-CT. The results showed that majority of the values are ad-hoc and only 6 of 91 procedures in the registry could be mapped to the SNOMED-CT. To tackle this issue, we assessed the feasibility of automated data abstraction process, by training machine learning classifiers, based on existing manually extracted data. These classifiers achieved a reasonable average F-measure of 0.94. We concluded that more informatics engagement is needed to improve the interoperability, reusability, and quality of the registry.

Identification of adults with congenital heart disease of moderate or great complexity from administrative data

INTRODUCTION

There is relatively sparse literature on the use of administrative datasets for research in patients with adult congenital heart disease (ACHD). The goal of this analysis is to examine the accuracy of administrative data for identifying patients with ACHD who died.

METHODS

A list of the International Classification of Diseases codes representing ACHD of moderate- or great-complexity was created. A search for these codes in the electronic health record of adults who received care in 2010-2016 was performed, and used state death records to identify patients who died during this period. Manual record review was completed to evaluate performance of this search strategy. Identified patients were also compared with a list of patients with moderate- or great-complexity ACHD known to have died.

RESULTS

About 134 patients were identified, of which 72 had moderate- or great-complexity ACHD confirmed by manual review, yielding a positive predictive value of 0.54 (95% CI 0.45, 0.62). Twenty six patients had a mild ACHD diagnosis. Thirty six patients had no identified ACHD on record review. Misidentifications were attributed to coding error for 19 patients (53%), and to acquired ventricular septal defects for 11 patients (31%). Diagnostic codes incorrect more than 50% of the time were those for congenitally corrected transposition, endocardial cushion defect, and hypoplastic left heart syndrome. Only 1 of 21 patients known to have died was not identified by the search, yielding a sensitivity of 0.95 (0.76, 0.99).

CONCLUSION

Use of administrative data to identify patients with ACHD of moderate or great complexity who have died had good sensitivity but suboptimal positive predictive value. Strategies to improve accuracy are needed. Administrative data is not ideal for identification of patients in this group, and manual record review is necessary to confirm these diagnoses.

Impact of postoperative complications on hospital costs following the Norwood operation

Introduction Patients undergoing the Norwood operation consume considerable healthcare resources; however, detailed information regarding factors impacting hospitalisation costs is lacking. We evaluated the association of postoperative complications with hospital costs.

METHODS

In the present study, we utilised a unique data set consisting of prospectively collected clinical data from the Pediatric Heart Network Single Ventricle Reconstruction trial linked at the patient level with cost data for 10 hospitals participating in the Children's Hospital Association Case Mix database during the trial period. The relationship between complications and cost was modelled using linear regression, accounting for the skewed distribution of cost, adjusting for within-centre clustering and baseline patient characteristics.

RESULTS

A total of 334 eligible Norwood records (97.5%) were matched between data sets. Overall, 82% suffered from at least one complication (median 2; with a range from 0 to 33). Those with complications had longer postoperative length of stay (25 versus 12 days, p<0.001), more total ventilator days (7 versus 5 days, p<0.001), and higher in-hospital mortality (17.6 versus 3.4%, p<0.006). Mean adjusted hospital cost in those with a complication was $190,689 (95% CI $111,344-$326,577) versus $120,584 (95% CI $69,246-$209,983) in those without complications (p=0.002). Costs increased with the number of complications (1-2 complications=$132,800 versus 3-4 complications=$182,353 versus ⩾5 complications=$309,372 [p<0.001]).

CONCLUSIONS

This merged data set of clinical trial and cost data demonstrated that postoperative complications are common following the Norwood operation and are associated with worse clinical outcomes and higher costs. Efforts to reduce complications in this population may lead to improved outcomes and cost savings.

Data integrity of the Pediatric Cardiac Critical Care Consortium (PC4) clinical registry

BACKGROUND

Clinical databases in congenital and paediatric cardiac care provide a foundation for quality improvement, research, policy evaluations and public reporting. Structured audits verifying data integrity allow database users to be confident in these endeavours. We report on the initial audit of the Pediatric Cardiac Critical Care Consortium (PC4) clinical registry. Materials and methods Participants reviewed the entire registry to determine key fields for audit, and defined major and minor discrepancies for the audited variables. In-person audits at the eight initial participating centres were conducted during a 12-month period. The data coordinating centre randomly selected intensive care encounters for review at each site. The audit consisted of source data verification and blinded chart abstraction, comparing findings by the auditors with those entered in the database. We also assessed completeness and timeliness of case submission. Quantitative evaluation of completeness, accuracy, and timeliness of case submission is reported.

RESULTS

We audited 434 encounters and 29,476 data fields. The aggregate overall accuracy was 99.1%, and the major discrepancy rate was 0.62%. Across hospitals, the overall accuracy ranged from 96.3 to 99.5%, and the major discrepancy rate ranged from 0.3 to 0.9%; seven of the eight hospitals submitted >90% of cases within 1 month of hospital discharge. There was no evidence for selective case omission.

CONCLUSIONS

Based on a rigorous audit process, data submitted to the PC4 clinical registry appear complete, accurate, and timely. The collaborative will maintain ongoing efforts to verify the integrity of the data to promote science that advances quality improvement efforts.

The Society of Thoracic Surgeons Congenital Heart Surgery Database: 2016 Update on Outcomes and Quality

The Society of Thoracic Surgeons Congenital Heart Surgery Database is the largest congenital and pediatric cardiac surgical clinical data registry in the world. It is the platform for all activities of The Society of Thoracic Surgeons related to the analysis of outcomes and the improvement of quality in this subspecialty. This article summarizes current aggregate national outcomes in congenital and pediatric cardiac surgery and reviews related activities in the areas of quality measurement, performance improvement, and transparency. The reported data about aggregate national outcomes are exemplified by an analysis of 10 benchmark operations performed from January 2011 to December 2014 and documenting overall discharge mortality (interquartile range among programs with more than 9 cases): off-bypass coarctation, 1.0% (0.0% to 0.9%); ventricular septal defect repair, 0.7% (0.0% to 1.1%); tetralogy of Fallot repair, 1.0% (0.0% to 1.7%); complete atrioventricular canal repair, 3.2% (0.0% to 6.5%); arterial switch operation, 2.7% (0.0% to 5.6%); arterial switch operation plus ventricular septal defect, 5.3% (0.0% to 6.7%); Glenn/hemiFontan, 2.1% (0.0% to 3.8%); Fontan operation, 1.4% (0.0% to 2.4%); truncus arteriosus repair, 9.6% (0.0 % to 11.8%); and Norwood procedure, 15.6% (10.0% to 21.4%).

How Suitable Are Registry Data for Recurrence Risk Calculations? Validation of Diagnoses on 1,593 Families With Congenital Heart Disease

Background:

Congenital heart disease (CHD) occurs in approximately 1% of all live births, and 3% to 8% of these have until now been considered familial cases, defined as the occurrence of two or more affected individuals in a family. The validity of CHD diagnoses in Danish administrative registry data has only been studied previously in highly selected patient populations. These studies identified high positive predictive values (PPVs) and recurrence risk ratios (RRRs—ratio between probabilities of CHD given family history of CHD and no family history). However, the RRR can be distorted if registry data are used indiscriminately. Here, we investigated the consequences of misclassifications for the RRR using validated diagnoses on Danish patients with familial CHD.

Methods:

Danish citizens are assigned a civil registration number (CPR number) at birth or immigration, which acts as a unique identifier in the Danish registries, thus enabling connection of information from several registries. Utilizing the CPR number, we identified Danish patients with familial CHD and reviewed each patient’s file. We compared diagnoses from the registries with those manually assigned, which enabled calculation of the PPVs of diagnoses in the Danish registries, and from this, we deduced the false discovery rate (FDR). To measure the consequences on the RRR, the FDR was applied to a simulated data set with true RRR values of 2 and 10.

Results:

We validated diagnoses of 2,442 patients from 1,593 families. Of these, 874 patients were misclassified corresponding to an FDR of 36%. Applying this FDR on the simulated data sets, we found that the RRR decreased from 2 and 10 to 1.4 and 5.1, respectively. Lastly, we estimated that 11% of all cases with CHD were familial.

Conclusion:

We found that approximately one of nine of all cases with CHD are familial, and we also found that 36% of individuals with CHD in administrative medical registries are misclassified, which distort the RRR in simulated scenarios.

The science of assessing the outcomes and improving the quality of the congenital and paediatric cardiac care

PURPOSE OF REVIEW

Although significant progress has been made in the care of patients with paediatric and congenital cardiac disease, optimization of outcomes remains a constant goal. This review article will discuss the latest advances in the science of assessing the outcomes and improving the quality of the congenital and paediatric cardiac care, and will also review some of the latest associated research.

RECENT FINDINGS

Important advances continue to be made in each of the following domains: standardized nomenclature; established uniform core dataset; evaluation of case complexity; verification of the completeness and accuracy of the data; collaboration between subspecialties; strategies for longitudinal follow-up; and incorporating quality improvement. In January 2015, the Society of Thoracic Surgeons Congenital Heart Surgery Database (STS-CHSD) will begin voluntary public reporting of programmatic congenital cardiac surgical outcomes using a new risk model that includes both procedural risk (as defined by the procedure itself and STAT Categories) and a number of patient-specific characteristics including age, weight, prior cardiothoracic operation, prematurity, chromosomal abnormalities, syndromes, noncardiac congenital anatomic abnormalities and preoperative factors. Clinical databases have been linked with administrative database to answer questions neither dataset can answer independently, providing new information about long-term mortality, rates of rehospitalization, long-term morbidity, comparative effectiveness of various treatments, and the cost of healthcare. Multiple research initiatives have recently been published using STS-CHSD.

SUMMARY

The science of assessing the outcomes and improving the quality of congenital and paediatric cardiac care continues to evolve. Recent advances will facilitate the continued evolution of a meaningful method of multiinstitutional outcomes analysis for congenital and paediatric cardiac surgery.

Quality-Cost Relationship in Congenital Heart Surgery

BACKGROUND

There is an increasing focus on optimizing health care quality and reducing costs. The care of children undergoing heart surgery requires significant investment of resources, and it remains unclear how costs of care relate to quality. We evaluated this relationship across a multicenter cohort.

METHODS

Clinical data from The Society of Thoracic Surgeons Database were merged with cost data from the Pediatric Health Information Systems Database for children undergoing heart surgery (2006 to 2010). Hospital-level costs were modeled using Bayesian hierarchical methods adjusting for case-mix, and hospitals were categorized into cost tertiles. The primary quality metric evaluated was in-hospital mortality.

RESULTS

Overall, 27 hospitals (30,670 patients) were included. Median adjusted cost per case was $82,360 and varied fivefold across hospitals, while median adjusted mortality was 3.4% and ranged from 2.4% to 5.0% across hospitals. Overall, hospitals in the lowest cost tertile had significantly lower adjusted mortality rates compared with the middle and high cost tertiles (2.5% vs 3.8% and 3.5%, respectively, both p < 0.001). When assessed at the individual hospital level, most (75%) but not all hospitals in the lowest cost tertile were also in the lowest mortality tertile. Similar relationships were seen across the spectrum of surgical complexity. Lower cost hospitals also had shorter length of stay and trends toward fewer major complications.

CONCLUSIONS

Lowest cost hospitals generally deliver the highest quality care for children undergoing heart surgery, although there is some variation in this relationship. This information is important in the design of initiatives aiming to optimize health care value in this population.