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Databases for assessing the outcomes of the treatment of patients with congenital and paediatric cardiac disease – the perspective of critical care

Published online by Cambridge University Press:  01 December 2008

Joan M. LaRovere*
Affiliation:
Department of Paediatric Intensive Care, The Royal Brompton Hospital, London, United Kingdom
Howard E. Jeffries
Affiliation:
Division of Critical Care, Seattle Children’s Hospital, Seattle, Washington, United States of America
Ramesh C. Sachdeva
Affiliation:
National Outcomes Center, United States of America Department of Critical Care, Children’s Hospital of Wisconsin, Milwaukee, Wisconsin, United States of America
Thomas B. Rice
Affiliation:
Department of Critical Care, Children’s Hospital of Wisconsin, Milwaukee, Wisconsin, United States of America
Randall C. Wetzel
Affiliation:
Critical Care Medicine, Children’s Hospital Los Angeles, Los Angeles, California, United States of America
David S. Cooper
Affiliation:
The Congenital Heart Institute of Florida (CHIF), Division of Critical Care, All Children’s Hospital and Children’s Hospital of Tampa, University of South Florida College of Medicine, Florida Pediatric Associates, Saint Petersburg and Tampa, Florida, United States of America
Geoffrey L. Bird
Affiliation:
Critical Care Medicine, Cardiac Centre, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America
Nancy S. Ghanayem
Affiliation:
Department of Critical Care, Children’s Hospital of Wisconsin, Milwaukee, Wisconsin, United States of America
Paul A. Checchia
Affiliation:
Critical Care Medicine, St Louis Children’s Hospital; St. Louis, Missouri, United States of America
Anthony C. Chang
Affiliation:
Heart Institute, Children’s Hospital of Orange County, Orange County, California, United States of America
David L. Wessel
Affiliation:
Critical Care Medicine, Children’s Hospital National Medical Center, Washington DC, United States of America
*
Correspondence to: Dr Joan M LaRovere, Paediatric Intensive Care Unit, The Royal Brompton Hospital, Sydney Street, London, SW3 6NP, United Kingdom. Tel: +44 (0)207 351 8546; Fax: +44 (0)207 351 8379; E-mail: j.larovere@rbht.nhs.uk

Abstract

The development of databases to track the outcomes of children with cardiovascular disease has been ongoing for much of the last two decades, paralleled by the rise of databases in the intensive care unit. While the breadth of data available in national, regional and local databases has grown exponentially, the ability to identify meaningful measurements of outcomes for patients with cardiovascular disease is still in its early stages.

In the United States of America, the Virtual Pediatric Intensive Care Unit Performance System (VPS) is a clinically based database system for the paediatric intensive care unit that provides standardized high quality, comparative data to its participants [https://portal.myvps.org/]. All participants collect information on multiple parameters: (1) patients and their stay in the hospital, (2) diagnoses, (3) interventions, (4) discharge, (5) various measures of outcome, (6) organ donation, and (7) paediatric severity of illness scores. Because of the standards of quality within the database, through customizable interfaces, the database can also be used for several applications: (1) administrative purposes, such as assessing the utilization of resources and strategic planning, (2) multi-institutional research studies, and (3) additional internal projects of quality improvement or research.

In the United Kingdom, The Paediatric Intensive Care Audit Network is a database established in 2002 to record details of the treatment of all critically ill children in paediatric intensive care units of the National Health Service in England, Wales and Scotland. The Paediatric Intensive Care Audit Network was designed to develop and maintain a secure and confidential high quality clinical database of pediatric intensive care activity in order to meet the following objectives: (1) identify best clinical practice, (2) monitor supply and demand, (3) monitor and review outcomes of treatment episodes, (4) facilitate strategic healthcare planning, (5) quantify resource requirements, and (6) study the epidemiology of critical illness in children.

Two distinct physiologic risk adjustment methodologies are the Pediatric Risk of Mortality Scoring System (PRISM), and the Paediatric Index of Mortality Scoring System 2 (PIM 2). Both Pediatric Risk of Mortality (PRISM 2) and Pediatric Risk of Mortality (PRISM 3) are comprised of clinical variables that include physiological and laboratory measurements that are weighted on a logistic scale. The raw Pediatric Risk of Mortality (PRISM) score provides quantitative measures of severity of illness. The Pediatric Risk of Mortality (PRISM) score when used in a logistic regression model provides a probability of the predicted risk of mortality. This predicted risk of mortality can then be used along with the rates of observed mortality to provide a quantitative measurement of the Standardized Mortality Ratio (SMR). Similar to the Pediatric Risk of Mortality (PRISM) scoring system, the Paediatric Index of Mortality (PIM) score is comprised of physiological and laboratory values and provides a quantitative measurement to estimate the probability of death using a logistic regression model.

The primary use of national and international databases of patients with congenital cardiac disease should be to improve the quality of care for these patients. The utilization of common nomenclature and datasets by the various regional subspecialty databases will facilitate the eventual linking of these databases and the creation of a comprehensive database that spans conventional geographic and subspecialty boundaries.

Type
Original Article
Copyright
Copyright © Cambridge University Press 2008

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Footnotes

*

These authors contributed equally to this work.

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