Literature DB >> 19063783

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

Joan M LaRovere1, Howard E Jeffries, Ramesh C Sachdeva, Thomas B Rice, Randall C Wetzel, David S Cooper, Geoffrey L Bird, Nancy S Ghanayem, Paul A Checchia, Anthony C Chang, David L Wessel.   

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.

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Year:  2008        PMID: 19063783     DOI: 10.1017/S1047951108002886

Source DB:  PubMed          Journal:  Cardiol Young        ISSN: 1047-9511            Impact factor:   1.093


  9 in total

1.  Low near infrared spectroscopic somatic oxygen saturation at admission is associated with need for lifesaving interventions among unplanned admissions to the pediatric intensive care unit.

Authors:  Binod Balakrishnan; Mahua Dasgupta; Kim Gajewski; Raymond G Hoffmann; Pippa M Simpson; Peter L Havens; Sheila J Hanson
Journal:  J Clin Monit Comput       Date:  2017-03-03       Impact factor: 2.502

2.  Intracranial bleeding due to vitamin K deficiency: advantages of using a pediatric intensive care registry.

Authors:  Désirée Y Visser; Nicolaas J Jansen; Marloes M Ijland; Tom J de Koning; Peter M van Hasselt
Journal:  Intensive Care Med       Date:  2011-03-11       Impact factor: 17.440

3.  The factors associated with high-quality communication for critically ill children.

Authors:  Jennifer K Walter; Brian D Benneyworth; Michelle Housey; Matthew M Davis
Journal:  Pediatrics       Date:  2013-03       Impact factor: 7.124

4.  Opportunities and challenges in linking information across databases in pediatric cardiovascular medicine.

Authors:  Sara K Pasqual; Jennifer S Li; Marshall L Jacobs; Samir S Shah; Jeffrey P Jacobs
Journal:  Prog Pediatr Cardiol       Date:  2012-01

5.  International comparison of the performance of the paediatric index of mortality (PIM) 2 score in two national data sets.

Authors:  Stéphane Leteurtre; Bruno Grandbastien; Francis Leclerc; Roger Parslow
Journal:  Intensive Care Med       Date:  2012-05-09       Impact factor: 17.440

6.  How do we define success in pediatric cardiac care?

Authors:  Shyam S Kothari
Journal:  Ann Pediatr Cardiol       Date:  2011-07

Review 7.  Existing data analysis in pediatric critical care research.

Authors:  Tellen D Bennett; Michael C Spaeder; Renée I Matos; R Scott Watson; Katri V Typpo; Robinder G Khemani; Sheri Crow; Brian D Benneyworth; Ravi R Thiagarajan; J Michael Dean; Barry P Markovitz
Journal:  Front Pediatr       Date:  2014-07-29       Impact factor: 3.418

8.  Enhance quality care performance: Determination of the variables for establishing a common database in French paediatric critical care units.

Authors:  Morgan Recher; Caroline Bertrac; Camille Guillot; Jean Benoit Baudelet; Yasemin Karaca-Altintas; Hervé Hubert; Francis Leclerc; Stéphane Leteurtre
Journal:  J Eval Clin Pract       Date:  2018-07-10       Impact factor: 2.431

9.  Public health science agenda for congenital heart defects: report from a Centers for Disease Control and Prevention experts meeting.

Authors:  Matthew E Oster; Tiffany Riehle-Colarusso; Regina M Simeone; Michelle Gurvitz; Jonathan R Kaltman; Michael McConnell; Geoffrey L Rosenthal; Margaret A Honein
Journal:  J Am Heart Assoc       Date:  2013-08-28       Impact factor: 5.501

  9 in total

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