Background:The prevalence of moderate or complex (moderate-complex) congenital heart defects (CHDs) among adults is increasing due to improved survival, but many patients experience lapses in specialty care or their CHDs are undocumented in the medical system. There is, to date, no efficient approach to identify this population.Objective:To develop and assess the performance of a risk score to identify adults aged 20-60 years with undocumented specific moderate-complex CHDs from electronic health records (EHR).Methods:We used a case-control study (596 adults with specific moderate-complex CHDs and 2384 controls). We extracted age, race/ethnicity, electrocardiogram (EKG), and blood tests from routine outpatient visits (1/ 2009 through 12/201...
BACKGROUND Sudden cardiac death (SCD) is the main preventable cause of death in patients with adult ...
BACKGROUND: Risk scores for prediction of coronary heart disease (CHD) in older adults a...
[Objectives] To develop, calibrate, test and validate a logistic regression model for accurate risk ...
Background:Improved treatment of congenital heart defects (CHDs) has increased survival of persons w...
BackgroundBecause of advancements in care, there has been a decline in mortality from congenital hea...
BACKGROUND: Administrative data sets utilize billing codes for research and quality assessment. Prev...
AIMS: Adequate risk prediction can optimize the clinical management in adult congenital heart diseas...
Background: Sudden cardiac death (SCD) is the main preventable cause of death in patients with adult...
CONTEXT: In populations of older adults, prediction of coronary heart disease (CHD) events through t...
Introduction: The population of adults with congenital heart disease (ACHD) is rapidly expanding and...
International audienceBackground: The content of electronic medical records (EMRs) encompasses both ...
Background: Coronary artery disease (CAD) will increasingly determine outcome in the aging adult con...
BackgroundLittle population-based data exist on limitations and health-related quality of life (HRQo...
University of Minnesota Ph.D. dissertation. May 2013. Major: Health Informatics. Advisor:Professor S...
BACKGROUND: Data on patient-reported outcomes (PROs) in adults with congenital heart disease (CHD) a...
BACKGROUND Sudden cardiac death (SCD) is the main preventable cause of death in patients with adult ...
BACKGROUND: Risk scores for prediction of coronary heart disease (CHD) in older adults a...
[Objectives] To develop, calibrate, test and validate a logistic regression model for accurate risk ...
Background:Improved treatment of congenital heart defects (CHDs) has increased survival of persons w...
BackgroundBecause of advancements in care, there has been a decline in mortality from congenital hea...
BACKGROUND: Administrative data sets utilize billing codes for research and quality assessment. Prev...
AIMS: Adequate risk prediction can optimize the clinical management in adult congenital heart diseas...
Background: Sudden cardiac death (SCD) is the main preventable cause of death in patients with adult...
CONTEXT: In populations of older adults, prediction of coronary heart disease (CHD) events through t...
Introduction: The population of adults with congenital heart disease (ACHD) is rapidly expanding and...
International audienceBackground: The content of electronic medical records (EMRs) encompasses both ...
Background: Coronary artery disease (CAD) will increasingly determine outcome in the aging adult con...
BackgroundLittle population-based data exist on limitations and health-related quality of life (HRQo...
University of Minnesota Ph.D. dissertation. May 2013. Major: Health Informatics. Advisor:Professor S...
BACKGROUND: Data on patient-reported outcomes (PROs) in adults with congenital heart disease (CHD) a...
BACKGROUND Sudden cardiac death (SCD) is the main preventable cause of death in patients with adult ...
BACKGROUND: Risk scores for prediction of coronary heart disease (CHD) in older adults a...
[Objectives] To develop, calibrate, test and validate a logistic regression model for accurate risk ...