Transcript Update In Obesity Assessment and Treatment

Underdiagnosis of Pediatric
Hypertension – An Example of the
Potential of Electronic Medical
Record Research for Clinical
Pediatricians
David C Kaelber, MD, PhD
Internal Medicine and Pediatrics Physician
National Library of Medicine Medical Informatics Fellow
Center for Information Technology Leadership (CITL)
Staff Physician
Children's Hospital Boston, Brigham and Women’s Hospital, Massachusetts
General Hospital, and Massachusetts General Hospital for Children
Disclosures
 I have no relevant financial relationships with
the manufacturers of any commercial
products and/or provider of commercial
services discussed in this CME activity.
 I do not intend to discuss an
unapproved/investigative use of a commercial
product/device in my presentation.
Background
Background
Blood
Pressure
Adult
Children
Normal
SBP ≤120 and/or DBP ≤80
SBP and/or DBP < 90% for gender, age,
and height
Prehypertensive
SBP >120 and ≤139 and/or
DBP >80 and ≤89
SBP and/or DBP ≥ 90% and < 95% for
gender, age, and height
Stage I HTN
SBP >139 and ≤159 and/or
DBP >89 and ≤99
SBP and/or DBP ≥ 95% and ≤ 99%
+5mmHg for gender, age, and height
Stage II HTN
SBP >159 and/or DBP >99
SBP and/or DBP > 99% +5mmHg for
gender, age, and height
Need 3 measurements for diagnosis of hypertension
(HTN) or prehypertension (preHTN).
2-5% of all children have hypertension.
Study Design
 Design: Cohort study.
 Setting: Outpatient clinics in a large, academic,
urban medical system in Northeast Ohio.
 Patients: 14187 children and adolescents age 318 years who were seen at least three times for
well-child care between June 1999 and
September 2006.
 Main Outcome Measures: Diagnosis of
hypertension or prehypertension documented in
the electronic medical record (EMR). Logistic
regression analysis was performed to identify
factors associated with a correct diagnosis.
EMR Data Collection

Basic Information

MR#

birth date

gender

race

primary care
physician

past medical history

past surgical history

family history

Visit information

visit date

visit site

BP reading(s)

height reading

weight reading

diagnosis code(s) (ICD9)

problem list code(s) (ICD9)

order(s)

billing code(s)
Study Results
4%
3%
HTN
Pre-HTN
Normal
93%
Study Results
HTN
Dx, 131,
26%
Un-Dx
Dx
Un-Dx, 376,
74%
Study Results – HTN factors
Logistic regression analysis of factors associated with
having a correct diagnosis of HTN
Variable
OR
95%CI
Age (1 year increase)
1.09
1.03-1.16
Height-for-Age Percentile (1% increase)
1.02
1.01-1.03
Weight-for-Age Percentile (1% increase)
1.00
0.98-1.01
Obesity-related diagnosis
2.61
1.49-4.55
Male Sex
1.15
0.73-1.80
African American Race
1.04
0.62-1.75
Hispanic/Latino Race
1.31
0.61-2.83
Family History of HTN
1.21
0.70-2.11
Number of Elevated Blood Pressures over 3 required
1.77
1.21-2.57
Stage 2 HTN
1.68
1.29-2.19
Task
EMR Study1
# of hours
Paper Chart Study2
Planning Meetings
30
30
IRB Preparation
10
10
Data Collection
5
5764
Data Processing
15
15
Data Analysis
30
30
Abstract
15
15
Manuscript
40
40
TOTAL
145
5909
Distribution of Task and # of hours to complete tasks.
1 – actual time for this EMR study
2 – estimated time for equivalent paper chart study (assumes 1 minute for
initial screen and 5 minutes to find and extract data)
Study Timeline
April
June
August
October
December
2007
2007
2007
2007
2007
Clinical
IRB
Approved
Observation
Study
Design and
Team
August
2008
PAS
Abstract
Submitted
Data
Obtained
and
Analyzed
ML Hanson, PW Gunn, and DC Kaelber.
Underdiagnosis of Hypertension in Children and
Adolescents. Journal of the American Medical
Association. 298(8):874-9. 2007.
1 3rd year medical school student, 1 4th year medical school student,
1 medical informatics fellow, ~150 hours, ~17 months, $0
Clinical Research Implications
(retrospective clinical research)
Characteristic
Old Paradigm
New Paradigm
Data
Separate Research
Database
Shared Research and
Clinic Database (EMR)
Time
1000+ hours
100+ hours
Money
100,000-1,000,000+
0-10,000+
People
Many
Few
Order of magnitude less time and money
with electronic medical records.
Conclusions
 Electronic medical records have the
potential to create a paradigm shift in
retrospective clinical research.
 This paradigm shift can make clinical
research much for accessible for clinical
pediatricians.
Questions??
Comments??
[email protected] or [email protected]