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Harnessing Louisiana Electronic Medical Records for ... · PDF fileHarnessing Louisiana Electronic Medical Records for Pediatric Obesity Research ... Obesity Toolkit ... Institute

Jul 22, 2018

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  • Harnessing Louisiana Electronic Medical Records for Pediatric Obesity Research

    Amanda E. Staiano, Ph.D., M.P.P.

    Pennington Biomedical Research CenterOctober 28, 2015

    Childhood Obesity and Public Health Conference 2015

  • Presentation Outline

    The Era of Digital Data

    What can we do with these data?

    Improve screening and treatment

    Identify high risk patients/groups

    Engage patients in healthcare

    What are the strengths and limitations?

  • What is an EMR?

  • HOW CAN WE USE THESE DATA?

    1. Improve screening and treatment

    2. Identify high risk patients/groups

    3. Engage patients in healthcare

  • 1. IMPROVE SCREENING AND

    TREATMENT OPTIONS

    Obesity Toolkit

    Access Health

    Louisiana

  • Louisiana Pediatric ObesityP

    edia

    tric

    Obesity P

    revale

    nce

    Year

    0

    5

    10

    15

    20

    25

    30

    35

    2005 2006 2007 2008 2009 2010 2011 2012 2013

    U.S.

    LA Health

    SBHCs

    HPFA

    Bogalusa

    RWJF F as in Fat 2012

  • http://www.pbrc.edu/obesitytoolkit/

  • Barlow et al. Pediatrics 2007;120:s164-92

  • Use of EMR Improves Clinical Care

    19% of physicians aware of recommendations, only 3% adhere to all of them (Kologatla & Adams, 2004)

    Barriers include (Rattay et al., 2009): low self-efficacy,

    inadequate tools/resources,

    lack knowledge/skills,

    lack of time,

    competing priorities,

    insufficient reimbursement, and

    lack of awareness of community resources.

    Kolagotla & Adams, Obes Res 2004;12(2):275-83

    Rattay et al., Pediatrics 2009;123:S100-7

  • In 740k pediatric visits, EMR decision tools (Coleman et al., 2012):

    BMI measurement: 66% to 94%

    Obesity diagnosis: 12% to 61%

    Counseling rates: 1% to 50%

    RCT: Decision alerts, counseling

    template, and diagnosis order set:

    Obesity diagnosis: 7% to 22%

    Weight-specific counseling: 15% to 27% (Tang et al., 2012)

    Physician & staff training needed (Coleman et al., 2012)

    Keehbauch et al., Clin Pediatr 2012;51(1):31-8

    Tang et al., JGIM 2012;27(8):933-9

    Coleman et al., J of Peds 2012;160(6):918-22

    Use of EMR Improves Clinical Care

  • Prevent, Identify, Treat Childhood Obesity

    Require BMI assessment; prompt if elevated

    Link to screenings; follow-up visits

    Online database of community resources

    Online counseling

    Monitor patients more frequently

  • Washington FQHC , Bogalusa

    Albert Cammon Middle School/St. Rose Elementary SBHC, St. Rose

    St. Charles FQHCs, Luling (2), Norco, Kenner

    Bonnabel High School SBHC, KennerJohn Ehret High School SBHC, MarreroJoshua Butler Elementary School SBHC, WestwegoRiverdale High School SBHC, JeffersonWest Jefferson High School SBHC, Harvey

    Belle Chasse FQHC, Belle Chasse

    Ruth Fertel/Tulane FQHC, New Orleans

    St. Bernard FQHC, Chalmette

    St. Tammany FQHCs, Slidell, Covington

    Warren Easton SBHC, New Orleans

    Partnership with Access Health Louisiana

  • 2. IDENTIFY HIGH RISK

    PATIENTS/GROUPS

    LSU Hospitals and Clinics

  • 0

    5

    10

    15

    20

    25

    0

    1

    2

    3

    4

    5

    6

    7

    8

    1958 61 64 67 70 73 76 79 82 85 88 91 94 97 00 03 06 09

    Nu

    mb

    er

    wit

    h D

    iab

    ete

    s (

    Millio

    ns)

    Perc

    en

    tag

    e w

    ith

    Dia

    bete

    s

    Year

    Percentage with Diabetes

    Number with Diabetes

    Number and Percentage of U.S. Population with Diagnosed Diabetes,

    19582010

    CDCs Division of Diabetes Translation. National Diabetes Surveillance System available at

    http://www.cdc.gov/diabetes/statistics

    Slides from Dr. Jackie Stephens

  • % of adults

    with diabetes

  • *Am. Diabetes Assn 2014, National Center for Chronic Disease Prevention 2010, Caregiving 2013.

    Louisianas Chronic Disease Burden

    These 3 diseases alone cost

    the state $10.6 billion/year.

  • Adult-Onset Diabetes?

    0.24 per 1000

    or 1 child in every 4000

    African Americans have 6x

    higher prevalence than Whites

  • LSU Hospitals & Clinics

    LSU Data Management Evaluation Database (DMED)

    Since 1990, 1.6 million unique patients

    (35% of Louisiana population)

    Under- and uninsured population

    46% free care,

    10% self-pay,

    20% Medicaid,

    14% Medicare,

    10% commercial insurance

  • LSU DMED

    Encounter Data

    Demographics

    Blood Pressure and

    Anthropometry

    Labs and Pathology

    Diagnoses Procedures

    Medications, Allergies,

    Immunizations

    Tobacco Use and Smoking

    Cessation

    n =

    1.6 mil

  • Characteristics of pediatric sample

    Average Diagnosis Age

    15.2 y for type 1 diabetes

    16.3 y for type 2 diabetes

    Unpublished data; In preparation

  • 3. ENGAGE PATIENTS

    IN THEIR OWN HEALTHCARE

    PROPEL

    &

    REACHNet

  • Identify patients that qualify

    Reports of patient health data during study enrollment

    PI: Peter Katzmarzyk, Ph.D.

    Test a 2-y obesity treatment program delivered

    in primary care setting to an underserved population

  • Research Action for Health Network

    REACHnet:Research Action for Health Network

    (Formerly known as the Louisiana Clinical Data Research Network)

    PI: Thomas Carton, Ph.D.

    Slides provided by

    Beth Nauman, MPH, PhD Research Director

    Louisiana Public Health Institute

  • Research Action for Health Network

    PCORnet

  • Research Action for Health Network

    An informatics and stakeholder engagement infrastructure for multi-site research in Louisiana and Texas

    Goal: To facilitate the efficient conduct of patient-centered comparative effectiveness research by establishing a data network containing clinical records for more than 1 million patients

    PARTNERS

    REACHnet

    http://www.stayhealthyla.org/http://www.stayhealthyla.org/http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&docid=k9qt0d6A9SAUqM&tbnid=63dJ8OiQgJ7LiM:&ved=0CAUQjRw&url=http://siliconbayounews.com/2011/08/11/pennington-biomedical-research-center-grabs-6-million-grant-for-research/&ei=5Y7hUrbPJYThqAG2yYB4&bvm=bv.59568121,d.aWM&psig=AFQjCNFI_OTU5iy4oax8RcJnEO8UcvdG4w&ust=1390600278099052http://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&docid=k9qt0d6A9SAUqM&tbnid=63dJ8OiQgJ7LiM:&ved=0CAUQjRw&url=http://siliconbayounews.com/2011/08/11/pennington-biomedical-research-center-grabs-6-million-grant-for-research/&ei=5Y7hUrbPJYThqAG2yYB4&bvm=bv.59568121,d.aWM&psig=AFQjCNFI_OTU5iy4oax8RcJnEO8UcvdG4w&ust=1390600278099052

  • Research Action for Health Network

    Common Data Model

  • WHAT ARE THE STRENGTHS AND

    LIMITATIONS OF DIGITAL DATA?

  • Strengths

    Large cohorts of chronic diseases and risk factors

    Cost effective

    Focus on ethnic minority groups and those at/near the poverty line

    Assessments actually conducted in clinical settings

    Can improve clinical diagnosis & treatment

  • Limitations

    Self-selected appointments

    Physician-selected assessments

    Retrospective data

    Limited validity and reliability

  • Concluding Thoughts

    "Evidence is the cornerstone of

    a high-performing healthcare

    system." - Institute of Medicine

  • Concluding Thoughts

    Glaeser et al., NBER 2014; Working Paper No. 20291

    "Evidence is the cornerstone of

    a high-performing healthcare

    system." - Institute of Medicine

  • Acknowledgements

    Our Lady of the Lake

    Childrens Hospital