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A Unique Summer Experience Without Traditional Course Work: Balancing an Internship and Additional Research. Janelle Noel, M.S. KUMC Biostatistics Ph.D. Graduate Student. Outline. Process of Obtaining an Internship The Internship Life as an Intern Daily Schedule Expectations

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A Unique Summer Experience Without Traditional Course Work: Balancing an Internship and Additional Research

Janelle Noel, M.S.

KUMC Biostatistics Ph.D. Graduate Student

outline
Outline
  • Process of Obtaining an Internship
  • The Internship
    • Life as an Intern
      • Daily Schedule
      • Expectations
    • Projects
  • GRA Project
  • Work-School-Life Balance
  • Most Valuable Lessons Learned
process of obtaining an internship where should you look for an internship
Process of Obtaining an Internship: Whereshould you look for an internship?
  • Watch for emails that go out from the department
  • American Statistical Association’s webpage
    • www.amstat.org
process of obtaining an internship where should you look for an internship2
Process of Obtaining an Internship: Whereshould you look for an internship?
  • Watch for emails that go out from the department
  • American Statistical Association’s webpage
    • www.amstat.org
  • Indeed, LinkedIn, and/or Career Builder
process of obtaining an internship where should you look for an internship4
Process of Obtaining an Internship: Whereshould you look for an internship?
  • Watch for emails that go out from the department
  • American Statistical Association’s webpage
    • www.amstat.org
  • Indeed, LinkedIn, and/or Career Builder
  • Look at websites from specific company
    • Research Triangle companies
    • Pharmaceutical companies: Novartis, Eli Lilly, Bayer, etc.
    • Hospital networks and other medical associations
process of obtaining an internship when should you look for an internship
Process of Obtaining an Internship: When should you look for an internship?
  • Don’t wait!
  • Announcements for summer internships come out as soon as November
    • Application deadlines are usually in late December or early January
process of obtaining an internship what should you have prepared
Process of Obtaining an Internship: Whatshould you have prepared?
  • Cover letter
    • General
    • Specific for each company
  • Résumé/ Curriculum vitae (C.V.)
  • Personal statement
  • Questions for future employer/company
  • Answers to common interview questions
slide11
Process of Obtaining an Internship: Once accepted, what steps do you need to take to make it a reality?

Step 1: Tell the necessary people

Step 2: Get a game plan!

  • Where will you live?
  • How will you get there?
  • Determine finances/budget
  • Create a timeline

Step 3: Organize your materials

Step 4: Continue to have open communication with your future boss/company until your start date

slide12

PRIMARY

RESEARCH

TEAM

HOME

the internship1
The Internship
  • The Children’s Hospital Association (CHA)
    • Legacy companies
      • Children Health Corporation of America (CHCA)
      • National Association of Children’s Hospitals and Related Institutions (NACHRI)

Two Campuses:

    • Overland Park, KS
    • Washington, D.C.

CEO: Mark Wietecha, M.S., M.B.A

Mission Statements: “We are committed to improving access to quality care, reducing costs and keeping the unique needs of children at the forefront of health care reform implementation.”

the internship2
The Internship

Title: Analyst Intern

Company Branch: Statistical Solutions

Research Team:

Jay Berry, M.D., M.P.H.

(Research Clinician/

Assistant Professor)

Matt Hall, Ph. D.

(Principal Biostatistician)

Troy Richardson, Ph. D.

(Biostatistician)

the internship overview
The Internship: Overview

Duration: 12 weeks

Day 1: Orientation

Week 1: Compliance, IT, Exploring datasets, and learning the ICD-9 coding system

Week 2: PI in-person visit

Week 3 :

Week 10:

Weeks 11/12: Documenting/Summarizing progress and verifying codes

programming, literature reviews, conference calls, weekly meetings, projects, learning their corporate culture, making caffeinated coffee, eating fruit & nuts, and introducing myself to 100+ people

project i ahrq r21 grant
Project I: AHRQ R21 Grant

Background:

  • Individuals living with multiple chronic conditions (MCC)
    • receive inadequate quality of health care
    • experience suboptimal health outcomes
  • Health care systems are poorly designed to provide high quality of care for children with multiple chronic conditions (CMCC) and their families.
  • Relevant to public health
    • rapidly advance our understanding of the U.S. population of CMCC
project i ahrq r21 grant1
Project I: AHRQ R21 Grant

Primary Aim:Adapt a publicly available, comprehensive diagnosis classification scheme developed by AHRQ to count the number of chronic conditions, name each chronic condition, and describe the combinations of chronic conditions endured for each CMCC.

Data:Healthcare Costs and Utilization Kid’s Inpatient Database 2009 (HCUP KID) and Medicaid data from Truven Health Analytics (2009-2012)

  • HCUP KID: 3.4 million individual records
  • Medicaid data: 8.6 billion records

Exclusion Criteria:Normal newborns and only one chronic condition

project i ahrq r21 grant3
Project I: AHRQ R21 Grant

My role:

  • Cleaning data
  • Sub-setting data
  • Presenting data findings and problems to research team
  • Conducting sub-analyses on healthcare cost and utilization
  • Building laying out framework for Classification and Regression Tree (CART) model
project ii side project
Project II: Side Project

Preliminary analysis

Objective:Determine if a trend exists year to year regarding the percentage of discharges and length of stays in children’s hospitals (CH) using two different definitions

Data: HCUP KID years 2000-2012

Method:Cochran—Armitage Trend Test

project iii new proposed projects
Project III: New Proposed Projects

Title: Prediction of Medical Expenditures (ME) in Children

Objective: To predict the expected medical expenditures and health care utilization (HCU) in medically complex children using CCC/CCI/CCS in future years.

Data: Medicaid data from Truven Health Analytics and

Exclusion Criteria: Records that contains missing values and patients 17 years old

Study Design/Method: Fit a two-stage regression model to predict ME and HCU in children.

Stage 1: Logistic Regression/Stage 2: Linear Regression

Potential Papers:

  • Use CCI to predict total payments for future years
  • Compare predictive ability of CCC vs. CCI vs. CCS
  • Using prior 2-3 years to predict future years—a longitudinal prediction study
gra project1
GRA Project

Two part genomics project

Part I: Determine differentially expressed (DE) genes found among the different DE analysis methods

-pre and post treatment

Part II: Assess

  • control of the type I error rateunder the null hypothesis assuming unpaired or paired measurements through a simulation study

2) impact of ignoring the paired design among samples (Summer ‘14)

gra project part i
GRA Project: Part I

Figure 1: Number of Differentially Expressed Genes (Statistical Framework)

Table 1: Number of Common Differentially Expressed When Methods Overlap

Figure 2: Number of Differentially Expressed Genes (Method’s Statistical Theory)

Paired Methods

Unpaired Methods

Bayesian Methods N=2609

Frequentist Methods N=4543

*Excludes EBseq from Venn Diagram

gra project part ii
GRA Project: Part II
  • Simulation study
    • Normal context
    • Varying
    • Null scenario
      • remain the same for each treatment group
    • Fold change (FC)/Power scenario
      • Different for each treatment group
slide29

Null Scenarios

  • Fold change (FC)/
  • Power scenarios
gra project part ii1
GRA Project: Part II
  • Simulation study
    • Normal context
    • Varying
    • Null scenario
      • remain the same for each treatment group
    • Fold change (FC)/Power scenario
      • Different for each treatment group
  • Future Work
    • Run scenarios in the Poisson and Negative Binomial contexts
      • Create a usable sandwich estimator for the lme4 package in R
      • Vary overdispersion in the NB context
      • Compare results
most valuable lessons learned1
Most Valuable Lessons Learned
  • Importance of programing skills
  • Government data is messy
  • Document, document, document
  • Don’t be afraid to ask
  • Importance of productive conference calls
  • Communication skills can always be improved
  • Awareness of professionalism
bloopers
Bloopers

What happens when you let two grown men decorate your office?

Every office needs at least one running joke…

acknowledgements
Acknowledgements
  • Drs. Brooke Fridley, Jo Wick, and Matt Mayo
  • Jackie Jorland
  • Drs. Matt Hall, Troy Richardson, Jay Berry
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