Janelle Noel, M.S. KUMC Biostatistics Ph.D. Graduate Student

1. A Unique Summer Experience Without Traditional Course Work: Balancing an Internship and Additional Research Janelle Noel, M.S. KUMC Biostatistics Ph.D. Graduate Student

2. 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

3. Process of Obtaining an Internship

4. 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

5. Process of Obtaining an Internship: Whereshould you look for an internship?

6. 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

7. Process of Obtaining an Internship: Whereshould you look for an internship?

8. 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

9. 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

10. 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

11. 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

12. PRIMARY RESEARCH TEAM HOME

13. The Internship

14. 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.”

15. 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)

16. 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

17. Life as an Intern: Daily Schedule

18. Life as an Intern

19. 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

20. 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

21. Project I: AHRQ R21 Grant

22. 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

23. 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

24. 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

25. GRA Project

26. 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)

27. 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

28. 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

29. Null Scenarios • Fold change (FC)/ • Power scenarios

30. 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

31. Work-School-Life Balance

32. Work-School-Life Balance….Ha! Life Work School

33. Most Valuable Lessons Learned

34. 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

35. Bloopers What happens when you let two grown men decorate your office? Every office needs at least one running joke…

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

37. Questions