°Õ³ó±ðÌý±«±·°äÌý,Ìý, andÌýProgram for Precision Medicine in Health Care (PPMH) presented a seminar series in May 2023 that provided an introduction to working with electronic health care data. Each Wednesday from May 10 through May 31, 2023 featured a presentation, followed by Q&A on research projects with NC TraCS analysts.
Learning Objectives:
- Week 1: Understand the basics of how the US health care system generates data and how this data is stored in the EHR.Ìý
- Week 2: Describe the code sets used to record health care data.Ìý
- Week 3: Recognize the fundamental units of how health care data is organized in the EHR.ÌýÌý
- Week 4: Understand how to design a research question for clinical data. Identify resources at ºÚÁÏÍø that support clinical data research.Ìý
Intended Audience:
Graduate students, postdocs, faculty, and clinicians who are interested in research using clinical data from ºÚÁÏÍø’s EHR system and the Carolina Data Warehouse
Seminar Recordings and Slides:
May 10, 2023
Instructor: Peter Leese
Topics Covered:
- Overview of how EHR works and history of EHR as billing systemÌý
- How health care data is generatedÌý
- Types of data & documentation used in patient care vs. billingÌý
- Structured vs. Non-structured dataÌý
- EHR database schemas & OMOP vocabulary
May 17, 2023
Instructor: Emily Pfaff
Topics Covered:
- Clinical TerminologiesÌý
- Diagnoses & ICD codesÌý
- Medications & lab dataÌý
May 24, 2023
Instructors: Peter Leese & Emily Pfaff
Topics Covered:
- Patient encounters – inpatient versus outpatientÌý
- Bringing domains together: encounters and stuff that happens at the encountersÌý
- How slightly different queries can yield vastly different resultsÌý
May 31, 2023
Instructors: Mike Adams & Anna Jojic
Topics Covered:
- Elements and examples of a well-formed queryÌý
- Solicit analytical questions from participants. Instructor models how to write an analytical question in plain English and specify/define all nouns in the queryÌý
- How to build a robust query – how do you estimate costsÌý
- Dos and don’ts in clinical data researchÌý
- Where to look things upÌý
- Resources for getting startedÌý
- How to make the most of your time working with NC TraCS analystsÌý