Using and Teaching Stata in Emergency Medicine Research Rotation

1
Using and Teaching Stata in Emergency Medicine
Research Rotation

• Muhammad
  Waseem, MD
• Research Director
• Emergency Medicine
• Lincoln Medical Mental Health Center
• Bronx, New York

2
Disclosure

• Financial disclosures None

3
Background

• Participation in scholarly activities is a
  requirement of an Emergency Medicine (EM)
  Residency Curriculum
• A research project is necessary for graduation of
  EM residents

4
Background

• In order to fulfill this requirement EM residents
  have a mandatory research rotation

5
Background

• ACGME fully accredited 3 year EM Residency
  Training Program
• 33 EM residents (11 / year)

6
EM Research Rotation

• Formulating a research question
• Basic research designs
• Protocol writing and submission to IRB
• Basic statistical concepts
• Data collection/entry and analysis

7
Background

• First step in data analysis is to organize the
  raw data into a format which can be used by Stata
• Stata is a general purpose statistical package
• Physicians versus Programmers

8
Background

• We believe that the research understanding of EM
  residents will be enhanced if they are provided
  with the basic knowledge of a statistical program
  prior to data collection and data entry
• The purpose of this training is to equip EM
  residents with the necessary knowledge and
  understanding that will help to improve data
  recording

9
Objective

• Does providing basic knowledge of a Statistical
  program (such as Stata) improve the accuracy of
  data recording and data entry?

10
Methods

• Design Observational
• Setting Emergency Department of an Urban
  Teaching Hospital
• Participants EM Residents

11
Methods

• Research Elective
• Two blocks of 14 days
• 1-2 per month (11 learning)

12
Methods

• EM Stata Manual describing basic operation of
  Stata created with version 10

13
Methods

• How does EM Stata manual differ from Stata help?

14
Methods

• How does EM Stata manual differ from Stata help?
• This manual was developed keeping in mind the
  needs of in-training EM Residents
• First time users
• EM residents may have some basic knowledge of
  statistics but little or no knowledge of Stata
• Emphasis on data entry and data import

15
Methods

• Teaches EM residents the essential skills for
  successful data entry and data import to Stata
• Purpose is to reduce the number of incorrect
  entries and make the data set usable to Stata
• Hands-on experience using Stata

16
Methods

• Strengths
• Tailored to the needs of a specific audience (EM
  residents)
• Discuss only simple and basic operation of Stata

17
Methods

• Weaknesses
• Tailored to the needs of a specific rotation (EM
  residents research elective)
• Does not teach residents detailed statistical
  analysis
• Does not discuss programming

18
Methods

• Keep it simple
• We utilize pull-down menus (rather than commands)
• No discussion on commands

19
(No Transcript)
20
Methods

• Getting started
• Stata screen
• 4 Windows, 8 Tabs

21
Methods

• 4 Windows
• Review
• Variables
• Results
• Command

22
(No Transcript)
23
Methods

• 8 Tabs
• File, Edit, Data, Graphics, Statistics, User,
  Window, and Help

24
(No Transcript)
25
Methods

• Basic commands with pull-down menus
• Describe and summarize data
• Tables of frequencies
• Tables of mean
• Data input and output
• Data Import
• Saving files

26
Methods

• Describe data
• Data editor
• Data browser

27
Data Sheets Prior to Introducing Stata
28
(No Transcript)
29
(No Transcript)
30
Data Sheets After Introducing Stata
31
(No Transcript)
32
(No Transcript)
33
(No Transcript)
34
Results

• Teaching basics of a statistical program (such as
  Stata) improves the accuracy of data recording
  and data entry

35
Conclusions

• Basic operation of Stata can be learned quickly
  by EM residents
• Teaching Stata to the EM residents may expand
  their research related knowledge
• Providing introduction of Stata prior to data
  entry improves accuracy of data recording and
  facilitates data analysis

36
Limitations

• Small sample
• Single center study
• Observational study not standardized

37
Implications

• Little effort before data entry can save
  significant time in data cleaning
• Teaching statistical program during research
  rotation makes it more practical and interactive