}

DS-practice page

Although one of the core duties of all infection preventionists (IP) is collection, analysis, and utilization of data, few IPs come into the position with basic statistical knowledge needed for those tasks. As such, concepts such as mean, median, mode, and p-value continually elude them and that deficiency hinders their functioning as an IP. (This position has been confirmed during the offerings of the EPI Analytics Learning Lab and the popularity of basic statistics presentations at Annual Conference, the Academy, and in Webinars.)
The current EPI Analytics Learning Lab does an excellent job of providing a quick overview of statistics, but its focus has always been (and should remain) on data presentation and application. The “Basic Statistics for Infection Preventionists” Learning Lab’s goal is to bridge the gap in knowledge.

Continuing Nursing Education Credits (CNEs) are a recognized method of quantifying participation in an organized continuing education experience under responsible sponsorship, capable direction, and qualified instruction. One contact hour is defined as one hour of time spent in an educational experience.

CEs: Attendees will be able to earn between 6-8 CNEs for this activity.

Download learning lab overview.

View the course registration form.

 

 

Your Module Schedule



Daniel Bronson-Lowe, PhD, CIC

Module 1: Basics and Descriptive stats

Monday, October 26, 2015
1:00pm - 2:00pm ET – 60 minute duration

Topics

  • Why we need statistics in infection prevention
  • Descriptive vs. inferential statistics
  • Quantitative vs. categorical data
  • Measures of central tendency
  • Measures of spread
  • Quartiles / percentiles

Objectives

After viewing the presentation and completing the related activities, the learner will be able to:

  • Explain the difference between descriptive and inferential statistics
  • Explain the difference between quantitative and categorical data
  • Define measures of central tendency and measures of spread

Methodology

The following instructional methodologies are used in this module:

  • Instructor presentation
  • Group discussion
  • Individual take-home activities



Daniel Bronson-Lowe, PhD, CIC

Module 2: Inferential stats, heavy on p-value, null vs alternative, two types of errors, statistical significance vs relevance

Monday, November 2, 2015
1:00pm - 2:00pm ET – 60 minute duration

Topics

  • Steps in statistical analysis (very brief)
  • Null vs alternative hypotheses
  • P-values, confidence intervals, level of significance, power, sample size
  • Type I and Type II error
  • Statistical significance vs. clinical relevance

Objectives

  • Differentiate between null and alternative hypotheses
  • Interpret p-values and confidence intervals
  • Explain the difference between statistical significance and clinical relevance

Methodology

The following instructional methodologies are used in this module:

  • Instructor presentation
  • Group discussion
  • Individual take-home activities



Daniel Bronson-Lowe, PhD, CIC

Module 3: Frequency and reliability, rates, ratios, proportions, SIRs

Monday, November 09, 2015
1:00pm - 2:00pm ET – 60 minute duration

Topics

  • Ratios, rates, and proportions (multiple examples of each)
  • Incidence vs. prevalence
  • Direct vs. indirect standardization
  • SIR calculation and interpretation
    o Including determination of statistical significance

Objectives

  • Define and interpret ratios, rates, and proportions
  • Differentiate between incidence and prevalence
  • Interpret standardized infection ratios (SIR)

Methodology

The following instructional methodologies are used in this module:

  • Instructor presentation
  • Group discussion
  • Individual take-home activities



Daniel Bronson-Lowe, PhD, CIC

Module 4: Sensitivity, Specificity

Monday, November 16, 2015
1:00pm - 2:00pm ET – 60 minute duration

Topics

  • Relative risk
    o Cohort studies
    o Determination of statistical significance
  • Odds ratios
    o Case-control studies
    o Determination of statistical significance
  • Sensitivity, specificity, positive predictive value, negative predictive value
    o Conditional probabilities vs. natural frequencies

Objectives

  • Interpret relative risks and odds ratios
  • Interpret sensitivity and specificity
  • Interpret positive and negative predictive values

Methodology

The following instructional methodologies are used in this module:

  • Instructor presentation
  • Group discussion
  • Individual take-home activities
  • Group de-brief

 

Why Should You Attend?

  • Progressively build skills on data use, display, analysis and communication
  • Integrate NHSN into a comprehensive approach to data management
  • Learn to apply data skills in wide variety of situations ranging from simple to complex
  • Enhance professional competency in the IP technical domain and prepare for board certification

*NEW- Certification Review Exercise to accompany each module.

 

Meet Our Clinical Advisor



Dan Bronson-Lowe, PhD, CIC, Senior Infection Preventionist, Carle Foundation Hospital, Urbana-Champaign, IL

Daniel Lowe is an infectious disease epidemiologist by training, a statistics teacher by necessity, and an infection preventionist by luck. He has worked as an infectious disease epidemiologist for the Arizona Department of Health Services, taught health data analysis at the University of Illinois at Urbana-Champaign, and currently serves on the infection prevention team at Carle Hospital and Physician Group. He is a member of both APIC and SHEA (Society for Healthcare Epidemiology of America). Lowe earned his doctorate and master’s in epidemiology and his bachelor’s in microbiology from the University of Arizona.

 

What to expect

Interested in enrolling? This is what you can expect

Everything in the Data Learning Lab will be done virtually, from listening to speakers to doing assignments. Each of the class’s six modules follow this pattern:

Pre-Work
Before each class, you will have a chance to get familiar with content through things like recommended readings and videos.

Virtual Class
Your week starts with a 90-minute Virtual-Instructor-Led class (see schedule below). The instructor will start class by looking at the previous week’s class and homework, then will talk about that week’s content.

Homework
Each week, you will have a homework assignment to let you apply concepts presented during the class. Assessments may include, but are not limited to, test questions, at-work projects, and videos.