Incorporating Data into Decision Making REBECCA LUTKENHAUS, - - PowerPoint PPT Presentation

incorporating data into
SMART_READER_LITE
LIVE PREVIEW

Incorporating Data into Decision Making REBECCA LUTKENHAUS, - - PowerPoint PPT Presentation

The Evidence S uggests: Incorporating Data into Decision Making REBECCA LUTKENHAUS, REFERENCE LIBRARIAN, DRAKE UNIVERSITY LAW LIBRARY MICHAEL ROBAK, ASSOCIATE DIRECTOR, UMKC LEON E. BLOCH LAW LIBRARY Where to begin Evidence Based


slide-1
SLIDE 1

The Evidence Suggests…: Incorporating Data into Decision Making

REBECCA LUTKENHAUS, REFERENCE LIBRARIAN, DRAKE UNIVERSITY LAW LIBRARY MICHAEL ROBAK, ASSOCIATE DIRECTOR, UMKC LEON E. BLOCH LAW LIBRARY

slide-2
SLIDE 2

Where to begin

 Evidence Based Practice “is an interdisciplinary

approach to clinical practice that has been gaining ground following its formal introduction in 1992.”

 From: http://en.wikipedia.org/wiki/Evidence-

based_practice

 It started in medicine as evidence-based medicine

(EBM) and spread to other fields such as… Library and Information Science

slide-3
SLIDE 3

Additional background

 “Most practices in evidence-based policy are based on

those arising from evidence-based medicine.”

 “In this parent discipline, evidence an data are (and

absolutely must be) distinguished from one another”

 “This is because EBM proponents claim that only

evidence (and not, say, data) must be used to ground healthcare decisions. And, fortunately for them, in their domain of practice, a very simple distinction is used and accepted.”

slide-4
SLIDE 4

Starting point

 What is the difference between  Evidence  Statistics  Data  FROM Evidence Based Medicine  “ Information about individuals is data. But once aggregated via

appropriate statistical work, and reported as the result of a trial, it is evidence. Put another way, a defining character of evidence in EBM is that it is compiled from many individuals. So data is token, evidence type.”

slide-5
SLIDE 5

The Hierarchy of Evidence Based Practice (EBP)

Underlying Data Application of Statistics Evidence Policy

slide-6
SLIDE 6

Why data matters

  • Leads to better decisions
  • Results in continuous improvement
  • Confirms accountability requirements have been

met

  • Conveys the library’s value to the organization
  • Prioritizes competing demands
  • Focuses effort on the most important functions
  • Need to maximize decreasing budgets
  • Increasing emphasis on the business aspect of legal

practice

slide-7
SLIDE 7

Evidence-based librarianship

“Promotes the collection, interpretation, and integration of valid, important and applicable user- reported, librarian-observed, and research-derived evidence.”

Andrew Booth, From EBM to EBL: Two Steps Forward or One Step Back?, MED. REFERENCE SERVICES Q., Fall 2002

slide-8
SLIDE 8

How EBL works

P = population or problem I = intervention C = comparison (if necessary) O = outcome P = among 2L and 3L students writing a seminar paper I = does research training from a librarian C = versus no training O = affect the quality of the references used in the paper?

Develop a focused, answerable question Prediction, intervention, exploration

slide-9
SLIDE 9

How EBL works

Systematic reviews Meta-analysis Cohort studies Surveys Case studies Levels of evidence

slide-10
SLIDE 10

Types of data

Quantitative – measurement tick marks on a sheet Qualitative – meaning READ scale

slide-11
SLIDE 11

Evaluation plan to gather data

Decide what you are evaluating (see table) Identify stakeholders Determine timeline Select performance indicators (SMART) Select methods and instruments

PETER BROPHY, MEASURING LIBRARY PERFORMANCE: PRINCIPLES AND TECHNIQUES (2006)

slide-12
SLIDE 12

What methods (e.g. surveys, focus groups) do you use to gather and analyze data?

slide-13
SLIDE 13

What software/tools do you use to gather and analyze data?

slide-14
SLIDE 14

LibAnalytics

DRAKE UNIVERSITY

slide-15
SLIDE 15
slide-16
SLIDE 16
slide-17
SLIDE 17
slide-18
SLIDE 18

Gimlet

UNIVERSITY OF MISSOURI – KANSAS CITY

slide-19
SLIDE 19
slide-20
SLIDE 20
slide-21
SLIDE 21
slide-22
SLIDE 22
slide-23
SLIDE 23
slide-24
SLIDE 24

What trends have you noticed in analyzing your data?

slide-25
SLIDE 25

Visualization

  • Summarize findings in less than a page
  • Focus on your key message
  • Identify audiences, and the key audience
  • Quantitative data: tables, charts, histograms
  • Qualitative data: explain process used to

interpret data

slide-26
SLIDE 26

How are you conveying your value and persuading stakeholders with your data?