Download presentation

Presentation is loading. Please wait.

Published byDiego Moss Modified over 3 years ago

1
Mellott & Associates LLC Statistics for the Healthcare Quality Professional Susan Mellott PhD, RN, CPHQ, FNAHQ

2
Mellott & Associates LLC Objectives Use basic statistical techniques to describe data and to evaluate data Use or coordinate the use of statistical process control components Use or Coordinate the use of process analysis tools to display data

3
Mellott & Associates LLC Mom Baseball Apple Pie Statistics

4
Mellott & Associates LLC What Type of Data? The type of data that you have controls what tools, statistics and display format are utilized Everything is driven from this

5
Mellott & Associates LLC Type of Data Category – Count Data Categories or groups Histogram Percentage Chi Squared Measured Data Time, Volume, Money, Scores Run Chart Control Chart Mean, Median, Mode, Range T-test

6
Mellott & Associates LLC Categorical Data Examples Men vs Women Age Ranges (0-30, 31-50, 51-70, 71+) DRGs Types of falls Types of injuries Diagnosis Complications

7
Mellott & Associates LLC Measured Data Examples Temperature LOS Average daily census Scores on a test Pre and Post Test scores Anything over time

8
Mellott & Associates LLC In Healthcare Quality Use more measured data than categorical data, but there is a place for each Use more Run and Control charts than Histograms

9
Mellott & Associates LLC And then there are other Problem Solving Tools Cause & effect diagram Pareto diagram Scatter diagram Regression analysis

10
Mellott & Associates LLC But First…… Some Basics

11
Mellott & Associates LLC Reliability and Validity Reliability – The ability to get the same answer time and time again if nothing changes Validity – To be sure you are counting or measuring what you intended to count or measure

12
Mellott & Associates LLC Reliability and Validity Must have reliability before you can have validity HINT: R comes before V in the alphabet

13
Mellott & Associates LLC Reliability Test / Retest reliability Inter-Rater reliability ***

14
Mellott & Associates LLC Validity Face Validity – Lowest level Criterion Validity *** – Based on criteria Construct Validity – Hardest to obtain

15
Mellott & Associates LLC Sampling How you pick your sample influences what you can do with your results – Can you generalize the findings outside of the sample you used – Are you confined to use your findings only in relation to the sample itself Probability vs Non-Probability – Usually use of combination of each type

16
Mellott & Associates LLC Probability Sampling You probably will be able to generalize your findings Simple Random – All items have an equal chance of being chosen Stratified Random – Creating 2 or more homogeneous groups and then randomly selecting items – Men vs Women Systemic Random – Every nth case

17
Mellott & Associates LLC Non-Probability Sampling You probably will not be able to generalize your findings Convenience – Using data readily available Quota – Set number of data sets Purposive – Demonstrate a desired characteristic – Expert sampling – Men vs Women

18
Mellott & Associates LLC Data Collection Must assure that measuring what you intend to measure – Pre-test your data collection tool! – Verify collection questions with requestor of the data Must assure that all data collectors collect the data from the same places and in the same manner

19
Mellott & Associates LLC Before Collect Data, Must: Know how you want to manipulate data; Know how you want to display data; Know how you want to report data; All of which is based on type of data!

20
Mellott & Associates LLC Categorical Data AKA: – Attribute, Qualitative, Nominal, Ordinal, Discrete Examples: – # of members, patients, births, procedures, occurrences, gender, ethnicity

21
Mellott & Associates LLC Categorical Data Usually Reported as: – % in each category, whole numbers Usually Displayed as: – Histogram, pie chart Usual statistical test of difference between groups: – Chi Squared

22
Mellott & Associates LLC Measured Data AKA: – Continuous, Variable, Quantitative Examples: – Age, height, weight, temperature, time, charges, LOS

23
Mellott & Associates LLC Measured Data Usually Reported as: – Mean, median, mode, minimum, maximum, percentiles, whole and fractional numbers Usually displayed as: – Run charts, control charts Usual statistical test of difference between groups: – T-test, or in special cases a Z-test

24
Mellott & Associates LLC Mean, Median, Mode Mean: – Average – Can be influenced by outliers/extreme values Median: – Middle of data – Best utilized when there are outliers Mode: – Most frequently occurring numbers

25
Mellott & Associates LLC Examples 2, 4, 6, 8, 10 – Mean: – Median: 2, 4, 6, 8, 100 – Mean: – Median:

26
Mellott & Associates LLC Example 2, 4, 6, 7, 8, 10 – Mean: – Median: 0, 0, 0, 0, 0, 7, 12, 26 – Mean: – Median:

27
Mellott & Associates LLC Examples 2, 4, 6, 8, 10 – Mode: 2, 3, 3, 4, 6, 8, 10 – Mode: 2, 3, 3, 4, 4, 4, 6, 8, 10 – Mode:

28
Mellott & Associates LLC STANDARD DEVIATION

29
Mellott & Associates LLC Statistical Differences between Groups Clinical differences occur before statistical differences Categorical data – Chi Square Measured data – T-test

30
Mellott & Associates LLC Chi-Squared test Similar to a t-test Get an X 2 value Then look that value up on a p-value table like a t-test score

31
Mellott & Associates LLC T-test Reported as a p score Ranges from 0 to and less shows statistical differences

32
Mellott & Associates LLC Histogram (Bar Chart) What is it: – A display of comparisons between different categories or groups When used: – To look at differences between categories or groups (non-statistical differences) What it will tell you: – What the amount of differences look like

33
Mellott & Associates LLC

34
Histogram vs Run Chart vs Control Chart Histogram – – only with categorical data – Best to display one to three points in time – If more than three points in time, better to use run chart – Much more effective than a pie chart

35
Mellott & Associates LLC Run Chart (Line Graph) What is it: – A line graph display of performance changes over time When used: – To look at data over time What it will tell you: – What is baseline performance? – Amount and type of variation in a process? – Is process changing over time? – Is change an improvement?

36
Mellott & Associates LLC Histogram vs Run Chart vs Control Chart Run Chart – – Categorical data over time – Sequential Data points – Display comparison between years, hospital units, stratification of data – Prior to having enough data for Control Chart

37
Mellott & Associates LLC Control Chart (Line Graph) What is it: – A line graph display that compares actual performance to the mean and includes upper and lower control limits When used: – To display normal variations and out-of-control variations What it will tell you: – Common cause or special cause variation

38
Mellott & Associates LLC Control Chart Conceptually – Run chart with standard deviation curve placed on its side

39
Mellott & Associates LLC Control Charts

40
Mellott & Associates LLC

41

42

43

44

45

46
Regression Analysis Simple Regression – How one variable affects another variable – Example: number of calories eaten vs weight gain Multiple Regression – How multiple variables affect another variable – Factors related to compliance with medication regime

47
Mellott & Associates LLC Regression Analysis Scatter Diagram Pictorial representation of a simple regression – Positive Relationship Data goes upward in an oval shape – Negative Relationship Data goes downward in an oval shape – No relationship Data neither goes upward nor downward

48
Mellott & Associates LLC Positive Correlation

49
Mellott & Associates LLC Negative Correlation

50
Mellott & Associates LLC No Relationship or Correlation

51
Mellott & Associates LLC Multiple Regression in Health Care Quality Many examples where multiple regression could be an important tool: Factors related to compliance with medication regime Factors related to infections Factors related to high cholesterol Factors related to flexibility & strength

52
Mellott & Associates LLC Multiple Regression Pareto diagram Cause & Effect diagram

53
Mellott & Associates LLC Pareto Diagram What is it: – Pictorial representation similar to multiple regression When used: – When you want to determine where to start to get the biggest bang for your buck What it will tell you: – Where you should start in your improvement efforts

54
Mellott & Associates LLC

55

56

57
Cause & Effect Diagram What is it: – Pictorial representation similar to multiple regression When used: – When you want to determine where to start to get the biggest bang for your buck What it will tell you: – Where you should start in your improvement efforts

58
Mellott & Associates LLC Cause & Effect Use when bad things happen to determine how it happened Use when want Good results to determine what you need to do to get those results

59
Mellott & Associates LLC Cause & Effect Diagram Effect Cause

60
Mellott & Associates LLC Isolation Shallow Staffing Limited Access to Specialists Master Calendar Speed of Change Mentor Program Medical Records Soldier Assistance Board Admin CBO Info Technology Library Empowered Staff Clinical CBO Education Program CME OPD NCOPD SGTs Time Life Quality Improvement Showplace of Medical Readiness World Class Service ProfessionalExcellence OasisofCare Focus Community In-processing Lack of Measurement Resources Time Community Wellness PAT Wellness Focus Info Technology Soldier Assist Board Awards Program AMMED Council FSG Youth Summer Turnover Measurement NTC Surgeon Leadership MASCAL/EPP Info Technology NCO Corps Management Orientation Access Info Flow Info Technology Turnover Team Work Staffing Restraints Committed Staff EC Issues Customer Focus Lack of Measurement MC/CS Division Ambulatory Care Center Commitment to Vision DRETS PT Test FSG © M. Ellicott

61
Mellott & Associates LLC Summary You first need to know what kind of data you are working with Then you have to know the types of tools and statistics you can use with that kind of data Then you design the data collection and plan the analysis of that data

Similar presentations

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google