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# Hypothesis Testing Fundamentals

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### Hypothesis Testing Fundamentals

1. 1. HealthCare Quality Improvement Solutions© 2012 by HealthCare Quality Improvement Solutions, LLC
2. 2. • What is hypothesis testing?  A quantitative method for answering questions and determining whether potential factors significantly effect process performance 2© 2012 by HealthCare Quality Improvement Solutions, LLC
3. 3. • Primary purpose from a quality improvement perspective:  Determine whether the outcome of interest is produced by a similar or dissimilar process 3© 2012 by HealthCare Quality Improvement Solutions, LLC
4. 4. Hospital Hospital Potential Performance Performance Factors Discharge Discharge Rx ACEI 75% Rx ACEI 75%Physician Similar Processes Dissimilar Processes 72% 95% 75% 71% 77% 60% P-Value 0.567 P-Value 0.001 4© 2012 by HealthCare Quality Improvement Solutions, LLC
5. 5. Similar Processes Dissimilar Processes • Critical few factors will • Critical few factors will not be identified be identified • Redesign the process • Focus quality improvement on the critical few factors 5© 2012 by HealthCare Quality Improvement Solutions, LLC
6. 6. • Question to be answered:  Is the defendant innocent or guilty? • The defendant is presumed innocent until proven guilty  In hypothesis testing this is known as the null hypothesis and is denoted H0  H0: Defendant is innocent • The plaintiff asserts that the defendant is guilty  In hypothesis testing this is known as the alternate hypothesis and is denoted HA  HA: Defendant is guilty 6© 2012 by HealthCare Quality Improvement Solutions, LLC
7. 7. • Potential factor:  Arrival day of week • Question:  Is there a significant difference in Pneumonia Antibiotic Timing (Median) between patients that arrive on a Weekday vs. Weekend? • Hypotheses:  H0: Weekday Median = Weekend Median  The antibiotic administration process is similar for weekdays and weekend – Arrival day of week does not significantly effect Pneumonia Antibiotic Timing  HA: Weekday Median Weekend Median  The antibiotic administration process is dissimilar for weekdays and weekend – Arrival day of week does significantly effect Pneumonia Antibiotic Timing and is among the Critical Few Factors 7© 2012 by HealthCare Quality Improvement Solutions, LLC
8. 8. • The null hypothesis H0:  Asserts there is no difference among factors • The alternate hypothesis HA:  Asserts that there is a difference among factors 8© 2012 by HealthCare Quality Improvement Solutions, LLC
9. 9. Legal Process • The legal process is not perfect Truth Innocent Guilty  Innocent defendants can be found guilty by the jury Jury Innocent Correct Incorrect  In hypothesis testing this is Decision Guilty Incorrect Correct known as a Type I Error – Rejecting the null Data Analysis hypothesis when it is true  Guilty defendants can be Actual State found innocent by the jury H0 True H0 False  In hypothesis testing this is Accept H0 Correct Type II known as a Type II Error Error - Decision – Accepting the null Reject H0 Type I Correct hypothesis when it is false Error -© 2012 by HealthCare Quality Improvement Solutions, LLC 9
10. 10. • The P-Value is the chance of making a Type I Error if H0 is rejected • Decision Criteria:  If the P-Value is less than or equal to - reject H0  If the P-Value is greater than - accept H0 10© 2012 by HealthCare Quality Improvement Solutions, LLC
11. 11. • Let’s return to the Pneumonia Antibiotic Timing question:  Is there a significant difference in Pneumonia Antibiotic Timing (Median) between patients that arrive on a Weekday vs. Weekend? • Hypotheses:  H0: Weekday Median = Weekend Median  HA: Weekday Median Weekend Median • Level of Significance ( ) – also referred to as alpha  0.05 11© 2012 by HealthCare Quality Improvement Solutions, LLC
12. 12. • Let’s return to the Pneumonia Antibiotic Timing question:  Is there a significant difference in Pneumonia Antibiotic Timing (Median) between patients that arrive on a Weekday vs. Weekend? Yes • Hypotheses:  H0: Weekday Median = Weekend Median  HA: Weekday Median Weekend Median • Level of Significance  0.05 P-Value 12© 2012 by HealthCare Quality Improvement Solutions, LLC
13. 13. P-Value • Investigate why it takes longer on the weekend to deliver the initial antibiotic. 13© 2012 by HealthCare Quality Improvement Solutions, LLC
14. 14. • When H0 is rejected, the hypothesis test is considered statistically significant at the selected level • It indicates that the sample measurement is unlikely if the null hypothesis is true • QI Perspective:  The sample measurements are likely being generated by dissimilar processes  The factor is a critical factor effecting performance 14© 2012 by HealthCare Quality Improvement Solutions, LLC
15. 15. Hospital Hospital Potential Performance Performance Factors Discharge Discharge Rx ACEI 75% Rx ACEI 75% Physician Similar Processes Dissimilar Processes 72% 95% 75% 71% 77% 60% P-Value 0.567 P-Value 0.001 15© 2012 by HealthCare Quality Improvement Solutions, LLC
16. 16. HealthCare Quality Improvement Solutions Robert Sutter Contact Information Website: https://sites.google.com/site/robertsutterrnmbamha/© 2012 by HealthCare Quality Improvement Solutions, LLC
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