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Data Collection Options For When the Quality Measures Are Not Available?

Data Collection Options For When the Quality Measures Are Not Available?. MetaStar Patient Safety Programs for Pressure Ulcer Reduction and Prevention and Physical Restraint Elimination Nathan Williams October 19, 2010. Objectives. Using data to your advantage A Statistical Primer

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Data Collection Options For When the Quality Measures Are Not Available?

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  1. Data Collection Options For When the Quality Measures Are Not Available? MetaStar Patient Safety Programs for Pressure Ulcer Reduction and Prevention and Physical Restraint Elimination Nathan Williams October 19, 2010

  2. Objectives • Using data to your advantage • A Statistical Primer • Implement or create your own data collection tools • Interpreting data and using it to make changes

  3. Using Data to Your Advantage • A Statistical Primer • Descriptive Statistics • Inferential Statistics • Statistical Process Control

  4. Statistical Process Control:Run Charts and Control Charts • Graphical depictions of chronologically-ordered measurements • Used to • Visualize trends • Determine whether variation is common cause only or whether variation also has a special cause component

  5. Statistical Process Control:Common Cause Variation • Variation in measure is inherent in the process • Variation is predictable because process is stable • Variation is caused by random factors • Improvement is made by changing the process

  6. Statistical Process Control:Special Cause Variation • Due to irregular causes that are not inherent in the process • Variation is not predictable because process is not stable • Is caused by non-random causes of variation • Improvement made by first dealing with special cause(s) (usually statistical outliers)

  7. Statistical Process Control: Examples of Common and Special Cause Variation • Common Cause: • These 19 Nursing Homes had an aggregate rate of approximately 10 percent during 2005 and 2006 • Rate peaked to nearly 12 percent in 2007 • Special Cause: • Aggregate rate improved for 7 consecutive quarters, eventually falling below 5 percent in 2009

  8. Tips for DesigningData Collection Tools • MS-Excel is useful and easy-to-use • Good data management tool • Built-in data analysis and Statistical functions • Can generate nice graphs and other visual displays

  9. Interpreting Data and Using it to Make Changes • Assessing statistical significance of changes helps us to make better arguments • Statistically significant findings are often • more scientifically credible • publishable • Useful for persuading others to allocate resources

  10. Interpreting Data and Using it to Make Changes (cont.) • Run Charts allow us to visualize trends • Dynamic data displays may unmask trends that aggregations tend to hide • Visual displays often speak to people • Statistics • Make us better consumers of information

  11. Interpreting Data and Using it to Make Changes (cont.) • “You can’t manage something unless you can measure it” – Peter Drucker

  12. Contact Information: Nathan Williams, MS Biostatistician MetaStar, Inc. 2909 Landmark Place Madison, WI 53713 (800) 362-2320 or (608) 274-1940 www.metastar.com nwilliam@metastar.com This material was prepared by MetaStar, the Medicare Quality Improvement Organization for Wisconsin, under contract with the Centers for Medicare & Medicaid Services (CMS), an agency of the U.S. Department of Health and Human Services. The contents presented do not necessarily reflect CMS policy.  9SOW-WI-PS-10-188.

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