Quality tools (2), Ola Elgaddar, 30 09 - 2013

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This is part two of the Quality Improvement tools lecture

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Quality tools (2), Ola Elgaddar, 30 09 - 2013

  1. 1. M t d lit t lManagement and quality tools Ola H. Elgaddar MBChB MS MD CPHQ LSSGBMBChB, MSc, MD, CPHQ, LSSGB Lecturer of Chemical Pathology Medical Research Institute Alexandria UniversityAlexandria University Ola.elgaddar@alexu.edu.eg
  2. 2. Performance ImprovementPerformance Improvement ToolsTools (II)( )
  3. 3. According to the Healthcare Quality Certification Board (HQCB):Certification Board (HQCB): I) T l f l iI) Tools for planning: Hoshin Planningg Force field analysis Gantt chartGantt chart
  4. 4. A di t th H lthAccording to the Healthcare Quality Certification Boardy (HQCB): II) Tools for team: B i t iBrainstorming Affinity diagramy g Selection grid
  5. 5. According to the Healthcare Quality Certification Board (HQCB):Certification Board (HQCB): III) Tools for data collection: IndicatorsIndicators Check sheets
  6. 6. A di t th H lth Q litAccording to the Healthcare Quality Certification Board (HQCB): IV) Tools for data analysis:IV) Tools for data analysis: Run / Control charts HistogramHistogram Scatter diagram
  7. 7. According to the Healthcare Quality Certification Board (HQCB):( Q ) IV) T l f t l i (RCA)IV) Tools for root cause analysis (RCA): Flow chart Cause - Effect diagram Pareto chartPareto chart
  8. 8. Indicators Indicators are quantitative measures of a specific part of a process or of ana specific part of a process or of an outcome, and comparing it to a target.p g g By themselves, they don’t directly lit th th h lmeasure quality, rather, they help provide data that when analyzed, givep y , g information about quality
  9. 9. Indicators 1) Rate based:1) Rate based: No of patients with a specified outcome from a disease management program /from a disease management program / total No of patients participating in the programprogram 2) Sentinel event:2) Sentinel event: 100 % analysis and 0 % acceptability All patients on which wrong side surgry was performed
  10. 10. Indicators Define: - The intent -Numerator and denominator-Numerator and denominator (Operational definition)( p ) - Reliability - Validity
  11. 11. Indicators Data triggers: - Sentinel event Expected performance rate- Expected performance rate - Trend (Specified rate change over time)Trend (Specified rate change over time) - Pattern (Specified diff between groups)
  12. 12. Check list A structured, prepared form for collecting and analyzing data.and analyzing data. When to Use a Check Sheet?When to Use a Check Sheet? When data can be observed and collected repeatedly by the same person or at therepeatedly by the same person or at the same location. When collecting data on the frequency ofWhen collecting data on the frequency of events, problems, defects, etc. When collecting data from a productionWhen collecting data from a production process.
  13. 13. Control charts (SPC)Control charts (SPC) The control chart is a graph used to studyThe control chart is a graph used to study how a process changes over time. It has a central line for the average, ang , upper line for the upper control limit and a lower line for the lower control limitlower line for the lower control limit. These lines are determined from historical data.data.
  14. 14. Control charts (SPC)Control charts (SPC) By comparing current data to theseBy comparing current data to these lines, you can draw conclusions abouty whether the process variation is consistent (in control) or isconsistent (in control) or is unpredictable (out of control, affected by special causes of variation)
  15. 15. Control charts (SPC)Control charts (SPC) Common cause variation:Common cause variation: Variations are inherent in the process and remain till the system changes Special cause variation:Special cause variation: The variations are considered to be the effect of many, individually small, unobserved influencesunobserved influences.
  16. 16. Histogram It shows how often each different value inIt shows how often each different value in a set of data occurs. It is the most commonly used graph to show frequency distributions and to viewshow frequency distributions and to view how the distribution of the data centers itself around the mean or main specificationaround the mean, or main specification. Histograms show the center of the data, the spread of the data and any data skewness or outliers.
  17. 17. Scatter diagram The Scatter Diagram is a Quality ToolThe Scatter Diagram is a Quality Tool that can be used to show the relationship between "paired data“, i.e: shows correlationshows correlation. Strong “r” = Higher correlation, in ith ideither sides
  18. 18. Flow chartFlow chart

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