quality improvement measures and data collection n.
Skip this Video
Loading SlideShow in 5 Seconds..
Quality Improvement: Measures and Data Collection PowerPoint Presentation
Download Presentation
Quality Improvement: Measures and Data Collection

Quality Improvement: Measures and Data Collection

90 Vues Download Presentation
Télécharger la présentation

Quality Improvement: Measures and Data Collection

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Quality Improvement:Measures and Data Collection Theresa Scott, MSTIPQC Data Manager Peter Grubb, MD TIPQC Medical Director

  2. Where do measures enter the picture? AIM statement MEASURE(S) • What specific measure(s) will you collect? • How will you operationally define the measure(s)?

  3. Types of measures • Outcome – measure(s) directly related to your AIM. • Process – measures that assess the points in the sequence (ie, flow) of the process that lead to an outcome. • Balancing – measures that look at the entire system from many viewpoints; can include competing explanations for success or the unintended consequences/adverse side effects that can occur when you make changes.

  4. Data to be collected: Monthly Outcome TJC PC-03 • Numerator is the number of patients with antenatal steroid therapy initiated prior to delivering preterm newborn between >= 24 weeks and <32 weeks. • Denominator is the number of patients delivering live preterm newborns between >=24 weeks and <32 weeks. • Exclusions (see definitions below) include a reason for not initiating antenatal steroid therapy that is explicitly documented in the patient’s chart. From Toolkit draft 131119

  5. Data to be collected: Monthly TJC PC-03 • Exclusions (see definitions below) include a reason for not initiating antenatal steroid therapy that is explicitly documented in the patient’s chart • Exclusions: generally accepted exclusions would include but not be limited to: • precipitous delivery • maternal infection • other maternal contraindication to corticosteroid administration. From Toolkit draft 131119

  6. Data to be collected: Monthly TJC PC-03 • Definitions for Primary Outcome Measure • Antenatal steroid therapy: dexamethasone 6 mg IM every 12 hours x4 doses or betamethasone 12 mg IM every 24 hours x 2 doses • Initiation of therapy: completed first dose of dexamethasone 6 mg IM or betamethasone 12 mg IM • Gestational age: completed weeks and days based on standard American Congress of Obstetrics and Gynecology criteria for dating From Toolkit draft 131119

  7. Data to be collected: Balancing Measures • Is there evidence to suggest potential unintended consequences of ANS administration? • Group discussion: What about “Serious maternal infection” • (Need operational definition, including numerator and denominator.) • Could we use CDC NHSN post-operative infection? • Data definitions are standardized between hospitals. • Data is already collected monthly... • Numerators and denominators are readily available • Any alternatives or additions to propose? From Toolkit draft 131119

  8. Data to be collected: Process Measures • Process measures tell us whether we are doing (the PBP) what we intend to do in a consistent, and highly reliable manner. • Pragmatic definition: What is really going on at 2 am? • Hard way: Actually measure and record everything… • Alternative way: Develop context appropriate, behavior specific measure that drive improvement, then sample strategically. (Chart Review, Rounding for Results, Random Clinical Audit, Checklist) From Toolkit draft 131119

  9. Data to be collected: Process Measures • Pragmatic definition: What is really going on at 2 am? • Sometimes useful to map what is happening and compare to map of what is supposed to happen. • Many techniques, don’t have time today… • Plan: collect Outcome and Balancing Measures • Create a baseline 4-6 months • Teams review CPQCC toolkit and their own practice • Develop process measures collectively • Looking for 5 keys to highly reliable implementation of evidence • Deploy 5 measures for monthly auditing & reporting ~7/14 From Toolkit draft 131119

  10. That’s the what, now for the how. • Once a month • Outcome: numerator, denominator, exclusions • Balancing: numerator, denominator • Note: both of the above are already collected • Process measures: • Maximum of 5: numerator, denominator • You decide frequency and sample size for your situation • Total: Enter 15 numbers, once a month

  11. Data Collection Plan • Collecting data allows you to monitor variation in a process, to see the effects of a process change, and to provide an objective forum for making decisions. • To maintain consistency and reliability of data capture, each team will need to develop a Data Collection Plan. • Includes: • purpose (the why) of collecting the data; • whatdata will be collected • whowill collect it; • AND the storage and editing of data; and planned analysis. Source:

  12. Data Entry Tool: REDCap • REDCap = Research Electronic Data Capture • Secure, web-based application designed to support traditional case report form (CRF) data capture for research studies. • Very intuitive and user friendly. • Idea for this project: online database will exist where all of the data for each “record” (from each group) will be entered and maintained. • Each record represents a month (& year) of data. • IMPORTANT: Data to be entered on a monthly basis no later than the 7th of the following month. • Will be able to generate real-time reports.

  13. REDCap Demo • Example: Breastfeeding Promotion Project • Ongoing for a year • ANS project is simpler, and requires less data. • Demo: •

  14. What does collecting and automating the data do for us?

  15. Roles of Data • Baseline – Tells us where you are at the start. • On-going – Tells us whether and how you are changing your outcomes and performance. • Overall – Tells you what impact you (ie, the project and its initiatives) have on your AIM. Source:

  16. Importance of “Good Data” • Must ensure that the data you collect are accurate, complete, and in the required format. • GIGO: Who are you fooling? • Good data on measures that matter creates leverage- especially data on solid PBP implementation. • The data you collect and enter are the ultimate proof of your success and will be shared broadly (ie, they will influence care and policy). Source: