1. Quality Reporting and Improvement Using Technology Mike Hindmarsh Hindsight Healthcare Strategies Cincinnati, OH June 18, 2010

2. How Do We Know That a Change is an Improvement? “When you can measure what you are speaking about and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind.” Lord Kelvin, May 3, 1883 Lord Kelvin, May 3, 1883

3. Measuring Performance for Improvement We cannot improve what we cannot measure We cannot improve what we cannot measure IT is a critical success factor in gather improvement data IT is a critical success factor in gather improvement data Understanding how to get data out of your EMR is essential Understanding how to get data out of your EMR is essential Garbage in, Garbage out Garbage in, Garbage out “Why bother, I’m doing okay in practice!” “Why bother, I’m doing okay in practice!”

4. Sometimes gathering data can bring new and surprising knowledge!

5. Different Purposes for Measurement AspectImprovementResearch Aim Improvement of care New knowledge Methods: Test Observability Test Observability Test observable Test blinded or controlled Bias Bias Accept consistent bias Design to eliminate bias Sample Size Sample Size “Just enough” data, small sequential samples “Just in case” data Flexibility of Flexibility of Hypothesis Hypothesis Hypothesis flexible, changes as learning takes place Fixed hypothesis Testing Strategy Testing Strategy Sequential tests One large test Determining if a Determining if a Change is an Change is an Improvement Improvement Run charts or Shewhart control charts Hypothesis, statistical tests (t-test, F- test, chi square), p-values Confidentiality of Confidentiality of the Data the Data Data used only by those involved with improvement Research subjects’ identities protected

6. Getting Started: Identify your population Create a query that identifies the population (e.g., ICD-9 codes) Create a query that identifies the population (e.g., ICD-9 codes) Be sure to code populations the same way. Be sure to code populations the same way. Don’t “over-worry” about the accuracy of case finding: you can clean it up as you go. Don’t “over-worry” about the accuracy of case finding: you can clean it up as you go. Get baseline data in the easiest, fastest fashion possible…..if it’s hard to program, leave it for later! Get baseline data in the easiest, fastest fashion possible…..if it’s hard to program, leave it for later! Don’t obsess about baseline data accuracy! Don’t obsess about baseline data accuracy! Select measures that you can impact and have clinical relevance Select measures that you can impact and have clinical relevance

7. For Each Measure Use measures from evidence-based guidelines Use measures from evidence-based guidelines Create concrete operational definitions to capture data from you IT in a reliable, consistent manner Create concrete operational definitions to capture data from you IT in a reliable, consistent manner Use the reporting template to display your measures as quickly as possible. Use the reporting template to display your measures as quickly as possible. Set goals based on evidence or best pratice Set goals based on evidence or best pratice Gather data monthly (quarterly at a minimum!) Gather data monthly (quarterly at a minimum!)

8. Example of Improvement Measures: Diabetes % with A1c<7 % with A1c<7 % with BP<130/80 % with BP<130/80 % on ACE1 or ARB % on ACE1 or ARB % with LDL<2.0 nmol/l % with LDL<2.0 nmol/l % screened for microalbumen % screened for microalbumen % with eye screen in last 24 months % with eye screen in last 24 months % with foot exam in last 12 months % with foot exam in last 12 months % with A1c in last six months % with A1c in last six months % with documented self-mgmt goals in medical record % with documented self-mgmt goals in medical record

9. Annotated Time Series

11. “This type of data reporting isn’t reliable!!” Yes it is….for quality improvement purposes! Yes it is….for quality improvement purposes! Trending is what you are looking for…not statistical reliability. Trending is what you are looking for…not statistical reliability. Your “goal” is to improve population outcomes over your usual care by changing care for every patient: the annotated time series (run chart) will tell you if you are succeeding! Your “goal” is to improve population outcomes over your usual care by changing care for every patient: the annotated time series (run chart) will tell you if you are succeeding!

12. Improvement in Glycemic Control Percent of (Patients with HbA1c >9 in Clinic A)

13. Improvement in Glycemic Control (% of Population with HbA1C >9 in Clinic A)

14. Improvement in Glycemic Control (% of Population with HbA1C >9 Clinics B and C)

15. Improvement in Glycemic Control (% of Population with HbA1C >9 in Clinic B)

16. Improvement in Glycemic Control (% of Population with HbA1C >9 in Clinic C)

17. Run Charts of Monthly Measures - Diabetes Population

18. Summary Define your population with carefully thought out queries Define your population with carefully thought out queries Obtain baseline data on relevant measures through structured queries Obtain baseline data on relevant measures through structured queries Produce regular reports for improvement activities Produce regular reports for improvement activities Set targets/goals for imporvement based on best practice Set targets/goals for imporvement based on best practice Be ambitious! Be ambitious!