Funded by HRSA HIV/AIDS Bureau Using Data for Quality Improvement for Part A & B Grantees Presented by: Barbara M. Rosa, RN, MS NQC Consultant

2Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Information Into Action

3Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Stages of Coping with Data Stage I: “The data are wrong….” Stage II: “The data are right, but it’s not a problem…” Stage III: “The data are right, it’s a problem, but it’s not my problem…” Stage IV: “The data are right, it’s a problem, it’s my problem…”

4Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Barriers To Putting Data Into Action Don’t even know where to get data/info Paralysis by analysis No one is interested in it Defensiveness Too complex to understand Incorrect interpretation of data

5Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Analyze Data* Analyze data and review the results. Identify areas where additional data are required. If historical data are available, compare for trends. Display and distribute data to communicate findings and results. Identify areas for improvement and select a quality improvement project. * Step 4 in HAB’s Quality Management Technical Assistance Manual

6Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Run Chart

7Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Control Chart Definition Control chart: a run chart with statistically determined upper and lower control lines drawn on either side of a process average; used to analyze different types of variations Creating a Control Chart  Create Run Chart  Calculate upper/lower control limits, plus or minus 3 standard deviations (3 sigma) of the centerline  Add the upper/lower control limits to the Run Chart  Most computer spreadsheet programs can be used to construct them.

8Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Control Chart

9Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Common/Special Cause Variation Common Cause Variation:  Variability caused by unknown factors that result in a steady but random distribution of output around the average of the data.  Also called random variation, noise, noncontrollable variation, within-group variation, or inherent variation. Special Cause Variation:  Variability caused by a specific factor or known factors such as environmental conditions or process input parameters that result in a non-random distribution of output.  Also referred to as "exceptional" or "assignable" variation.

10Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Histogram

11Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Pareto Chart

12Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Data Follow-up Sheet A) Data Analysis: What are the results for key clinical indicators? What are the major findings based on generated data reports and your data analyses? B) Data Sharing: Did you discuss the data results and analysis with your QI committee? Facility-wide QI committee? How did you share the data results with your staff and consumers (CAB, etc.)? C) Data Follow-up: What immediate changes will you make based on the key findings? Are you considering initiating a QI project to address the data findings? Who will be responsible and what are the next steps?

13Using Data for Quality for Part A & B Grantees National Quality Center (NQC) All HIV Indicators Combined

14Using Data for Quality for Part A & B Grantees National Quality Center (NQC) WHAT ARE WE TRYING TO ACCOMPLISH? Understand the current situation Use data to define the situation

15Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Data Follow-up What immediate changes will you make based on the key findings? Are you considering initiating a QI project to address the data findings? Who will be responsible and what are the next steps?

16Using Data for Quality for Part A & B Grantees National Quality Center (NQC) What Changes Can We Make that Will Result in an Improvement? Do the changes have well-defined parameters? Will the changes improve client care relatively quickly? Will staff members and leaders be able to live with the changes? “Yes, it sounds good, but you don’t know my organization.” Learning how to make the change in your organization is the purpose of PDSA

17Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Model For Improvement Model consists of: A) three questions (aim, measure, change) to form context for improvement B) Plan-Do-Study-Act (PDSA) Cycle to structure tests

18Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Act What changes are to be made? Next cycle? Plan Objective Questions and predictions (why) Plan to carry out the cycle (who, what, where, when) Study Complete the analysis of the data. Compare data to predictions. Summarize what was learned Do Carry out the plan Document problems and unexpected observations Begin analysis of the data The PDSA Cycle For Learning And Improvement

19Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Repeated Use of Cycle Hunches Theories Ideas Changes That Result in Improvement AP SD A P S D AP SD D S P A Learning from Data Very small scale test Follow-up tests Wide-scale tests of change Implementation of change PDSA Measures

20Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Use of Mental Health Screening Tool by Case Managers MH screening tool used by CM will ID patients needing further assessment Improved ID of clients needing MH referral AP SD A P S D AP SD D S P A DATA D S P A Cycle 1A: Adapt MH screening form and try for one week w/ 1 CM Cycle 1B: Evaluate & revise form again based on findings Cycle 1C: Present revised form to all CM and document feedback Cycle 1D: Revise & test form with all patients for one mo. Cycle 1E: Implement & monitor the standards

21Using Data for Quality for Part A & B Grantees National Quality Center (NQC) Summary: Remember to…… Begin the analysis with a few questions or hypotheses before “digging” through the data. Limit the display of data results to summarize your most important findings. Display data graphically whenever possible Publicize the results

22Using Data for Quality for Part A & B Grantees National Quality Center (NQC) "Quality" Is Not a Department, Program, or Project….* Quality improvement is not a program or a project; it isn’t the responsibility of one individual or even those assigned to the quality department. Meaningful and sustainable changes are possible only when people throughout an organization feel a shared desire to make processes and outcomes better every day. *Mark Maus—Medical Director, Solano Co. Family Health Services