Module 4
Why Data Display Matters
Data that's easy to understand builds momentum, accountability, and celebration. It helps frontline staff and leadership see the value of improvement efforts and sustains engagement over time. The way you display data matters as much as the data itself.
The Primary Tool: Run Charts
In QI, showing data over time is more important than showing a single snapshot. A single number tells you where you are today, but it can't tell you whether you're improving, holding steady, or slipping, and it can't show you whether a change you made actually made a difference.
A run chart is simply a line graph that plots your measure over time. Time (days, weeks, or months) goes along the bottom (x-axis), and your measure, like the percentage of completed screenings, goes up the side (y-axis). Each point represents one data collection period, connected in the order they occurred.
Run charts are the preferred display method in QI because they let you see patterns and shifts as they happen and, when you mark the date of a change on the chart, connect a specific intervention to a specific change in the data. This is what separates a run chart from a plain bar graph or a static report: it tells the story of change, not just a single result.
💡 Example: Run Chart in Practice — ED Trauma Screening
A PMHCA coach suggests that a partner site try something simple: post the weekly run chart they've helped compile of completed trauma screenings somewhere staff naturally gather, like next to the breakroom coffee machine. The site agrees to test it, pairing it with a 5-minute huddle each week where staff reflects on progress:
- What helped or hurt screening rates this week?
- What should we try differently?
As shown in the chart above, weekly screening rates hovered around a baseline median of 62% for the first five weeks. When the site introduced a new EMR prompt in Week 6, the run chart showed a clear upward shift to 74%, then 78%, then 82% — immediately visible to the whole team, without anyone needing to pull a report.
Result: A small PMHCA suggestion turned a static metric into a visible, shared team story of improvement.
Other Tools You Can Use
A variety of tools and software programs can help your team collect, organize, analyze, and visualize data to support QI efforts. Some are simple, familiar tools that require little setup, while others offer more advanced capabilities. The examples below can help you identify options based on your team's needs, experience, and available resources.
Data Collection
- Google Forms or Microsoft Forms: Simple tools for creating surveys and collecting data. Responses can be automatically organized in spreadsheets for easy review and analysis.
- REDCap: A secure data collection platform commonly used in healthcare and research. It supports structured data entry, surveys, data validation, and exporting information for analysis.
Data Organization and Preparation
- Microsoft Excel or Google Sheets: Familiar spreadsheet tools for entering, organizing, cleaning, and analyzing data using formulas, pivot tables, and charts.
- Power Query (Excel or Power BI): Helps combine, clean, and reformat data from multiple sources. Data preparation steps can be saved and repeated as new information becomes available.
Data Analysis
For teams that need to conduct more advanced statistical analyses, several software options are available:
- SPSS: A statistical software package with user-friendly menus for conducting analyses without extensive coding experience. It also supports reusable analysis commands.
- Stata: Commonly used in public health and healthcare research, offering both menu-based and command-based options for analyzing data.
- SAS: An advanced statistical software package used in healthcare, government, and research to manage large datasets and conduct complex, reproducible analyses. It typically requires programming experience and a paid license.
- R or Python: Free, programming-based tools for advanced data cleaning, transformation, statistical analysis, and visualization. They offer flexibility but require coding skills.
Data Visualization and Reporting
Once your team is comfortable with run charts, other visualization approaches can help you explore your data, communicate findings, and engage stakeholders. These should supplement, not replace, run charts.
- Bar Graphs and Pie Charts: Useful for comparing groups or showing a snapshot at a single point in time, but they may mask trends over time.
- Dashboards: Combine multiple measures (e.g., screening rates, referral follow-up, and family satisfaction) into one visual. Particularly useful for monitoring progress and reporting to leadership.
- Visual Trackers and Huddle Boards: Sticky note walls, whiteboards, or printed run charts displayed in staff areas can promote team engagement and daily awareness of QI efforts.
- Power BI or Tableau: Software for creating interactive dashboards, charts, and reports to monitor QI measures, identify trends, and track progress over time.
Workflow Automation
- Power Automate, Alteryx, or KNIME: Tools that automate repetitive tasks, such as transferring, combining, and transforming data across systems. They may require additional setup but can reduce manual work and improve efficiency.
Choosing the Right Tool
You do not need advanced software to get started with QI. Many teams can successfully collect, analyze, and track their data using familiar tools such as Excel, Google Sheets, or Microsoft Forms. As your project grows, additional tools may help streamline processes, manage larger datasets, or support more complex analyses.
Consider ease of use, cost, technical support, and data security requirements when selecting a tool. Always follow your organization's privacy and security policies, particularly when working with patient information.