Developing Tools for Data-Driven Decisions in the Management of Respiratory Care

 Published: June 30, 2021



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We may all be familiar with the headlines expressing health care changes driven by data analytics and evidence-based practice. In many organizations, it will take years before large data solutions are easy to use. Issues with data collection and consistency will leave managers without essential tools for leadership. In these cases, it is up to leaders to design and implement Data-Driven Decision Making (DDDM) with the tools available in their departments. In many cases, leaders must make decisions with an endless stream of changes, priorities, and limited information. These decisions may affect their department in both the short run and years to come. The ability to hit the bullseye on every decision is impossible but using data-driven techniques may help leaders increase those chances.

Data can support decision-making by providing a wide-angle lens to a project or process. The picture that data creates helps leaders zoom in on details or objectives worth consideration. An experienced leader will know what components need to be kept in focus as different approaches are considered. There are many types of data in DDDM, and experience, intuition, and stakeholder feedback should all be considered in data collection and analysis. Leaders need to understand how to identify, develop and use DDDM to promote and support best practices and demonstrate the value respiratory care provides their organizations.

A Framework for decision making

The famous analytical author Tom Davenport explained his decision-making framework in his work “Making Better Decisions,” published in the Harvard business review. The framework he describes includes the following key steps.

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If this framework is the vehicle for decision-making, then data is the fuel that powers the whole machine. An accomplished leader can drive this vehicle and achieve change within their department.


Respiratory therapy management, even in smaller departments, is a complex operation with therapists treating all different patient types in almost every hospital unit and in the outpatient environment. It can be a challenge to identify critical decisions of daily operations. However, like most clinical operations, much of the logistics can be boiled down to key pillars of operations. Staffing volume and skill, supplies and inventory, and billing/productivity may be the largest identifiable sources of decisions within a department. For this reason, managers need to understand and collect data about these sources.


Not all respiratory care departments have the same resources or support within their organizations. Regardless of your department and resources, it is crucial to understand and evaluate different sources of data.

Some managers may have support from information systems or supply chains, and others may be left to creating their own internal systems. If we look at what has been identified, we can see some essential items that leaders will want to inventory. Types of services, number of staff, capital equipment, billable services, and other sets of data and information should be close at hand for a respiratory leader. These sets of data will set a foundation for DDDM. Leaders can create their own dashboards like this one to help keep track of daily operations and see their current resource pools.

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Identifying problems is easy, but finding where things are slowing down, stopping, or even breaking is far more complex, and there is an opportunity for improvement. If a leader has a comprehensive staff database, an inventory and use system, and a productivity tracking system, then they may have insight into what interventions are needed. Making decisions about what problems to fix is a matter of resources and priority. We do not want to dedicate all our time to minor issues or ones that lay outside of our department’s abilities to fix. Instead, pick something that makes an impact. The consequences of that decision will help identify the subsequent intervention and next steps.



With how fast things change in the clinical environment, leaders require assistance in making decisions. This assistance refers to the resources provided, the size and scope of decision-making, and the delegation of findings to the proper level. For example, a department manager may not have the capacity to make every decision within a department. Thus, training and delegating and staff on each shift to make these decisions is critical to ensuring optimal department operations.

Building Department Specific Data Tools

Most institutions will use enterprise-level solutions for decision-making. Enterprise tools like Kronos or Workday are commonly used for timekeeping and human resource management. Others will use Oracle or Tableau for data visualization and workforce and resource management. These programs may not have specific reports or tools for department managers to use daily. In the absence of specialized infrastructure, one may have to build personalized tools in Microsoft excel or access databases. In most cases, enterprise-level solutions will be able to report raw data in a usable format.

The creation of databases, visualization, and even specialty functions can all be developed for department-specific data needs. Using the records from enterprise solutions, managers can create tools that are easy to use and flexible for daily operations.

  • Staffing Database
    • Collect data from Human resources and timekeeping programs
  • The Inventory Database
    • Collect data on total inventory and age from software like Peoplesoft or Workaday
  • The Productivity Database
    • Collect data from finance on value measurements and procedures volumes

The Staffing Database

Using the information on staff employee status and years of service provided by HR, a manager can create a few simple dashboards for staffing. Having start dates, skill levels, years of experience, and schedule data all in one place makes a shared pool of information for management decisions. If the database stays updated, a leader can calculate shifts covered in a scheduled period and help to project the RT labor to meet patient demand for services. In addition, a simple database can report information to help document and clarify the current staffing situation.

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Using a staffing database can be crucial in times of turnover or mismatch of patient demand with RT clinical FTEs. For example, staffing was one of the most significant challenges during the pandemic. Being able to update the status of current staff and see how it affected our schedule in real-time meant that action could be taken sooner and with a level of credibility.

The Inventory Database

In many cases, decisions around supplies, equipment, and technology are made on precise financial and budget timetables. Regardless, decisions around equipment can be some of the most considerable changes in a department’s clinical operations. A few critical pieces of data related to inventory can help make better decisions. The total number of devices and their ages is a good start. It is essential to prepare for the decommissioning of equipment before it is used beyond manufacturer recommendations or is more prone to failure. Information on use, supply volumes, and even pricing can all be required to make a Data-Driven Decision. A basic Inventory dashboard may look like this:

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An inventory database can help leaders understand what resources are available for their daily operations, for both standard operating times as well as crisis events during which the normal supply-demand is disrupted. These challenges were seen during the onset of the COVID-19 pandemic and may drive significant health care manufacturing changes. The New England Journal of Medicine published an article titled, “Critical Supply Shortages — The Need for Ventilators and Personal Protective Equipment during the Covid-19 Pandemic” that discussed critical shortages in the initial stages of the pandemic. Having an inventory database already in use can identify a department’s resource shortage in a crucial time of need and assist in projecting proactive responses for future crises.

The Productivity Database

A productivity database is an essential tool for respiratory care departments to understand the ability of a department to flex their staffing to changing patient demand. Whether an organization tracks total procedures or clinical activity time, understanding what is measured and how it relates to staffing is essential to DDDM. Having a productivity database can start with a list of all billable activities and lead to annual statistics of every clinical activity performed within the department. If you can drill the data down to each clinical therapist, one could create an employee profile and dashboard for each department member. Total ventilator days and skilled procedure counts are valuable for tracking both productivity and education.

National Respiratory Patient Advocacy Award logo
National Respiratory Patient Advocacy Award logo

Productivity data is a foundation that builds over time. Looking at a shift, day, or week in time can help managers understand how they must flex their staff to changing patient demand. Productivity data displayed as a run chart can be precious by revealing trends over a pay period, month, or year-to-year to document changes in patient demand. Examining data in this manner allows the manager to document both changes in patient demand and communicate to leadership why a particular staffing model is needed.

Pulling it all together

No information system is perfect. The goal for managers using DDDM is to get better over time, based upon analysis of the data in various reporting formats Confidence in leadership and change management within the department should improve as RT clinical staff and executives see the value of the information system. The amount of work created in building these systems should decrease, and the rewards of quality information and faster results should be a product of understanding and utilizing the system to improve performance.

As leaders in respiratory care, we need to adapt to health care change. We can improve by using technology and adapting it to the field of respiratory care. As leaders, we can drive change instead of reacting to it as it comes. We can also serve our organizations by demonstrating and communicating how these systems within respiratory care could be used in other clinical departments.

Academic Resources

There is no shortage of resources related to DDDM and evidence-based leadership. However, one cannot learn everything at once. For a deeper look into DDDM, check out these resources:

  • “Evidence-Based Management in Healthcare: Principles, Cases, and Perspectives, Second Edition” by Anthony R. Kovner, Ph.D., and Thomas D’Aunno
  • “HBR’s 10 Must Reads on Making Smart Decisions” by Daniel Kahneman, Dan Lovallo, and Olivier Sibony
  • “Leading Change: An Action Plan from the World’s Foremost Expert on Business Leadership” by John P. Kotter
  • “The Checklist Manifesto” by Atul Gawande


Davenport H, T. (2009). Make Better Decisions. Harvard Business Review, 1-6. Retrieved from

Ranney ML, Griffeth V, Jha AK. Critical Supply Shortages – The Need for Ventilators and Personal Protective Equipment during the Covid-19 Pandemic. N Engl J Med. 2020 Apr 30;382(18):e41. doi: 10.1056/NEJMp2006141. Epub 2020 Mar 25. PMID: 32212516.

Email with questions or comments, we’d love to hear from you.

David Eitel, RRT, MHA, MSRT, RRT-ACCS, CPFT, is an experienced Respiratory Therapist and health care leader with over eight years of industry experience. David is passionate about health care policy and personal development. You can connect with him on LinkedIn or find his excel and health care-related content on YouTube. On his days off, David enjoys making digital content, hiking, and watching movies.

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