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Behind the data: Factors driving optimal EMS delivery

Quality management implementation at Monroe Fire Department

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Businessman analyzing company’s financial balance sheet working with digital augmented reality graphics. Businessman calculates financial data for long-term investment.

Thapana Onphalai/Getty Images/iStockphoto

By Joe Locke, AAS; Kelly Wright, MS

This manuscript details Monroe fire department’s improvement across crucial data points through its quality management program. However, simply identifying and tracking errors will not enhance the EMS care given by providers. We illustrate multiple factors that improve EMS service delivery, including quality management programs, training, data utilization and emphasizing EMS care.

Monroe Fire Department in Ohio needed a universally objective way of assessing its EMS service to evaluate its level of service. In July 2019, the department established a formal Quality Management (QM) system to ensure EMS care met agency expectations. The QM program aims to provide a perpetual, systematic process to enhance the overall quality of departmental prehospital emergency medical care. This system utilizes data from the electronic prehospital report to identify provider errors, which can identify organizational training needs, improve patient outcomes and optimize EMS billing revenue.

The Monroe Fire Department’s QM process is comprised of two parts: quality assessment (QA) and quality improvement (QI). The QA portion of the QM process is a continuous, systematic evaluation of defined standards to ensure that EMS care meets established protocols and assesses individual and team proficiency during patient care. Monroe Fire Department’s QA team reviews 100% of EMS patient care reports. To ensure clinical accuracy, the QA team member assesses the electronic patient care reports for accurate and thorough documentation of patient care, including vital signs, interventions and other relevant information.

Expert perspectives on improving patient outcomes

Data methods and analysis

The QI process begins once an error is identified during the QA process. The QA team member will objectively identify errors based on protocol language or department policy. This information is documented and sent to the EMS coordinator for review. After confirming the error, the EMS coordinator drafts the QI form and delivers it to the EMS provider’s supervisor, who then ultimately reviews the error with the EMS provider.

This process aims to prevent future errors by identifying the error and providing any education needed to close any knowledge gaps.

The QI form used to document identified errors was amended to include a “Root Cause Analysis” based on the 2017 Joint Commission recommendations and extracted from “Root Cause Analysis in Health Care: Tools and Techniques, Sixth Edition,” which is a form that Atrium Medical Center (the nearest admitting medical facility) uses as a part of their own QM process. Including this Root Cause Analysis section helps leadership and responders understand why an error occurred (i.e., lack of training, unforeseen issues or technology failures).

These errors are entered into an internal Excel spreadsheet, recording error data for each provider and detailing the per-month and year-to-date (YTD) errors of each type. This data grows over time per provider and can be used as a diagnostic tool to identify areas of improvement in a long-term, defensible, quantifiable way.

Tracking electronic EMS data allows current statistics to be generated on an individual, crew, shift and department scale. When errors are identified, they are classified into one of three categories: documentation, clinical or gross.

  • Documentation errors are categorized as minor documentation errors unrelated to patient care, such as documenting an incorrect incident number.
  • Clinical errors are related to the examination and treatment of patients, such as performing an inadequate stroke assessment.
  • Gross errors are significant clinical errors relating to any action or inaction interpreted as dangerous or which could cause a direct negative effect on a patient’s outcome, including a sentinel event. An example of a gross error would be administering an incorrect medication or incorrect dosage, which caused harm or death.

As the QM process has matured, so has the need for differentiating between these different error types. The Fire Department now breaks down the total errors into further subtypes to determine what, if any, relationships exist between the number of documentation errors and revenue recognized from EMS billing.
Analyzing the data acquired through the QM process is crucial for identifying areas of strength, weakness and trending progress, and ensuring ongoing compliance with agency standards and objectives. Organizations can use this data to enhance performance, reduce risks and meet agency goals.

This data-driven approach reduces intentional or unintentional bias, drastically reduces the likelihood of prejudice or favoritism during assessment and provides the EMS coordinator with the ability to provide meaningful, fact-based feedback to improve provider performance.

Using a quantitative approach also provides leadership with an avenue to foment accountability within the organization at the individual, unit, station and department levels. Monthly error data is gross data (not normalized); a net run-to-error ratio is calculated at the end of each year as part of individual employee performance assessment and for use in determining performance award eligibility.

Measuring the results of QI implementation


Figure 2. Number of EMS reports versus total errors relative to each other, July 2019 to October 2023.

Image/Courtesy of City of Monroe Fire Department

According to a retrospective analysis of past data, before QM program implementation, Monroe FD was experiencing monthly errors in the 100s. The department’s error rate has dramatically improved since the QM initiative, averaging about 13/month.

Increases in errors in July 2021 and June 2022 directly correlate to hiring new providers whose experience curves can lead to higher error frequency. The historic lows of three errors in April 2022 and five errors in February and March 2021 correlate with unusually long periods of employee retention and, thus, program optimization, further supporting the hypothesis that a formal QA/QI process improves provider performance.

As a result of an unexplained increase in errors in April 2023, Monroe FD implemented a step in the QM program in which leadership meets with a provider with five or more errors in the year to formally review policy and procedure to mitigate future errors. The QI form and aggregated monthly error data are used to educate the provider and provide concrete, data-driven opportunities for improvement.

Improving revenue with quality management

Since implementing the QM program, the City of Monroe has also seen an overall increase in EMS billing revenue.

Much of this increase in revenue is directly attributable to the reduction in documentation errors, which include billing errors.

For example, a provider incorrectly documents or omits a patient’s name, home address or social security number on an EMS report, which impacts patient billing. If the provider does not obtain the appropriate signatures from the patient, hospital or EMS staff, that also can impact billing.

As the department recovers billing money based on the level of service provided/the number of interventions performed, incorrectly documenting EMS runs can cause the department to only receive a portion of what it could if correctly documented in the first place.

Thus, department EMS billing revenue increased, not because of a spike in patient transports – in fact, there were fewer transports in 2020 – but because of better and more thorough documentation of patient case reports.


Figure 3: EMS billing revenue recognized versus number of transported patients, 2018-2022.

Image/Courtesy of City of Monroe Fire Department

As the EMS industry begins to navigate data complexities, utilizing data for progress with an ethical focus is imperative.

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About the authors

Joe Locke, AAS, is EMS coordinator, City of Monroe Fire department.

Kelly Wright, MS is a City of Monroe GIS specialist.