Improving real-time vital signs documentation : Nursing Management

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Improving real-time vital signs documentation

Fuller, Tina MSN, RN-BC; Fox, Becky MSN, RN-BC, CNIO; Lake, Donna PhD, RN, NEA-BC; Crawford, Karen MSN, RN-BC, CHTS-PW

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Nursing Management (Springhouse) 49(1):p 28-33, January 2018. | DOI: 10.1097/01.NUMA.0000527716.05512.4e
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In Brief

This quality improvement project set out to increase real-time collection and documentation of vital signs data by using interfaced mobile vital signs machines. Did it succeed?


Assessing and documenting vital signs are essential tasks routinely performed by nurses and unlicensed assistive personnel (UAP). The information gathered is useful in identifying a patient's overall health status and physiologic signs of deterioration, and can lead to early recognition and treatment of serious conditions such as sepsis.

When vital signs information is documented in the electronic health record (EHR), clinical decision support tools can alert clinicians to subtle changes or deterioration in a patient's clinical condition. Without timely documentation of vital signs, clinical decision support alerts may trigger too late to impact patient outcomes. That's why there's a growing need to improve efficiencies in obtaining and documenting vital signs data to ensure patient safety, enhance the patient experience, and improve clinician workflows.1

The time between vital signs collection and documentation can be lengthy due to numerous factors, including nurse-to-patient ratios, interruptions, vital signs machines not interfacing with the EHR, requirements to log into the EHR between each patient, and patient care taking priority over documentation.2 In addition, despite the availability of mobile computers, nurses and UAPs have voiced concerns about taking the computer and vital signs machine into a patient's room when completing vital signs documentation, due to room capacity and ergonomic hazards. For these reasons, clinicians typically collect one patient's vital signs, document the findings on paper, go to the next assigned patient, and repeat. Once the process is complete for all assigned patients, clinicians batch document all of the vital signs into the EHR at a computer station.

Entering vital signs in batches further delays documentation and creates duplicative work and the potential for errors. Research indicates that the percentage of errors with manual transcription of vital signs ranges between 10% and 18.75%.3,4 Additionally, research suggests that vital signs should be documented automatically as they're collected to improve accuracy and timeliness.5

We embarked on a quality improvement project to improve the rate of real-time collection and documentation of vital signs data by using interfaced mobile vital signs machines.


Using the Dartmouth Clinical Microsystem Action Guide and Institute for Healthcare Improvement methodology, we put together a team of nurses, UAPs, informatics staff, and key nurse leaders to assess the clinical microsystem for vital signs collection, documentation in the EHR, contribution to clinical decision alerts, and identification of patient deterioration.6 In addition, we mapped the documentation workflow process and created a fishbone diagram for the action items needed to develop the mobile vital signs machine documentation process. Lastly, we determined a measurement plan and pilot activities based on our project management tool.

The process and workflow patterns studied included collection of vital signs data beginning with bedside measurement of BP, heart rate, respirations, temperature, and oxygen saturation by a nurse or UAP and ending when the collected data were entered manually into the EHR.

The Plan, Do, Study, Act (PDSA) cycle and team approach provided a structure to conduct this quality improvement project.7 As shown in Table 1, the Define, Measure, Analyze, Improve, Control (DMAIC) methodology was utilized to isolate the lack of interfaced equipment as the root cause.8 The team continued with the test of change and measurement activity, using the PDSA cycle.13

Table 1::
DMAIC example

Our global aim was to improve the process for electronically recording vital signs data on medical-surgical units without continuous bedside monitoring devices. The specific aim was to implement mobile vital signs machines interfaced with the EHR to decrease the lag time between vital signs collection and documentation to achieve the following:

  • reduce the average time between vital signs collection and documentation (91 minutes) by 85%
  • reduce the number of steps taken to record vital signs in the computer by 100%
  • decrease the time to enter vital signs into the computer by 80%
  • decrease the number of patients with delayed vital signs entry by 75% by December 31, 2016.

With the pilot implementation of a mobile vital signs machine interfaced with the EHR, unit nurses anticipated a decrease in lag time between vital signs collection and documentation.


A 32-bed medical telemetry unit with the following demographics was selected for the test: patients with one of the top four discharge diagnoses (heart failure, pneumonia, atrial fibrillation, and chest pain), with an average hospital stay of 3 days and an average age of 65. Routine vital signs were obtained every 4 hours. The nurse-to-patient ratio was 1:4 and the UAP-to-patient ratio was 1:10. Before the test, the average time between vital signs collection and documentation for this patient population was 91 minutes.

To coordinate the steps required to complete a process change and improve the likelihood of adoption, Rogers' Diffusion of Innovation Theory and Kotter's eight-stage change process were incorporated.9-11 Following Kotter's stages, the urgency for the change was established, a team was developed to guide the change, the vision was communicated, teams were empowered to make the change, short-term wins were celebrated and communicated to produce more change, and the process was monitored to ensure that it was anchored as part of the culture.12,13

Before implementation, a device fair was conducted to allow clinical nurses and UAPs an opportunity to evaluate two different vendors of mobile vital signs machines with interface capability. The mobile vital signs machines were also capable of interfacing other routinely documented clinical data, such as urine output, amount of meal eaten, and patient positioning, to further optimize workflow.

Predetermined requirements were developed with input from various departments, including information technology (IT), biomedical services, and end-users. Forty-one clinicians (84%) responded to an anonymous survey soliciting feedback on each device and a vendor was chosen. Clinical nurse leaders identified key stakeholders who worked with the IT department to plan the implementation.

Research has shown that barriers prevent the anchoring and full adoption of a change into standard practice.12 To minimize barriers, we followed Roger's Diffusion of Innovation Theory to identify the innovators and early adopters, assigning them as team leads, trainers, or super users.14 The team monitored performance metrics daily to identify outliers, discussed the barriers to change, and established interventions to minimize interruptions in adoption.9


To analyze the impact of this change, a Systems Applications Products Audit was used to query recorded times for vital signs data to obtain a baseline and measure for change. In addition, a time and motion study plotted the number of steps and time taken to document vital signs data. As shown in Table 2, the use of the interfaced mobile vital signs machine reduced delays in documentation, removed unnecessary/duplicative steps, and eliminated the time taken to transcribe vital signs data into the EHR.

Table 2::
Performance metrics

Before implementation, there were significant delays between collection and documentation of vital signs. (See Figure 1.) However, before 100% of clinicians (54 nurses and UAPs) on the 32-bed medical telemetry unit cycled through the pilot, they'd already gained approximately 7 minutes of time saved per 10 patients for each set of vital signs rounds performed. (See Figures 2 and 3.) Extrapolating these findings across the test unit suggests a time savings of approximately 817 hours per year, as shown in Table 3.

Figure 1::
Results before vital signs machines (11/27/16 to 12/7/16)
Figure 2::
Implementation of interfaced vital signs machines
Figure 3::
Results post vital signs machine implementation
Table 3::
Medical telemetry vital signs documentation annualized time savings


To our knowledge, interfaced vital signs machines have been available on the market for more than 5 years; however, many nursing units rely on older equipment and continue to transcribe vital signs data, contributing to delayed documentation. These findings are consistent with our specific aim to improve the rate of real-time vital signs documentation by improving the workflow process. With the implementation of mobile vital signs machines that interface with the EHR, we demonstrated an improvement in real-time documentation, removing unnecessary steps in the vital signs documentation process.

From the results of our clinician survey, we know nurses and UAPs perceive real-time documentation of vital signs as important to patient safety. Our findings indicate that when technology supports the workflow process, patient care improves. There were outliers in performance related to rapid response events; however, we achieved an overall 95% reduction in delayed vital signs documentation with the interfaced mobile vital signs machines.

Our nurses have responded positively to this technology change as reflected in the 2016 employee engagement survey. In comparison with other National Database of Nursing Quality Indicators® facilities, our organization ranked in the 85th percentile for the question “I get the tools and resources I need to do my job,” with an improved rating of 4.03 (up from 3.86 in 2015). Through the nursing practice and facility informatics councils, leadership continues to hear from bedside staff about the desire to have more (and improved) technology in their hands to help care for patients.

Lifesaving change

Vital signs data actively contribute to lifesaving early warning alerts. Although technology can improve real-time documentation, technology alone won't ensure success. Nurses and UAPs should be included in the selection and design process. Ongoing monitoring must be conducted to ensure adoption and celebrate improvements, which aren't possible without the team's willingness to adopt innovation and the organization's dedication to quality improvement. Another critical factor is leadership support to invest in technology that optimizes workflow, standardizes practices, and improves efficiency at the bedside. As nurse leaders, we must continually assess the work environment and workflow processes to identify opportunities to leverage technology to make improvements.


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