Practice Matters

Improving patient safety with a modified early warning scoring system

scoring system

The modified early warning system (MEWS) is a physiologic scoring system for bedside assessment of medical-surgical patients. Early detection of changes in a patient’s condition can make a life-saving difference. Research shows subtle vital-sign changes (especially in respiratory rate and level of consciousness [LOC]) usually precede in-hospital cardiac arrests and rapid response team (RRT) deployment. These changes commonly start 6 to 8 hours before the patient shows recognizable deterioration. Identifying patients at risk for deterioration and cardiopulmonary arrest and providing early intervention can reduce unplanned admissions to the intensive care unit (ICU), in-patient cardiac arrests, and deaths.

Designed for use with med-surg patients regardless of diagnosis, the MEWS screening tool has a numeric scale based on physiologic assessment criteria for screening and scoring patients. Parameters include respiratory rate, heart rate, systolic blood pressure, LOC, and body temperature. Some authors have suggested adding more parameters—usually urine output and oxygen saturation. 

Purpose of the MEWS project

The purpose of the project described in this article was to implement a MEWS screening tool on an adult thoracic med-surg unit and evaluate patient outcomes related to cardiac arrest, RRT deployment, and unplanned ICU admission. The project was implemented in a 520-bed tertiary-care hospital that’s part of a large health system in southwestern Pennsylvania. It was approved and designated as a quality-improvement project by the institutional review boards (IRB) of both the hospital where the project was conducted and the university where the project leader (the author) was a student.

Benefits of MEWS

Scoring vital signs and basic physiologic parameters removes subjectivity from patient assessment and gives healthcare professionals (especially novice nurses) confidence in seeking advice on how best to manage subtle changes in a patient’s condition. MEWS also helps quantify more experienced nurses’ intuitions that a patient is going to deteriorate, which often hinges on subtle changes in vital signs, LOC, and behavior before clinical signs of deterioration appear.

Algorithms for action formulated to accompany the MEWS scoring tool provide a consistent script and plan for nursing intervention and promote prompt communication between nurses and other care providers. A population- or hospital-specific algorithm can be used in conjunction with the MEWS score to increase frequency and consistency of assessing, recording, and analyzing vital sign data based on patient condition. Alternatively, the algorithm may direct nurses to call physicians for immediate help.

Most patients can be managed effectively on the med-surg unit if problems are identified early. Unplanned ICU transfers have negative implications for both patients and hospitals. Costs associated with ICU beds ($6,930/day) are much higher than those for general med-surg beds ($2,300/day) and monitored/telemetry beds ($3,020/day). Also, ICU patients are at higher risk for hospital-associated infections and complications related to invasive therapies (such as central lines, ventilators, and indwelling urinary catheters) and vasoactive medications. They’re also more likely to have longer stays or to require admission to a skilled nursing, long-term acute care, or rehabilitation facility on discharge from the acute-care hospital setting. (Note: Estimated bed costs come from the hospital where the MEWS pilot was conducted.)

Project methods

A multidisciplinary team comprised of the project leader, a quality-improvement specialist/sepsis team coordinator, pilot unit nursing director, and registered nurse clinicians from the pilot unit was formed to evaluate the literature on MEWS and choose an effective but easy-to-use MEWS screening tool to identify at-risk patients. The team focused on finding a basic tool in current published literature that had been used successfully to improve patient outcomes in the acute-care clinical setting. Once the team identified a basic MEWS scoring tool and a corresponding color-coded algorithm, they sought and obtained permission to use the tool for the project. Color coding, similar to traffic lights, provides visual guidance. Green represents the lowest score, corresponding to the most stable patient. As the score rises, the color changes from yellow to orange and then red, corresponding to potential serious clinical changes that should be reviewed carefully. The project theme, “Going Green,” emphasizes the need to keep patients safe. (See the box below.)


MEWS project screening tool and call-out algorithmThe MEWS screening tool used for this project scored and screened the patient’s temperature, heart rate, respiratory rate, systolic blood pressure and LOC. It was accompanied by a color-coded “call-out” algorithm with the lowest scores (0 to 1) appearing green and slightly increased scores (2 to 3) appearing yellow, indicating the need for increased caution with these patients. Orange was used for higher scores (4 to 5), indicating deterioration and the need for greater concern. Finally, red denoted a score of 6 or higher, meaning the patient was experiencing serious changes in condition that called for immediate action. For a patient with a rising score, the nurse should consider the context of the clinical situation and take appropriate nursing interventions, followed by reevaluation.This algorithm is called a call-out algorithm because the nurse should “call out” or notify the healthcare provider, of the rising MEWS score and changes in the patient’s condition to permit early intervention.MEWS (Modified Early Warning System)

On advice from the attending thoracic surgeon, the team agreed that a MEWS range of 2 to 3 (which corresponded with the yellow MEWS score range on the chosen algorithm) was an appropriate trigger range for the nurse to reassess the patient more frequently. If a readily identifiable cause of the score elevation existed (such as an elevated heart rate or blood pressure due to increased pain), the nurse implemented a nursing intervention, such as administering pain medication. If the score was 3 or higher with no readily identifiable reason for the elevation, or if the score wasn’t corrected when the patient was reassessed within an hour after a nursing intervention, the thoracic surgery team was notified.

Staff education

The pilot unit’s charge nurses, nursing supervisors, nursing staff, patient-care technicians (PCTs), unit coordinators, thoracic surgery attending physicians, affiliated residents, nurse practitioners, and physician assistants received education on MEWS and the care algorithm in the week before implementation. Education stressed that MEWS quantifies patient deterioration and condition changes. It included case studies in which early detection of declining patient condition using MEWS resulted in early intervention and positive patient outcomes, demonstrating efficacy of the MEWS tool. As part of the post-test, nurses demonstrated competency in calculating MEWS scores.

Pilot implementation

Each employee received a MEWS reference card containing the scoring tool and algorithm for quick reference; the card fit behind the employee identification badge. Laminated posters with the same information were posted on the unit. Patients received usual or standard care; the only change was that the MEWS score was calculated and the algorithm was to be followed for elevated scores.

PCTs obtained patients’ vital signs every 4 hours according to hospital routine. They recorded vital signs on data collection sheets that initially hung in the room on the patient’s bulletin board, and notified the nurse that this task was completed. Nurses were encouraged to calculate and record the MEWS score as soon as possible after vital-sign collection. (A definitive time frame wasn’t established by the project team for this action; hindsight indicates criteria should have been established to promote time-sensitive interventions for patients with elevated scores.)

For 2 months, all patients admitted to the thoracic surgery service line on the unit were included in the project, until sample size reached 50 patients. Patients were excluded from MEWS scoring if they were being discharged home for hospice care or were on hospice care in the hospital. However, patients with a “Do not resuscitate” order or “No code” designation weren’t excluded, because these designations don’t denote “Do not treat.” The pilot excluded only those patients who were designated to receive “comfort measures only” or were actively dying.

Each patient’s electronic health record (EHR) was accessed and retrospectively analyzed to evaluate use of the MEWS tool. Data were collected on compliance with completing the MEWS score, recognition of patient deterioration, and whether interventions were taken based on assessment findings and the MEWS score. The number and circumstances of RRT deployments, cardiac arrests, and unplanned ICU transfers were analyzed on the population.

Throughout the pilot, staff were supported and encouraged to perform MEWS scoring and follow the algorithm. During the first week of the pilot, the project leader conducted surveillance rounds twice daily. After that, she conducted rounds three to four times weekly for the remainder of the pilot, based on her full-time work schedule. Staff were interviewed to gain their perceptions of workflow and barriers to MEWS scoring. Staff members who were properly screening, scoring, and following the algorithm were commended, thanked, and encouraged to continue using MEWS. Whenever possible, barriers to MEWS use were mitigated in real-time.


During the pilot project, overall nursing staff reached 80% compliance with MEWS scoring every 4 hours Twenty-two (44%) of the 50 patients had MEWS scores of 3 or higher; of these, 18 (81.8%) were treated according to the algorithm. In 10 patients, nurses appropriately increased monitoring frequency or performed nursing interventions, such as administering pain medications. They called the thoracic surgery team 12 times, with 10 calls resulting in new orders and two calls leading to increased monitoring frequency. Twenty of the 22 patients (90.9%) were able to receive appropriate care on the nursing unit.

No cardiac arrests occurred in this population during the pilot project. One RRT was called for a patient who became acutely short of breath related to pulmonary edema. Review of MEWS scores didn’t identify this patient at risk during the 4-hour period before deterioration. Two other patients had unplanned ICU admissions; although the PCT had completed their vital signs, neither patient had real-time MEWS scoring completed by the nurse in the hours before ICU transfer.


In this project, the MEWS tool and algorithm proved to be an effective way to identify patients at risk for deterioration and to ensure early intervention to prevent complications. Similar findings have been reported in the literature. Of the four patients for whom a MEWS score wasn’t calculated, two were admitted to the ICU, representing missed opportunities for early intervention. MEWS scoring didn’t seem helpful for one patient whose condition deteriorated rapidly, but it’s unclear whether this represented an inherent weakness in the scoring system or stemmed from erroneous vital signs. Vital-signs analysis of three patients transferred to the ICU revealed respiratory rates consistently recorded as 16, 18, and 18 breaths/minute before transfer. However, on arrival to the ICU, their respiratory rates were assessed as 21, 27, and 30 breaths/minute respectively. Retrospective review of the patients’ clinical course before ICU transfer showed decreasing O2 sat levels, increasing supplemental O2 requirements, decreasing urine output, and significant mental-status changes (anxiety, confusion, or lethargy).

Facilitators and barriers

For MEWS screening and scoring to be effective, staff need to measure and record vital signs accurately and the nurse needs to intervene according to the calculated MEWS score. Previously, healthcare professionals believed the MEWS tool and algorithm could be implemented easily into practice because the screening tool quantifies work already done on a routine basis. However, analysis revealed concerns with documented respiratory rates.

 Barriers for PCTs

The project leader spent time with PCTs to gain an understanding of their barriers to accurately measuring and recording respiratory rates. The following barriers were identified:

  • A wall clock was used instead of a handheld timing device, such as a wristwatch, to assess respiratory rate. Use of a wall clock requires the PCT to look away from the patient’s chest when assessing visually, often missing respirations; this can lead to an inaccurate assessment.
  • Multipliers were used inconsistently when assessing the respiratory rate. Some PCTs counted for 15 seconds and multiplied by 4, whereas others counted for 20 seconds and multiplied by 3. However, in their education, they were taught to count the respiratory rate under direct visualization for 30 seconds and multiply by 2 if the respiratory rate is regular, or to count for a full minute if the rate is irregular.
  • PCTs identified patients talking during assessment as an obstacle to accurate respiratory rate assessment.

To improve the accuracy of respiratory rate measurement and documentation, the project leader carried out the following interventions:

  • emphasized the value and importance of PCTs in patient-related nursing and medical decisions, based on accuracy of vital-sign assessment
  • developed an education program for PCTs called “Vital Signs are VITAL!”
  • counted respiratory rates with PCTs using different methods, multipliers, and timing devices to demonstrate inconsistency and potential inaccuracies in respiratory rate assessment
  • offered PCTs suggestions on how to distract talkative patients by leaving the thermometer in the patient’s mouth while counting the respiratory rate or holding the patient’s wrist in a pulse-counting position while continuing to count the respiratory rate.

Also, the hospital’s nurse executive committee added a wristwatch to the PCT dress code and recommended changes to PCT education—specifically, use of a handheld timing device rather than a wall clock to measure respiratory rates.

Barriers for nurses

As described earlier, two patients requiring transfer to the ICU had vital-sign changes and MEWS scores of 3 or higher; nurses hadn’t calculated their MEWS scores or noticed their condition changes. Common barriers to nurses’ scoring were identified during surveillance rounds, and attempts were made to overcome them.

  • The initial barrier was that nurses were forgetting to score patients because data collection sheets were in patients’ rooms. This was resolved by moving the data collection sheet outside the room (positioned so it faced the wall and all patient-identifiers were concealed to comply with HIPPA regulations).
  • Another barrier was the time required to manually complete real-time scoring; some nurses put off scoring until later in the day. To mitigate this, staff received education and reinforcement that MEWS is a real-time screening tool to identify patients at risk for deterioration early, in an effort to prevent complications and clinical deterioration that could necessitate ICU transfer. Patients transferred to the ICU were used as case examples of opportunities for improvement. As time passed, the barrier of “forgetting” to score resurfaced, despite patients’ rooms being clearly demarcated with a MEWS tag and the data collection sheet hanging outside the room. As a result, a reminder to perform MEWS scoring was added to the unit’s morning huddle and the charge nurse’s rounds each shift.


  • Because this pilot was designed as a single hospital-based quality improvement project, outcomes can’t be generalized to other settings.
  • The small sample size, especially of patients who required transfer to the ICU, may have affected reported outcomes.
  • Although MEWS is designed for use with all med-surg patients, the pilot was completed only on patients admitted to the thoracic surgery service.
  • Data collection and statistics were negatively affected by nurses’ increased workload resulting from the need to manually calculate and score MEWS during the pilot.

Consequently, methods should be explored for calculating the MEWS score electronically within the EHR. Since the pilot was completed, the hospital’s information technology department has been working to redesign the EHR so MEWS scoring is calculated automatically when the patient’s vital signs are entered. Currently, the hospital is in the process of implementing the early warning system into the EHR.


The MEWS tool is a promising assessment and communication tool for early identification of patients at risk for clinical deterioration. The tool and algorithm used in this pilot didn’t take into consideration O2 sat, supplemental O2 requirements, or urine output. However, all patients who were transferred to the ICU during the pilot had increasing O2 requirements, decreasing O2 sat, mental-status changes (such as increasing confusion), and reduced urine output. (Note: For this project, the MEWS tool didn’t initially include O2 sat in MEWS score calculation. However, PCTs recorded O2 sat so data could be compiled on the potential significance and impact on scoring, as some tools do score O2 sat. After the project, experts recommended that scoring include O2 sat and supplemental O2. The early warning system implemented in the EHR will include O2 sat, supplemental O2, and urine output.)

Healthcare facilities should consider including O2 sat, supplemental O2, and urine output in the EHR as MEWS scoring and screening parameters. Other published literature has demonstrated and supported this action. Although MEWS isn’t meant to replace current care or nursing assessment, this project demonstrates that it’s useful as a screening and decision tool.

Tara Kay Race is a faculty member at UPMC Shadyside School of Nursing in Pittsburgh, Pennsylvania.

Selected references

Cei M, Bartolomei C, Mumoli N. In-hospital mortality and morbidity of elderly medical patients can be predicted at admission by the Modified Early Warning Score: a prospective study. Int J Clin Pract. 2009;63(4):591-5.

Duncan KD, McMullan C, Mills BM. Early warning systems: the next level of rapid response. Nursing. 2012;42(2):39-44.

Gardner-Thorpe J, Love N, Wrightson J, et al. The value of modified early warning score (MEWS) in surgical in-patients: a prospective observational study. Ann R Coll Surg Engl. 2006;88(6):571-5.

Mapp ID, Davis LL, Krowchuk H. Prevention of unplanned intensive care unit admissions and hospital mortality by early warning systems. Dimens Crit Care Nurs. 2013;32(6):300-9.

Moon A, Cosgrove JF, Lea D, et al. An eight year audit before and after the implementation of modified early warning score (MEWS) charts, of patients admitted to a tertiary referral intensive care unit after CPR. Resuscitation. 2011;82(2):150-4.

Scott RD. The direct medical costs of health care associated infections in U.S. hospitals and the benefits of prevention. Centers for Disease Control and Prevention, March 2009.

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