Safer and more efficient vital signs monitoring protocols to identify the deteriorating patients in the general hospital ward: an observational study.

Background: The frequency at which patients should have their vital signs (e.g. blood pressure, pulse, oxygen saturation) measured on hospital wards is currently unknown. Current National Health Service monitoring protocols are based on expert opinion but supported by little empirical evidence. The challenge is finding the balance between insufficient monitoring (risking missing early signs of deterioration and delays in treatment) and over-observation of stable patients (wasting resources needed in other aspects of care). Objective: Provide an evidence-based approach to creating monitoring protocols based on a patient's risk of deterioration and link these to nursing workload and economic impact. Design: Our study consisted of two parts: (1) an observational study of nursing staff to ascertain the time to perform vital sign observations; and (2) a retrospective study of historic data on patient admissions exploring the relationships between National Early Warning Score and risk of outcome over time. These were underpinned by opinions and experiences from stakeholders. Setting and participants: Observational study: observed nursing staff on 16 randomly selected adult general wards at four acute National Health Service hospitals. Retrospective study: extracted, linked and analysed routinely collected data from two large National Health Service acute trusts; data from over 400,000 patient admissions and 9,000,000 vital sign observations. Results: Observational study found a variety of practices, with two hospitals having registered nurses take the majority of vital sign observations and two favouring healthcare assistants or student nurses. However, whoever took the observations spent roughly the same length of time. The average was 5:01 minutes per observation over a 'round', including time to locate and prepare the equipment and travel to the patient area. Retrospective study created survival models predicting the risk of outcomes over time since the patient was last observed. For low-risk patients, there was little difference in risk between 4 hours and 24 hours post observation. Conclusions: We explored several different scenarios with our stakeholders (clinicians and patients), based on how 'risk' could be managed in different ways. Vital sign observations are often done more frequently than necessary from a bald assessment of the patient's risk, and we show that a maximum threshold of risk could theoretically be achieved with less resource. Existing resources could therefore be redeployed within a changed protocol to achieve better outcomes for some patients without compromising the safety of the rest. Our work supports the approach of the current monitoring protocol, whereby patients' National Early Warning Score 2 guides observation frequency. Existing practice is to observe higher-risk patients more frequently and our findings have shown that this is objectively justified. It is worth noting that important nurse-patient interactions take place during vital sign monitoring and should not be eliminated under new monitoring processes. Our study contributes to the existing evidence on how vital sign observations should be scheduled. However, ultimately, it is for the relevant professionals to decide how our work should be used. Study registration: This study is registered as ISRCTN10863045. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: 17/05/03) and is published in full in Health and Social Care Delivery Research; Vol. 12, No. 6. See the NIHR Funding and Awards website for further award information.

Patient recovery in hospital is tracked by measuring heart rate, blood pressure and other 'vital signs' and converting them into a score. These are 'observed' regularly by nursing staff so that deterioration can be spotted early. However, taking observations can disturb patients, and taking them too often causes extra work for staff. More frequent monitoring is recommended for higher scores, but evidence is lacking. To work out how often patients should be monitored, we needed to know how likely it is for patients to become more unwell between observations. We analysed over 400,000 patient records from two hospitals to understand how scores change with time. We looked at three of the most serious risks for patients in hospital. These risks are dying, needing intensive care or having a cardiac arrest. We also looked at the risk that a patient's condition would deteriorate significantly before their measurements were taken again. We identified early signs of deterioration and how changes in vital signs affected the risk of a patient's condition becoming worse. From this we calculated a maximum risk of deterioration. We then calculated different monitoring schedules that keep individual patients below this risk level. Some of those would consume less staff time than current National Health Service guidelines suggest. We also watched staff record patients' vital signs. We learnt it takes about 5 minutes to take these measurements from each patient. This information helped us calculate how costs would change if patients' vital signs were taken more or less often. We found that patients with a low overall score could have their vital signs monitored less often without being in danger of serious harm. This frees up nursing time so that patients with a higher score can be monitored more often. Importantly, this can be achieved without employing more staff.

What impact does nursing care left undone have on patient outcomes? Review of the literature.

AIMS AND OBJECTIVES: Systematic review of the impact of missed nursing care on outcomes in adults, on acute hospital wards and in nursing homes. BACKGROUND: A considerable body of evidence supports the hypothesis that lower levels of registered nurses on duty increase the likelihood of patients dying on hospital wards, and the risk of many aspects of care being either delayed or left undone (missed). However, the direct consequence of missed care remains unclear. DESIGN: Systematic review. METHODS: We searched Medline (via Ovid), CINAHL (EBSCOhost) and Scopus for studies examining the association of missed nursing care and at least one patient outcome. Studies regarding registered nurses, healthcare assistants/support workers/nurses' aides were retained. Only adult settings were included. Because of the nature of the review, qualitative studies, editorials, letters and commentaries were excluded. PRISMA guidelines were followed in reporting the review. RESULTS: Fourteen studies reported associations between missed care and patient outcomes. Some studies were secondary analyses of a large parent study. Most of the studies used nurse or patient reports to capture outcomes, with some using administrative data. Four studies found significantly decreased patient satisfaction associated with missed care. Seven studies reported associations with one or more patient outcomes including medication errors, urinary tract infections, patient falls, pressure ulcers, critical incidents, quality of care and patient readmissions. Three studies investigated whether there was a link between missed care and mortality and from these results no clear associations emerged. CONCLUSIONS: The review shows the modest evidence base of studies exploring missed care and patient outcomes generated mostly from nurse and patient self-reported data. To support the assertion that nurse staffing levels and skill mix are associated with adverse outcomes as a result of missed care, more research that uses objective staffing and outcome measures is required. RELEVANCE TO CLINICAL PRACTICE: Although nurses may exercise judgements in rationing care in the face of pressure, there are nonetheless adverse consequences for patients (ranging from poor experience of care to increased risk of infection, readmissions and complications due to critical incidents from undetected physiological deterioration). Hospitals should pay attention to nurses' reports of missed care and consider routine monitoring as a quality and safety indicator.

A Comparison of the Ability of the Physiologic Components of Medical Emergency Team Criteria and the U.K. National Early Warning Score to Discriminate Patients at Risk of a Range of Adverse Clinical Outcomes.

OBJECTIVE: To compare the ability of medical emergency team criteria and the National Early Warning Score to discriminate cardiac arrest, unanticipated ICU admission and death within 24 hours of a vital signs measurement, and to quantify the associated workload. DESIGN: Retrospective cohort study. SETTING: A large U.K. National Health Service District General Hospital. PATIENTS: Adults hospitalized from May 25, 2011, to December 31, 2013. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We applied the National Early Warning Score and 44 sets of medical emergency team criteria to a database of 2,245,778 vital signs sets (103,998 admissions). The National Early Warning Score's performance was assessed using the area under the receiver-operating characteristic curve and compared with sensitivity/specificity for different medical emergency team criteria. Area under the receiver-operating characteristic curve (95% CI) for the National Early Warning Score for the combined outcome (i.e., death, cardiac arrest, or unanticipated ICU admission) was 0.88 (0.88-0.88). A National Early Warning Score value of 7 had sensitivity/specificity values of 44.5% and 97.4%, respectively. For the 44 sets of medical emergency team criteria studied, sensitivity ranged from 19.6% to 71.2% and specificity from 71.5% to 98.5%. For all outcomes, the position of the National Early Warning Score receiver-operating characteristic curve was above and to the left of all medical emergency team criteria points, indicating better discrimination. Similarly, the positions of all medical emergency team criteria points were above and to the left of the National Early Warning Score efficiency curve, indicating higher workloads (trigger rates). CONCLUSIONS: When medical emergency team systems are compared to a National Early Warning Score value of greater than or equal to 7, some medical emergency team systems have a higher sensitivity than National Early Warning Score values of greater than or equal to 7. However, all of these medical emergency team systems have a lower specificity and would generate greater workloads.

Can binary early warning scores perform as well as standard early warning scores for discriminating a patient's risk of cardiac arrest, death or unanticipated intensive care unit admission?

INTRODUCTION: Although the weightings to be summed in an early warning score (EWS) calculation are small, calculation and other errors occur frequently, potentially impacting on hospital efficiency and patient care. Use of a simpler EWS has the potential to reduce errors. METHODS: We truncated 36 published 'standard' EWSs so that, for each component, only two scores were possible: 0 when the standard EWS scored 0 and 1 when the standard EWS scored greater than 0. Using 1564,153 vital signs observation sets from 68,576 patient care episodes, we compared the discrimination (measured using the area under the receiver operator characteristic curve--AUROC) of each standard EWS and its truncated 'binary' equivalent. RESULTS: The binary EWSs had lower AUROCs than the standard EWSs in most cases, although for some the difference was not significant. One system, the binary form of the National Early Warning System (NEWS), had significantly better discrimination than all standard EWSs, except for NEWS. Overall, Binary NEWS at a trigger value of 3 would detect as many adverse outcomes as are detected by NEWS using a trigger of 5, but would require a 15% higher triggering rate. CONCLUSIONS: The performance of Binary NEWS is only exceeded by that of standard NEWS. It may be that Binary NEWS, as a simplified system, can be used with fewer errors. However, its introduction could lead to significant increases in workload for ward and rapid response team staff. The balance between fewer errors and a potentially greater workload needs further investigation.

Are observation selection methods important when comparing early warning score performance?

INTRODUCTION: Sicker patients generally have more vital sign assessments, particularly immediately before an adverse outcome, and especially if the vital sign monitoring schedule is driven by an early warning score (EWS) value. This lack of independence could influence the measured discriminatory performance of an EWS. METHODS: We used a population of 1564,143 consecutive vital signs observation sets collected as a routine part of patients' care. We compared 35 published EWSs for their discrimination of the risk of death within 24h of an observation set using (1) all observations in our dataset, (2) one observation per patient care episode, chosen at random and (3) one observation per patient care episode, chosen as the closest to a randomly selected point in time in each episode. We compared the area under the ROC curve (AUROC) as a measure of discrimination for each of the 35 EWSs under each observation selection method and looked for changes in their rank order. RESULTS: There were no significant changes in rank order of the EWSs based on AUROC between the different observation selection methods, except for one EWS that included age among its components. Whichever method of observation selection was used, the National Early Warning Score (NEWS) showed the highest discrimination of risk of death within 24h. AUROCs were higher when only one observation set was used per episode of care (significantly higher for many EWSs, including NEWS). CONCLUSIONS: Vital sign measurements can be treated as if they are independent - multiple observations can be used from each episode of care--when comparing the performance and ranking of EWSs, provided no EWS includes age.

Aggregate National Early Warning Score (NEWS) values are more important than high scores for a single vital signs parameter for discriminating the risk of adverse outcomes.

INTRODUCTION: The Royal College of Physicians (RCPL) National Early Warning Score (NEWS) escalates care to a doctor at NEWS values of ≥5 and when the score for any single vital sign is 3. METHODS: We calculated the 24-h risk of serious clinical outcomes for vital signs observation sets with NEWS values of 3, 4 and 5, separately determining risks when the score did/did not include a single score of 3. We compared workloads generated by the RCPL's escalation protocol and for aggregate NEWS value alone. RESULTS: Aggregate NEWS values of 3 or 4 (n=142,282) formed 15.1% of all vital signs sets measured; those containing a single vital sign scoring 3 (n=36,207) constituted 3.8% of all sets. Aggregate NEWS values of either 3 or 4 with a component score of 3 have significantly lower risks (OR: 0.26 and 0.53) than an aggregate value of 5 (OR: 1.0). Escalating care to a doctor when any single component of NEWS scores 3 compared to when aggregate NEWS values ≥5, would have increased doctors' workload by 40% with only a small increase in detected adverse outcomes from 2.99 to 3.08 per day (a 3% improvement in detection). CONCLUSIONS: The recommended NEWS escalation protocol produces additional work for the bedside nurse and responding doctor, disproportionate to a modest benefit in increased detection of adverse outcomes. It may have significant ramifications for efficient staff resource allocation, distort patient safety focus and risk alarm fatigue. Our findings suggest that the RCPL escalation guidance warrants review.

Development and validation of a decision tree early warning score based on routine laboratory test results for the discrimination of hospital mortality in emergency medical admissions.

AIM OF STUDY: To build an early warning score (EWS) based exclusively on routinely undertaken laboratory tests that might provide early discrimination of in-hospital death and could be easily implemented on paper. MATERIALS AND METHODS: Using a database of combined haematology and biochemistry results for 86,472 discharged adult patients for whom the admission specialty was Medicine, we used decision tree (DT) analysis to generate a laboratory decision tree early warning score (LDT-EWS) for each gender. LDT-EWS was developed for a single set (n=3496) (Q1) and validated in 22 other discrete sets each of three months long (Q2, Q3…Q23) (total n=82,976; range of n=3428 to 4093) by testing its ability to discriminate in-hospital death using the area under the receiver-operating characteristic (AUROC) curve. RESULTS: The data generated slightly different models for male and female patients. The ranges of AUROC values (95% CI) for LDT-EWS with in-hospital death as the outcome for the validation sets Q2-Q23 were: 0.755 (0.727-0.783) (Q16) to 0.801 (0.776-0.826) [all patients combined, n=82,976]; 0.744 (0.704-0.784, Q16) to 0.824 (0.792-0.856, Q2) [39,591 males]; and 0.742 (0.707-0.777, Q10) to 0.826 (0.796-0.856, Q12) [43,385 females]. CONCLUSIONS: This study provides evidence that the results of commonly measured laboratory tests collected soon after hospital admission can be represented in a simple, paper-based EWS (LDT-EWS) to discriminate in-hospital mortality. We hypothesise that, with appropriate modification, it might be possible to extend the use of LDT-EWS throughout the patient's hospital stay.