Title: Safer and more efficient vital signs monitoring to identify the deteriorating patient: An observational study towards deriving evidence-based protocols for patient surveillance on the general hospital ward
Funder: Department of Health and Social Care

Abstract: The frequency at which patients should have their vital signs (e.g. blood pressure, pulse, oxygen saturations) measured on general medical and surgical wards is currently unknown. Monitoring protocols in use at present are based on expert opinion[1–3], but supported by little empirical evidence[4]. A key conclusion of national audits of NHS hospitals[5,6] is that inadequate patient surveillance contributes to avoidable harm through a failure to detect patient deterioration, and risks missing early signs of deterioration and delaying remedial treatment. In contrast, over-observation of stable patients wastes valuable nursing resources that could be better deployed to other essential aspects of patient care. Using our unique database of vital signs, this study will be the first to guide hospitals on how best to target observations, irrespective of the system or early warning score used to record them. This is a retrospective study using two large databases of vital signs observations from patients on general medical and surgical wards in Portsmouth and Oxford. Data at both sites was recorded via electronic devices at the patient’s bedside, in the Vitalpac™ and SEND systems. By linking these vital signs to the patient administration, intensive care unit (ICU) and cardiac arrest databases, the study will create two large longitudinal data sets to explore the relationship between changes in vital signs and adverse events over time. Data from Portsmouth will be used for model development, with predictions validated on the Oxford cohort. To explore this, we will develop continuous time state-space models (e.g. Hidden Markov Models) of the patient population to estimate the risk of future deterioration, given a patient’s current acuity. To ensure our models are robust, we will use a range of early warning scores (such as the National Early Warning Score (NEWS)[1] and the Centile Early Warning Score(CEWS) [7]) as measures of clinically significant changes in physiology. Data from cardiac arrests, ICU admission and death will also be incorporated into our models in order to map the risk of these adverse events over time. The results of these models will allow us to predict the expected time of onset of deterioration, given a set of vital sign measurements. Estimates from our models will then be used to design a range of safe, simple monitoring protocols, based on patient acuity, to target observations to patients at risk of deterioration. These protocols will be validated on data from Oxford. In parallel, we will undertake observations of nursing care to estimate the time taken to obtain vital sign observations and (where necessary) initiate an appropriate clinical response, and use these to estimate the expected workload and costs generated by different approaches to patient surveillance. This will form part of an economic analysis of the costs and consequences of our novel monitoring protocols. The ultimate aim of the study is to derive the first evidenced-based protocol for patient surveillance, which will be both safe and achievable across all acute NHS hospitals, independent of the system to record vital signs.

Lay abstract: Taking measurements of heart rate, blood pressure, temperature and other “vital signs” is an important part of care for nearly all patients in hospital. Staff and patients often refer to this as taking observations. Changes in observations are used to track recovery and can show when someone’s condition is getting worse and needs urgent attention. When changes are spotted early, medical staff can often prevent serious deterioration, provide early treatment and avoid serious consequences including death. However, taking observations can be burdensome to patients, interfering with rest and sleep, which are also important to recovery. Frequent observations also cause more work for nursing staff. At the moment, there is little evidence to guide hospital staff on how frequently to take observations. In the UK, the Royal College of Physicians and the National Institute for Clinical Excellence recommend that vital signs observations are combined into a single score (NEWS) that shows when the measurements are abnormal. There is now some evidence to support using the NEWS score to identify patients at increased risk of cardiac arrest, death or unexpected transfer to intensive care, so that staff can take preventative action. The guidance is also that the higher the NEWS score, the more often a patient should be observed. Although it is recommended that people with higher scores need more frequent observation, there is no direct evidence for this. We need to find out how often we need to monitor patients. Moreover, some observations could be unnecessary or too far apart to be useful in spotting deterioration. Our study aims to address this by developing a protocol for how frequently observations should be made. We will use records from two hospitals where vital signs are recorded in electronic systems. No personal information that identifies individual patients will be used. In total, 6 million measurements from over 200,000 hospital admissions are available. Using information from one hospital, we will calculate NEWS scores and look to see how these change over time, with the aim of identifying the earliest point possible where we might detect that a patient is deteriorating. By linking these measurements to other information (such as diagnoses, cardiac arrests, intensive care admissions), we will also be able to see the extent to which changes in vital signs affect patients’ risk of poor outcomes. The results of these analyses will be used to set monitoring schedules, which will then be tested on the patient data from the second hospital. Together with the results from a study where we watch and time ward staff taking observations, we will also be able to estimate how much work will be generated by each monitoring schedule and estimate the expected staff requirements. We aim for this study to provide the first evidenced-based protocol for patient monitoring, which will be both safe and achievable across all acute NHS hospitals.

Research activity codes: 7.3 MANAGEMENT AND DECISION MAKING
Health categories: GENERIC HEALTH RELEVANCE