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.

Trust, trustworthiness and sharing patient data for research.

When it comes to using patient data from the National Health Service (NHS) for research, we are often told that it is a matter of trust: we need to trust, we need to build trust, we need to restore trust. Various policy papers and reports articulate and develop these ideas and make very important contributions to public dialogue on the trustworthiness of our research institutions. But these documents and policies are apparently constructed with little sustained reflection on the nature of trust and trustworthiness, and therefore are missing important features that matter for how we manage concerns related to trust. We suggest that what we mean by 'trust' and 'trustworthiness' matters and should affect the policies and guidance that govern data sharing in the NHS. We offer a number of initial, general reflections on the way in which some of these features might affect our approach to principles, policies and strategies that are related to sharing patient data for research. This paper is the outcome of a 'public ethics' coproduction activity which involved members of the public and two academic ethicists. Our task was to consider collectively the accounts of trust developed by philosophers as they applied in the context of the NHS and to coproduce an argumentative position relevant to this context.

Economic and technical assessment of rooftop solar photovoltaic potential in Brownsville, Texas, U.S.A.

Localized assessment of solar energy economic feasibility will benefit the structuring of residential solar energy deployment globally. In the U.S. growing interest in rooftop residential solar among city managers has spurred the development of photovoltaic (PV) feasibility maps of the technical and economic solar potential within cities. The City of Brownsville, Texas was interested in evaluating solar feasibility for their city but lacked information to make informed policy decisions on PV development. This paper presents novel and systems approaches for determining the technical and economic feasibility of solar development for homes in the Brownsville using LiDAR and local information. Residential technical and economic potential was assessed by optimizing the internal rate of return (IRR) and an average residential building demand profile to determine ideal size and placement of solar arrays. Results showed that residential structures in Brownsville have the technical potential to generate approximately 11% of the total energy provided by the local utility; however, average IRR was only 2.9% with a payback period of over 15 years. Five neighborhoods in the City of Brownsville were identified with spatially clustered homes that had relatively higher IRRs compared with other areas in the city. Despite the high technical potential, modeled results indicate that perspective home owners interested in solar development may require additional incentives to improve the economic feasibility of PV in Brownsville. This study provides a demonstration of an interdisciplinary systems approach and methodology that can be adopted internationally to evaluate the feasibility of solar development in other areas.

Comparison of Medical Priority Dispatch (MPD) and Criteria Based Dispatch (CBD) relating to cardiac arrest calls.

BACKGROUND: Prompt emergency medical service (EMS) system activation with rapid delivery of pre-hospital treatment is essential for patients suffering out-of-hospital cardiac arrest (OHCA). The two most commonly used dispatch tools are Medical Priority Dispatch (MPD) and Criteria Based Dispatch (CBD). We compared cardiac arrest call processing using these two dispatch tools in two different dispatch centres. METHODS: Observational study of adult EMS confirmed (non-EMS witnessed) OHCA calls during one year in Richmond, USA (MPD) and Oslo, Norway (CBD). Patients receiving CPR prior to call, interrupted calls or calls where the caller did not have access to the patients were excluded from analysis. Dispatch logs, ambulance records and digitalized dispatcher and caller voice recordings were compared. RESULTS: The MPDS-site processed 182 cardiac arrest calls and the CBD-site 232, of which 100 and 140 calls met the inclusion criteria, respectively. The recognition of cardiac arrest was not different in the MPD and CBD systems; 82% vs. 77% (p=0.42), and pre-EMS arrival CPR instructions were offered to 81% vs. 74% (p=0.22) of callers, respectively. Time to ambulance dispatch was median (95% confidence interval) 15 (13, 17) vs. 33 (29, 36) seconds (p<0.001) and time to chest compression delivery; 4.3 (3.7, 4.9) vs. 3.7 (3.0, 4.1)min for the MPD and CBD systems, respectively (p=0.05). CONCLUSION: Pre-arrival CPR instructions were offered faster and more frequently in the CBD system, but in both systems chest compressions were delayed 3-4min. Earlier recognition of cardiac arrest and improved CPR instructions may facilitate earlier lay rescuer CPR.