61 research outputs found
A model-based cost-utility analysis of an automated notification system for deteriorating patients on general wards
No full textDelayed response to clinical deterioration of hospital inpatients is common. Deployment of an electronic automated advisory vital signs monitoring and notification system to signal clinical deterioration is associated with significant improvements in clinical outcomes but there is no evidence on the cost-effectiveness compared with routine monitoring, in the National Health Service (NHS) in the United Kingdom (UK). A decision analytic model was developed to estimate the cost-effectiveness of an electronic automated advisory notification system versus standard care, in adults admitted to a district general hospital. Analyses considered: (1) the cost-effectiveness of the technology based on secondary analysis of patient level data of 3787 inpatients in a before-and-after study; and (2) the cost-utility (cost per quality-adjusted life-year (QALY)) over a lifetime horizon, extrapolated using published data. Analysis was conducted from the perspective of the NHS. Uncertainty in the model was assessed using a range of sensitivity analyses. The study population had a mean age of 68 years, 48% male, with a median inpatient stay of 6 days. Expected life expectancy at discharge was assumed to be 17.74 years. (1) Cost-effectiveness analysis: The automated notification system was more effective (-0.027 reduction in mean events per patient) and provided a cost saving of -£12.17 (-182.07 to 154.80) per patient admission. (2) Cost-utility analysis: Over a lifetime horizon the automated notification system was dominant, demonstrating a positive incremental QALY gain (0.0287 QALYs, equivalent to ~10 days of perfect health) and a cost saving of £55.35. At a threshold of £20,000 per QALY, the probability of automated monitoring being cost-effective in the NHS was 81%. Increased use of cableless sensors may reduce cost-savings, however, the intervention remains cost-effective at 100% usage (ICER: £3,107/QALY). Stratified cost-effectiveness analysis by age, National Early Warning Score (NEWS) on admission, and primary diagnosis indicated the automated notification system was cost-effective for most strategies and that use representative of the patient population studied was the most cost-saving strategy. Automated notification system for adult patients admitted to general wards appears to be a cost-effective use in the NHS; adopting this technology could be good use of scarce resources with significance for patient safety. [Abstract copyright: Copyright: © 2024 Holmes et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Acute Medicine: How will we grow? - An analysis of organisational capabilities for quality improvement, research & education from SAMBA 2021"
No full textBackground: Education, research, and Quality Improvement (QI) are key enablers for high quality care. We aimed to map the capability of Acute Medical Units (AMUs) to facilitate excellence in these areas.
Methods: AMUs were surveyed in an organisational questionnaire within the Society for Acute Medicine Benchmarking Audit 2021.
Results: 143 units participated. 80 units had a QI lead, 24 had a research lead and 99 had a medical education lead. 15 units had all three leadership roles. Most QI work considered service structure rather than changes in processes or care outcomes.
Conclusion: The organisational capability of AMUs in the strategic areas considered is variable. Improving leadership and disseminating learning could help build a strategic foundation for acute medicine to grow
Frailty measures in the critically ill: are we approaching a critical age? A systematic review
No full textAnticipating care needs of patients after discharge from hospital:Frail and elderly patients without physiological abnormality on day of admission are more likely to require social services input
No full textINTRODUCTION: Acute admissions to hospital are rising. As a part of a service evaluation we examined pathways of patients following hospital discharge depending on data available on admission to hospital.METHODS: We merged data available on admission to the Wrexham Maelor hospital from an existing data-base in the Acute Medical Unit with follow up data from local social services as part of a data sharing agreement. Patients requiring support by social services post-discharge were matched with patients not requiring social services from the same post-code.RESULTS: Stepwise logistic regression analysis identified candidate variables predicting likely support need. Decision tree analysis identified sub-groups of patients with higher likelihood to require support by social services after discharge from hospital. We found patients with normal physiology on admission as evidenced by a value of zero for the National Early Warning Score who were frail or older than 85years were most likely to require support after discharge.CONCLUSIONS: Information available on admission to hospital might inform long term care needs. Prospective testing is needed. The algorithms are prone to be dependent on availability of local services but our methodology is expected to be transferable to other organizations.</p
Acute care service performance during winter : report from the Winter SAMBA 2020 national audit of acute care
No full textThe Winter Society for Acute Medicine Benchmarking Audit (SAMBA) provides the first comparison of performance within acute medicine against clinical quality indicators during winter, a time of increased pressure and demand on acute services. 105 hospitals participated in Winter SAMBA, collecting data over 24-hours on 30th January 2020. 5626 patients
Evaluating acute medical service performance against assessment time metrics:the Society for Acute Medicine Benchmarking Audit 2023 (SAMBA23)
No full textPerformance within acute medicine services is impacted by ongoing pressures on acute care services. Data from the Society for Acute Medicine Benchmarking Audit 2023 (SAMBA23), was used to assess performance of acute medicine services compared to key clinical quality indicators, comparing performance by initial assessment location. Data was analysed for 8213 unplanned attendances across 161 hospitals. Comparing by initial assessment location, performance against the clinical quality indicators was unchanged from 2022. Only 29% of daytime arrivals assessed within the Emergency Department received consultant review within target times. Delays were seen in transfer between acute care locations. 29% of patients requiring admission were not admitted to the AMU. There is ongoing variation in acute medical service performance nationally, with significant delays in patient access to appropriate assessment locations.</p
Society for Acute Medicine Benchmarking Audit 2019 (SAMBA19): Trends in Acute Medical Care.
No full textntroductionThe eighth Society for Acute Medicine Benchmarking Audit (SAMBA19) took place on Thursday 27th June 2019. SAMBA gives a broad picture of acute medical care in the UK and allows individual units to compare their performance against their peers.MethodAll UK hospitals were invited to participate. Unit and patient level were collected. Data were analysed against published Clinical Quality indicators (CQI) and standards. This was the biggest SAMBA to date, with data from 7170 patients across 142 units in 140 hospitals.Results84.5% of patients had an Early Warning Score measured within 30 minutes of arrival in hospital (SAMBA18 84.1%), 90.4% of patients were seen by a competent clinical decision maker within four hours of arrival in hospital (SAMBA18 91.4 %) and 68.6% of patients were seen by a consultant within the timeframe standard (SAMBA18 62.7%). Ambulatory Emergency Care is provided in 99.3% of hospitals. 61.8% of patients are initially seen in the Emergency Department (ED). Since SAMBA18 death rates and planned discharge rates, while the use of NEWS2 increased from 2.5% to 59.2% of hospitals.ConclusionSAMBA19 highlighted the evolving complexity of acute medical pathways for patients. The challenge now is to increase sample frequency, assess the impact of SAMBA open a broader debate to define optimal CQIs
Effect of introducing the Modified Early Warning score on clinical outcomes, cardio-pulmonary arrests and intensive care utilisation in acute medical admissions*
No full textA Low-Power Simplified-MEWS Scoring device for Patient Monitoring
No full textThe Modified Early Warning System is a paper based system used in general wards of hospitals to monitor patients health during the duration of the patient stay. Using this system, patient deterioration/improvement can rapidly be detected so as to assist and alert healthcare providers. In this paper we describe a simplified MEWS device which assists healthcare providers in assessing several of the patients vitals quantitatively, so as to allow the provider to focus on a qualitative assessment of the patient
A new approach to scoring systems to improve identification of acute medical admissions that will require critical care
No full textRemoval of the intensive care unit (ICU) at the Vale of Leven Hospital mandated the identification and transfer out of those acute medical admissions with a high risk of requiring ICU. The aim of the study was to develop triaging tools that identified such patients and compare them with other scoring systems. The methodology included a retrospective analysis of physiological and arterial gas measurements from 1976 acute medical admissions produced PREEMPT-1 (PRE-critical Emergency Medical Patient Triage). A simpler one for ambulance use (PREAMBLE-1 [PRE-Admission Medical Blue-Light Emergency]) was produced by the addition of peripheral oxygen saturation to a modification of MEWS (Modified Early Warning Score). Prospective application of these tools produced a larger database of 4447 acute admissions from which logistic regression models produced PREEMPT-2 and PREAMBLE-2, which were then compared with the original systems and seven other early warning scoring systems. Results showed that in patients with arterial gases, the area under the receiver operator characteristic curve was significantly higher in PREEMPT-2 (89·1%) and PREAMBLE-2 (84.4%) than all other scoring systems. Similarly, in all patients, it was higher in PREAMBLE-2 (92·4%) than PREAMBLE-1 (88·1%) and the other scoring systems. In conclusion, risk of requiring ICU can be more accurately predicted using PREEMPT-2 and PREAMBLE-2, as described here, than by other early warning scoring systems developed over recent years
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