52 research outputs found
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
Anticipating 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
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
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
Effect of introducing the Modified Early Warning score on clinical outcomes, cardio-pulmonary arrests and intensive care utilisation in acute medical admissions*
No full textCorrection to: Understanding what matters most to patients in acute care in seven countries, using the flash mob study design
No full textFollowing publication of the original article [1], the authors identified an error in the author name of Ling Yan LEUNG. The incorrect author name is: L. E. U. N. G. Ling Yan The correct author name is: Ling Yan LEUNG The author group has been updated above and the original article [1] has been corrected.</p
Changes in vital signs post discharge as a potential target for intervention to avoid readmission
No full textReadmissions are treated as adverse events in many healthcare systems. Causes can be physiological deterioration or breakdown of social support systems. We investigated data from a European multi-centre study of readmissions for changes in vital signs between index admission and readmission. Data sets were graded according to the National Early Warning Score (NEWS). Of 487 patients in whom NEWS could be calculated on discharge and again on re-admission, 39.6% had worse vital signs with a NEWS score difference ≥ 2 points while only 7.6% had improved by ≤ 2 points. Changes in individual vital signs of 20% or more were most common in respiratory rate and heart rate. Monitoring of respiratory rate and pulse rate post-discharge might predict some deteriorations.</p
Changes in vital signs post discharge as a potential target for intervention to avoid readmission
No full textReadmissions are treated as adverse events in many healthcare systems. Causes can be physiological deterioration or breakdown of social support systems. We investigated data from a European multi-centre study of readmissions for changes in vital signs between index admission and readmission. Data sets were graded according to the National Early Warning Score (NEWS). Of 487 patients in whom NEWS could be calculated on discharge and again on re-admission, 39.6% had worse vital signs with a NEWS score difference ≥ 2 points while only 7.6% had improved by ≤ 2 points. Changes in individual vital signs of 20% or more were most common in respiratory rate and heart rate. Monitoring of respiratory rate and pulse rate post-discharge might predict some deteriorations.</p
Readmissions of medical patients: an external validation of two existing prediction scores
No full textBACKGROUND: Hospital readmissions are increasingly used as a quality indicator with a belief that they are a marker of poor care and have led to financial penalties in UK and USA. Risk scoring systems, such as LACE and HOSPITAL, have been proposed as tools for identifying patients at high risk of readmission but have not been validated in international populations. AIM: To perform an external independent validation of the HOSPITAL and LACE scores. DESIGN: An unplanned secondary cohort study. METHODS: Patients admitted to the medical admission unit at the Hospital of South West Jutland (10/2008-2/2009; 2/2010-5/2010) and the Odense University Hospital (6/2009-8/2011) were analysed. Validation of the scores using 30 day readmissions as the endpoint was performed. RESULTS: A total of 19 277 patients fulfilled the inclusion criteria. Median age was 67 (range 18-107) years and 8977 (46.6%) were female. The LACE score had a discriminatory power of 0.648 with poor calibration and the HOSPITAL score had a discriminatory power of 0.661 with poor calibration. The HOSPITAL score was significantly better than the LACE score for identifying patients at risk of 30 day readmission (P < 0.001). The discriminatory power of both scores decreased with increasing age. CONCLUSION: Readmissions are a complex phenomenon with not only medical conditions contributing but also system, cultural and environmental factors exerting a significant influence. It is possible that the heterogeneity of the population and health care systems may prohibit the creation of a simple prediction tool that can be used internationally
Reliability of frailty assessment in the critically ill: a multicentre prospective observational study
No full textDemand for critical care among older patients is increasing in many countries. Assessment of frailty may inform discussions and decision making, but acute illness and reliance on proxies for history‐taking pose particular challenges in patients who are critically ill. Our aim was to investigate the inter‐rater reliability of the Clinical Frailty Scale for assessing frailty in patients admitted to critical care. We conducted a prospective, multi‐centre study comparing assessments of frailty by staff from medical, nursing and physiotherapy backgrounds. Each assessment was made independently by two assessors after review of clinical notes and interview with an individual who maintained close contact with the patient. Frailty was defined as a Clinical Frailty Scale rating > 4. We made 202 assessments in 101 patients (median (IQR [range]) age 69 (65–75 [60–80]) years, median (IQR [range]) Acute Physiology and Chronic Health Evaluation II score 19 (15–23 [7–33])). Fifty‐two (51%) of the included patients were able to participate in the interview; 35 patients (35%) were considered frail. Linear weighted kappa was 0.74 (95%CI 0.67–0.80) indicating a good level of agreement between assessors. However, frailty rating differed by at least one category in 47 (47%) cases. Factors independently associated with higher frailty ratings were: female sex; higher Acute Physiology and Chronic Health Evaluation II score; higher category of pre‐hospital dependence; and the assessor having a medical background. We identified a good level of agreement in frailty assessment using the Clinical Frailty Scale, supporting its use in clinical care, but identified factors independently associated with higher ratings which could indicate personal bias
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