Fifteen-year outcomes of an acute medical admission unit

Effects of a medical admission unit on in-hospital patient flow and clinical outcomes

BACKGROUND

the burden of acute complex patients, increasingly older and poli-pathological, accessing to Emergency Departments (ED) leads up hospital overcrowding and the outlying phenomenon. These issues highlight the need for new adequate patients' management strategies. The aim of this study is to analyse the effects on in-hospital patient flow and clinical outcomes of a high-technology and time-limited Medical Admission Unit (MAU) run by internists.

METHODS

all consecutive patients admitted to MAU from Dec-2017 to Nov-2019 were included in the study. The admissions number from ED and hospitalization rate, the overall in-hospital mortality rate in medical department, the total days of hospitalization and the overall outliers bed days were compared to those from the previous two years.

RESULTS

2162 patients were admitted in MAU, 2085(95.6%) from ED, 476(22.0%) were directly discharged, 88(4.1%) died and 1598(73.9%) were transferred to other wards, with a median in-MAU time of stay of 64.5 [0.2-344.2] hours. Comparing the 24 months before, despite the increase in admissions/year from ED in medical department (3842 ± 106 in Dec2015-Nov2017 vs 4062 ± 100 in Dec2017-Nov2019, p<0.001), the number of the outlier bed days has been reduced, especially in surgical department (11.46 ± 6.25% in Dec2015-Nov2017 vs 6.39 ± 3.08% in Dec2017-Nov2019, p=0.001), and mortality in medical area has dropped from 8.74 ± 0.37% to 7.29 ± 0.57%, p<0.001.

CONCLUSIONS

over two years, a patient-centred and problem-oriented approach in a medical admission buffer unit run by internists has ensured a constant flow of acute patients with positive effects on clinical risk and quality of care reducing medical outliers and in-hospital mortality.

Reduced 30-day in-hospital but increased long-term mortality for weekend vs weekday acute medical admission

BACKGROUND

Acute medical admission at the weekend has been reported to be associated with increased mortality. We aimed to assess 30-day in-hospital mortality and subsequent follow-up of all community deaths following discharge for acute medical admission to our institution over 21 years.

METHODS

We employed a database of all acute medical admissions to our institution over 21 years (2002-2023). We compared 30-day in-hospital mortality by weekend (Saturday/Sunday) or weekday (Tuesday/Wednesday) admission. Outcome post-discharge was determined from the National Death Register to December 2021. Predictors of 30-day in-hospital and long-term mortality were analysed by logistic regression or Cox proportional hazards models.

RESULTS

The study population consisted of 109,232 admissions in 57,059 patients. A weekend admission was associated with a reduced 30-day in-hospital mortality, odds ratio (OR) 0.70 (95%CI 0.65, 0.76). Major predictors of 30-day in-hospital mortality were acute illness severity score (AISS) OR 6.9 (95%CI 5.5, 8.6) and comorbidity score OR 2.4 (95%CI 1.2, 4.6). At a median follow-up of 5.9 years post-discharge, 19.0% had died. The strongest long-term predictor of mortality was admission AISS OR 6.7 (95%CI 4.6, 9.9). The overall survival half-life after hospital discharge was 16.6 years. Survival was significantly worse for weekend admissions at 20.8 years compared to weekday admissions at 13.3 years.

CONCLUSION

Weekend admission of acute medical patients is associated with reduced 30-day in-hospital mortality but reduced long-term survival.

Short- and long-term mortality following acute medical admission

BACKGROUND

Short-term in-hospital mortality following acute medical admission has been widely investigated. Longer term mortality, particularly out-of-hospital mortality, has been less well studied.

AIM

The aim of this study is to evaluate short- and long-term mortality, and predictors of such, following acute medical admission.

DESIGN

Retrospective database study.

METHODS

We evaluated all acute medical admissions to our institution over 10 years (2002-11) with a minimum of a further 10 years follow-up to 2021 using the Irish National Death Register. Predictors of 30-day in-hospital and long-term mortality were analysed with logistic and Cox regression, with loss of life years estimated.

RESULTS

The 2002-11 cohort consisted of 62 184 admissions in 35 140 patients. 30-Day in hospital mortality (n = 3646) per patient was 10.4% and per admission was 5.9%. There were an additional 11 440 longer-term deaths by 2021-total mortality was 15 086 (42.9%). Deaths post hospital discharge had median age at admission of 75.4 years [interquartile range (IQR) 63.7, 82.8] and died at median age of 80 years (IQR 69, 87). The half-life of survival following admission was 195 months-representing a short fall of 8 life years (32.9%) compared with the projected population reference of 24.3 years. Age [odds ratio (OR) 1.73 (95% confidence interval (CI) 1.64, 1.81)], acute illness severity score [OR 1.39 (95% CI 1.36, 1.43)] and comorbidity score [OR 1.09 (95% CI 1.08, 1.10)] predicted long-term mortality.

CONCLUSION

Similar factors influence both short- and long-term mortality following acute medical admission, the magnitude of effect is attenuated over time.

Red Cell Distribution Width as a Prognostic Indicator in Acute Medical Admissions

The red cell distribution width (RDW) is the coefficient of variation of the mean corpuscular volume (MCV). We sought to evaluate RDW as a predictor of outcomes following acute medical admission. We studied 10 years of acute medical admissions (2002-2011) with subsequent follow-up to 2021. RDW was converted to a categorical variable, Q1 < 12.9 fl, Q2-Q4 ≥ 12.9 and <15.7 fL and Q5 ≥ 15.7 fL. The predictive value of RDW for 30-day in-hospital and long-term mortality was evaluated with logistic and Cox regression modelling. Adjusted odds ratios (aORs) were calculated and loss of life years estimated. There were 62,184 admissions in 35,140 patients. The 30-day in-hospital mortality (n = 3646) occurred in 5.9% of admissions. An additional 15,086 (42.9%) deaths occurred by December 2021. Admission RDW independently predicted 30-day in-hospital mortality aOR 1.93 (95%CI 1.79, 2.07). Admission RDW independently predicted long-term mortality aOR 1.04 (95%CI 1.02, 1.05). Median survival post-admission was 189 months. For those with admission RDW in Q5, observed survival half-life was 133 months-this represents a shortfall of 5.7 life years (33.9%). In conclusion, admission RDW independently predicts 30-day in-hospital and long-term mortality.

Prognostic value and clinical utility of NT-proBNP in acute emergency medical admissions

BACKGROUND

NT-proB-type natriuretic peptide (NT-proBNP) is a frequently utilized test in congestive cardiac failure. There is little data on its utility in unselected emergency medical admissions.

AIM

This study aims to investigate the clinical utility and prognostic value of NT-proBNP in emergency medical admissions and to determine whether such testing influenced downstream investigations and length of stay (LOS).

METHODS

We report on NT-proBNP tests performed in emergency medical admissions in a 2005/2006 and subsequent 7-year (2014-2020) retrospective cohort. We assessed 30-day in-hospital mortality with a multivariable logistic regression model. The utilization of procedures/services was related to LOS with zero-truncated Poisson regression.

RESULTS

There were 64,212 admissions in 36,252 patients. Patients with a NT-proBNP test were significantly older at 75.3 years vs. 63.0 years and had longer LOS -9.4 days vs. 4.9 days. They had higher acute illness severity and comorbidity scores. Thirty-day in-hospital mortality was higher in those with a NT-proBNP test (8.8%) vs. no request (3.2%). NT-proBNP test level was prognostic in univariate - OR 2.87 (2.61, 3.15), and multivariate analyses - OR 1.40 (1.26, 1.56). Higher NT-proBNP levels predicted higher 30-day in-hospital mortality. Multivariable thirty-day in-hospital mortality was 3.8% (3.6%, 3.9%) for those without a test, increasing to 4.9% (4.7%, 5.2%) for ≥ 250 ng/L and 5.8% (5.8%, 6.3%) for ≥ 3000 ng/L. LOS was linearly related to the total number of procedures/services performed.

CONCLUSION

NT-proBNP is prognostic in emergency medical admissions. Downstream resource utilization differed following an NT-proBNP test; this may reflect different case complexity or the 'uncertainty' surrounding such admissions.

Hospital mortality and length of stay differences in emergency medical admissions related to 'on-call' specialty

BACKGROUND

The outcomes of acute medical admissions have been shown to be influenced by a variety of factors including system, patient, societal, and physician-specific differences.

AIM

To evaluate the influence of on-call specialty on outcomes in acute medical admissions.

METHODS

All acute medical admissions to our institution from 2015 to 2020 were evaluated. Admissions were grouped based on admitting specialty. Thirty-day in-hospital mortality and length of stay (LOS) were evaluated. Data was analysed using multivariable logistic regression and truncated Poisson regression modelling.

RESULTS

There were 50,347 admissions in 30,228 patients. The majority of admissions were under Acute Medicine (47.0%), and major medical subspecialties (36.1%); Elderly Care admitted 12.1%. Acute Medicine admissions were older at 72.9 years (IQR 57.0, 82.9) vs. 67.2 years (IQR 50.1, 80.2), had higher Acute Illness Severity (grades 4-6: 85.9% vs. 81.3%; p < 0.001), Charlson Index (> group 0; 61.5% vs. 54.6%; p < 0.001), and Comorbidity Score (40.7% vs. 36.7%; p < 0.001). Over time, there was a small (+ 8%) but significant increase in 30-day in-hospital mortality. Mortality rates for Acute Medicine, major medical specialties, and Elderly Care were not different at 5.1% (95% CI: 4.7, 5.5), 4.7% (95% CI: 4.3, 5.1), and 4.7% (95% CI: 3.9, 5.4), respectively. Elderly Care admissions had shorter LOS (7.8 days (95% CI: 7.6, 8.0)) compared with either Acute Medicine (8.7 days (95% CI: 8.6, 8.8)) or major medical specialties (8.7 days (95% CI: 8.6, 8.9)).

CONCLUSION

No difference in mortality and minor differences in LOS were observed. The prior pattern of improved outcomes year on year for emergency medical admissions appears ended.

Acute medical units during the first wave of the COVID-19 pandemic: a cross-national exploratory study of impact and responses

BACKGROUND

The COVID-19 pandemic represents one of the greatest ever challenges for healthcare. In the UK and beyond, acute medical units (AMUs) are the first point of assessment and care for the majority of medical inpatients. By their design and systems, they inevitably played an important role in the COVID-19 response but to date little has been published on how the COVID-19 pandemic has affected how AMUs have reorganised their resources, processes and structure.

METHODS

This retrospective study in August 2020 of 10 AMUs across Europe and Australasia used a standardised questionnaire to investigate existing practice and structure of AMUs, the national context of local hospital experience, changes to practice during the COVID-19 pandemic and views regarding future practice.

RESULTS

Changes to AMU structure, process and organisation are described in two contexts: preventing and controlling the spread of COVID-19 and adding value to the patient's acute care journey in the local context. We describe novel practices that have arisen and highlight areas of concern.

CONCLUSIONS

The AMUs were able to adapt to meet the demands of acute care delivery during the first wave of the COVID-19 pandemic. Operational planning and prioritisation of resources must be optimised to ensure sustainability of these services for future waves.

Emergency medical admissions and COVID-19: impact on 30-day mortality and hospital length of stay

BACKGROUND

The COVID-19 pandemic has put considerable strain on healthcare systems.

AIM

To investigate the effect of the COVID-19 pandemic on 30-day in-hospital mortality, length of stay (LOS) and resource utilization in acute medical care.

METHODS

We compared emergency medical admissions to a single secondary care centre during 2020 to the preceding 18 years (2002-2019). We investigated 30-day in-hospital mortality with a multiple variable logistic regression model. Utilization of procedures/services was related to LOS with zero truncated Poisson regression.

RESULTS

There were 132,715 admissions in 67,185 patients over the 19-year study. There was a linear reduction in 30-day in-hospital mortality over time; over the most recent 5 years (2016-2020), there was a relative risk reduction of 36%, from 7.9 to 4.3% with a number needed to treat of 27.7. Emergency medical admissions increased 18.8% to 10,452 in 2020 with COVID-19 admissions representing 3.5%. 18.6% of COVID-19 cases required ICU admission with a median stay of 10.1 days (IQR 3.8, 16.0). COVID-19 was a significant univariate predictor of 30-day in-hospital mortality, 18.5% (95%CI: 13.9, 23.1) vs. 3.0% (95%CI: 2.7, 3.4)-OR 7.3 (95%CI: 5.3, 10.1). ICU admission was the dominant outcome predictor-OR 12.4 (95%CI: 7.7, 20.1). COVID-19 mortality in the last third of 2020 improved-OR 0.64 (95%CI: 0.47, 0.86). Hospital LOS and resource utilization were increased.

CONCLUSION

A diagnosis of COVID-19 was associated with significantly increased mortality and LOS but represented only 3.5% of admissions and did not attenuate the established temporal decline in overall in-hospital mortality.

Non-Specific Clinical Presentations are Not Prognostic and do not Anticipate Hospital Length of Stay or Resource Utilization

AIM

To investigate whether a specific (SP) or non-specific (NSP) clinical presentation, predicts prognosis and in-hospital resource utilization in emergency medical admissions.

METHODS

We studied admissions over 5 years (2015-2019) and classified the symptom presentation as SP or NSP. The predictive capacity of the NSP category was related to 30-day in-hospital mortality with a multivariable logistic regression model. Utilization of procedures/services was related to hospital length of stay (LOS) with zero truncated Poisson regression.

RESULTS

There were 39,776 admissions in 23,995 patients. A NSP occurred in 18.2% of our top 20 clinical presentations; the top five being shortness of breath (12.8%), 'unwell' (7.1%), collapse (4.1%), abdominal pain (3.6%) and headache (2.7%). Baseline demographic characteristics were similar and unrelated to type of presentation; the model adjusted mortality by SP 4.0% (95% CI: 3.8%, 4.2%) or NSP 3.9% (95% CI: 3.5%, 4.4%) was identical. LOS was a dependant quantitative function of procedures/services undertaken; for the top two presentations of shortness of breath (SP) or unwell (NSP) there was no relationship between a SP or NSP presentation and hospital utilization of procedures/services or LOS.

CONCLUSION

Our data suggest no utility for a categorisation of presentations as specific or non-specific in terms of provision of prognostic information nor as an indicator of the pattern of hospital investigation or LOS.

Is there excessive troponin testing in clinical practice? Evidence from emergency medical admissions

AIM

To investigate whether excessive high-sensitivity cardiac troponin T (hscTnT) testing, in non-cardiac presentations, increases hospital length of stay (LOS) by driving down-stream investigations.

METHODS

We report on all hscTnT tests in emergency medical admissions, performed over a 9-year period between 2011-2019. Troponin testing frequency in different risk cohorts was determined and related to 30-day in-hospital mortality with a multivariable logistic regression model adjusted for other outcome predictors. Downstream utilization of procedures/services was related to LOS with zero truncated Poisson regression.

RESULTS

There were 66,475 admissions in 36,518 patients. hscTnT was tested in 24.4% of admissions, more frequently in the elderly (>70 years 33.4%, >80 years 35.9%), cardiovascular presentations (33.6%) and in those with high comorbidity (42.2%), and reduced in those with neurologic presentations (20%). A hscTnT request predicted increased 30-day in-hospital mortality OR 3.33 (95% CI: 3.06, 3.64). The univariate odds ratio (OR) of hscTnT test result was 1.45 (95% CI: 1.42, 1.49) and was semi-quantative with worsening outcomes as hscTnT increased. It remained predictive in the fully adjusted model OR 1.17 (95% CI: 1.09, 1.26). LOS was linearly related to the number of procedures/services performed. hscTnT testing did not increase LOS or number of procedures/services CONCLUSION: : A clinical request for hscTnT testing is prognostic and risk categorises. Subsequent resource utilization, if increased, appears an epiphenomenon related to risk categorisation, rather than being driven by inappropriate hscTnT testing.

Air pollution and comorbidity burden influencing acute hospital mortality outcomes in a large academic teaching hospital in Dublin, Ireland: a semi-ecologic analysis

OBJECTIVE

To investigate the extent to which air pollution interacts with comorbidity in determining mortality outcomes of emergency medical admissions.

STUDY DESIGN

Routinely collected data were used to study all emergency medical admissions to an academic teaching hospital in Dublin, Ireland, from 2002 to 2018. Air pollution was measured by particulate matter with aerodynamic diameter ≤10 μm (PM₁₀) and sulphur dioxide (SO₂) levels on the day of admission. Comorbidity Score was measured using a previously derived score.

METHODS

A multivariable logistic regression model was used to relate air pollutant levels, Comorbidity Scores, and their interaction to 30-day in-hospital mortality.

RESULTS

There were 102,483 admissions in 58,127 patients over 17 years. Both air pollutant levels and Comorbidity Score were associated with 30-day in-hospital mortality. On admission days with PM₁₀ levels above the median, mortality was higher (Odds ratio [OR] 1.09; 95% confidence interval [CI] 1.06, 1.18) at 11.2% (95% CI 10.5, 12) compared with 10.4% (95% CI 10, 10.7) on days when PM₁₀ levels were below the median. On admission days with SO₂ levels above the median, mortality was higher (OR 1.13; 95% CI 1.10, 1.16) at 12.2% (95% CI 11.4, 13) compared with 10.7% (95% CI 10.3, 11.1) on days when SO₂ levels were below the median. Comorbidity Score was strongly associated with mortality (mortality rate of 8.9% for those with a 6-point score vs mortality rate of 30.3% for those with a 16-point score). There was limited interaction between air pollutant levels and Comorbidity Score.

CONCLUSION

Both air pollution levels on the day of admission and Comorbidity Score were associated with 30-day in-hospital mortality. However, there was limited interaction between these two factors.

Comparative influence of Acute Illness Severity and comorbidity on mortality

BACKGROUND

The extent to which illness severity and comorbidity determine the outcome of an emergency medical admission is uncertain. We aim to quantitate the relative effect of these factors on mortality.

METHODS

We evaluated all emergency medical admission to our institution between 2002 and 2018. We derived an Acute Illness Severity Score (AISS) and Comorbidity Score from admission data and International Classification of Diseases codings. We employed a multivariable logistic regression model to relate both to 30-day in-hospital mortality.

RESULTS

There were 113,807 admissions in 58,126 patients. Both AISS, Odds Ratio (OR) 4.4 (95%CI 3.5, 5.5), and Comorbidity Score, OR 1.91 (95%CI 1.67, 2.18), independently predicted 30-day in-hospital mortality. The two highest AISS risk groups encompassed 46.5% of admissions with predicted mortality of 5.9% (95%CI 5.7%, 6.1%) and 14.4% (95%CI 13.9%, 14.8%) respectively. Comorbidity Score >=10 occurred in 17.9% of admissions with a predicted mortality of 13.3%. AISS and Comorbidity Score interacted to adversely influence mortality; the threshold effect for Comorbidity Score was reduced at high levels of AISS.

CONCLUSION

High AISS and Comorbidity Scores were predictive of 30-day in-hospital mortality and relatively common in emergency medical admissions. There is a strong interaction between the two scores.

Outcomes in acute medicine - Evidence from extended observations on readmissions, hospital length of stay and mortality outcomes

BACKGROUND

The Acute Medical Admission Unit (AMAU) model of care has been widely deployed, we examine changes in hospital readmission rates, length of stay (LOS) and 30-day in-hospital mortality over 16 years.

METHODS

All emergency medical admissions between 2002 and 2017 were examined. We assessed 30-day in-hospital mortality, readmission rates, and LOS using logistic regression and margins statistics modelled outcomes against predictor variables.

RESULTS

There were 106,586 admissions in 54,928 patients over 16 years. Calculated per patient the 30-day in-hospital mortality was 8.9% (95%CI 8.6% to 9.2%) and showed a relative risk reduction (RRR) of 61.1% from 12.4% to 4.8% over the 16 years (p = .001). Calculated per admission the 30-day in-hospital mortality was 4.5% (95%CI 4.4% to 4.6%) with a RRR of 31.9% from 2002 to 2017. Over this extended period 48.7% of patients were readmitted at least once, 9.3% >5 times and 20 patients >50 times each. The median LOS was 5.9 days (IQR 2.4, 12.9) with no trend of change over time. Total readmissions increased as a time dependent function; early readmissions (<4 weeks) fluctuated without time trend at 10.5% (95%CI 9.6 to 11.3). A logistic regression model described the hospital LOS as a linear function both of comorbidity and the utilisation of inpatient procedures and services.

CONCLUSION

30-day in-hospital mortality showed a linear trend to reduce over time at unaltered LOS and readmission rates. LOS showed linear dependency on clinical complexity; interventions aimed at reducing LOS may not be appropriate beyond a certain point.