BackgroundThe association between emergency department (ED) overcrowding and poor patient outcomes is well described, with recent work suggesting that the phenomenon causes delays in time-sensitive interventions, such as resuscitation. Even though most researchers agree on the fact that admitted patients boarding in the ED is a major contributing factor to ED overcrowding, little work explicitly addresses whether in-hospital occupancy is associated to the probability of patients being admitted from the ED. The objective of the present study is to investigate whether such an association exists.MethodsRetrospective analysis of data on all ED visits to Helsingborg General Hospital in southern Sweden between January 1, 2011, and December 31, 2012, was undertaken. The fraction of admitted patients was calculated separately for strata of in-hospital occupancy <95%, 95–100%, 100–105%, and >105%. Multivariate models were constructed in an attempt to take confounding factors, e.g., presenting complaints, age, referral status, triage priority, and sex into account. Subgroup analysis was performed for each specialty unit within the ED.ResultsOverall, 118,668 visits were included. The total admitted fraction was 30.9%. For levels of in-hospital occupancy <95%, 95–100%, 100–105%, and >105% the admitted fractions were 31.5%, 30.9%, 29.9%, and 28.7%, respectively. After taking confounding factors into account, the odds ratio for admission were 0.88 (CI 0.84–0.93, P >0.001) for occupancy level 95–100%, 0.82 (CI 0.78–0.87, P >0.001) for occupancy level 100–105%, and 0.74 (CI 0.67–0.81, P >0.001) for occupancy level >105%, relative to the odds ratio for admission at occupancy level <95%. A similar pattern was observed upon subgroup analysis.ConclusionsIn-hospital occupancy was significantly associated with a decreased odds ratio for admission in the study population. One interpretation is that patients who would benefit from inpatient care instead received suboptimal care in outpatient settings at times of high in-hospital occupancy. A second interpretation is that physicians admit patients who could be managed safely in the outpatient setting, in times of good in-hospital bed availability. Physicians thereby expose patients to healthcare-associated infections and other hazards, in addition to consuming resources better needed by others.

BackgroundA possible downstream effect of high in-hospital bed occupancy is that patients in the emergency department (ED) who would benefit from in-hospital care are denied admission. The present study aimed at evaluating this hypothesis through investigating associations between in-hospital bed occupancy at the time of presentation in the ED and the probability for unplanned 72-hour (72-h) revisits to the ED among patients discharged at index. A second outcome was unplanned 72-h revisits resulting in admission.MethodsAll visits to the ED of a 420-bed emergency hospital in southern Sweden between 1 January 2011 and 31 December 2012, which did not result in admission, death, or transfer to another hospital were included. Revisiting fractions were computed for in-hospital occupancy intervals <85%, 85% to 90%, 90% to 95%, 95% to 100%, 100% to 105%, and ≥105%. Multivariate models were constructed in an attempt to take confounding factors from, e.g., presenting complaints, age, referral status, and triage priority into account.ResultsIncluded in the study are 81,878 visits. The fraction of unplanned 72-h revisits/unplanned 72-h revisits resulting in admission was 5.8%/1.4% overall, 6.2%/1.4% for occupancy <85%, 6.4%/1.5% for occupancy 85% to 90%, 5.8%/1.4% for occupancy 90% to 95%, 6.0%/1.6% for occupancy 95% to 100%, 5.4%/1.6% for occupancy 100% to 105%, and 4.9%/1.4% for occupancy ≥105%.In the multivariate models, a trend to lower probability of unplanned 72-h revisits was observed at occupancy ≥105% compared to occupancy <95% (OR 0.88, CI 0.76 to 1.01). No significant associations between in-hospital occupancy at index and the probability of making unplanned 72-h revisits resulting in admission were observed.ConclusionsThe lack of associations between in-hospital occupancy and unplanned 72-h revisits does not support the hypothesis that ED patients are inappropriately discharged when in-hospital beds are scarce. The results are reassuring as they indicate that physicians are able to make good decisions, also while resources are constrained.

BackgroundPrevious work has suggested that given a hospital’s need to admit more patients from the emergency department (ED), high inpatient bed occupancy may encourage premature hospital discharges that favor the hospital’s need for beds over patients’ medical interests. We argue that the effects of such action would be measurable as a greater proportion of unplanned hospital readmissions among patients discharged when the hospital was full than when not. In response, the present study tested this hypothesis by investigating the association between inpatient bed occupancy at the time of hospital discharge and the 30-day readmission rate.MethodsThe sample included all inpatient admissions from the ED at a 420-bed emergency hospital in southern Sweden during 2011–2012 that resulted in discharge before 1 December 2012. The share of unplanned readmissions within 30 days was computed for levels of inpatient bed occupancy of <95 %, 95–100 %, 100–105 % and >105 % at the hour of discharge. A binary logistic regression model was constructed to adjust for age, time of discharge, and other factors that could affect the outcome.ResultsIn all, 32,811 visits were included in the study, 9.9 % of which resulted in an unplanned readmission within 30 days of discharge. The proportion of readmissions was 9.0 % for occupancy levels of <95 % at the patient’s discharge, 10.2 % for 95–100 % occupancy, 10.8 % for 100–105 % occupancy, and 10.5 % for >105 % occupancy (p = 0.0001). Results from the multivariate models show that the OR (95 % CI) of readmission was 1.11 (1.01–1.22) for patients discharged at 95–100 % occupancy, 1.17 (1.06–1.29) at 100–105 % occupancy, and 1.15 (0.99–1.34) at >105 % occupancy.ConclusionsResults indicate that patients discharged from inpatient wards at times of high inpatient bed occupancy experience an increased risk of unplanned readmission within 30 days of discharge.

ObjectivesThe aim of this work was to train machine learning models to identify patients at end of life with clinically meaningful diagnostic accuracy, using 30-day mortality in patients discharged from the emergency department (ED) as a proxy.DesignRetrospective, population-based registry study.SettingSwedish health services.Primary and secondary outcome measuresAll cause 30-day mortality.MethodsElectronic health records (EHRs) and administrative data were used to train six supervised machine learning models to predict all-cause mortality within 30 days in patients discharged from EDs in southern Sweden, Europe.ParticipantsThe models were trained using 65 776 ED visits and validated on 55 164 visits from a separate ED to which the models were not exposed during training.ResultsThe outcome occurred in 136 visits (0.21%) in the development set and in 83 visits (0.15%) in the validation set. The model with highest discrimination attained ROC–AUC 0.95 (95% CI 0.93 to 0.96), with sensitivity 0.87 (95% CI 0.80 to 0.93) and specificity 0.86 (0.86 to 0.86) on the validation set.ConclusionsMultiple models displayed excellent discrimination on the validation set and outperformed available indexes for short-term mortality prediction interms of ROC–AUC (by indirect comparison). The practical utility of the models increases as the data they were trained on did not require costly de novo collection but were real-world data generated as a by-product of routine care delivery.

Background and Purpose: Intravenous thrombolysis is a well-established treatment for acute ischemic stroke. Our aim was to quantify the effect of each minute delay in door-to-needle time (DNT) on 90-day survival, intracerebral hemorrhagic complication <36 hours, and functional outcomes at 3 months, in routine clinical practice. Methods: Our nationwide registry-based study included 14 132 adult patient admissions with ischemic stroke receiving intravenous thrombolysis from 2010 to 2017. Outcomes were analyzed using multivariable logistic regression, adjusting for potential confounders. Results: Median DNT was 47 minutes, with an improvement from 65 to 38 minutes during the study. Median age was 74 years, and median National Institutes of Health Stroke Scale 8 points. We found a significant impact of each minute delay in DNT with reduced odds of survival by 0.6%, increased odds of intracerebral hemorrhagic and worse activities of daily living by 0.3%, and worse living conditions and mobility by 0.4%. Conclusions: Improving DNT is a key factor in achieving good outcomes after stroke. We estimate that in Sweden alone in 2017, compared with 2010, the shorter DNT achieved have saved 38 lives, avoided 8 intracerebral hemorrhagic transformations, and spared, respectively, 36, 51, and 52 patients from a worsening in activities of daily living, living conditions, and mobility. DNT is sensitive for interventions and should be targeted in quality improvement efforts.