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Hospital-acquired infections (HAIs), including emerging multi-drug resistant organisms, threaten healthcare systems worldwide. Efficient containment measures of HAIs must mobilize the entire healthcare network. Thus, to best understand how to reduce the potential scale of HAI epidemic spread, we explore patient transfer patterns in the French healthcare system. Using an exhaustive database of all hospital discharge summaries in France in 2014, we construct and analyze three patient networks based on the following: transfers of patients with HAI (HAI-specific network); patients with suspected HAI (suspected-HAI network); and all patients (general network). All three networks have heterogeneous patient flow and demonstrate small-world and scale-free characteristics. Patient populations that comprise these networks are also heterogeneous in their movement patterns. Ranking of hospitals by centrality measures and comparing community clustering using community detection algorithms shows that despite the differences in patient population, the HAI-specific and suspected-HAI networks rely on the same underlying structure as that of the general network. As a result, the general network may be more reliable in studying potential spread of HAIs. Finally, we identify transfer patterns at both the French regional and departmental (county) levels that are important in the identification of key hospital centers, patient flow trajectories, and regional clusters that may serve as a basis for novel wide-scale infection control strategies.

AbstractObjectiveTo determine if postnatal transfer or birth in a non-tertiary hospital is associated with adverse outcomes.DesignObservational cohort study with propensity score matching.SettingNational health service neonatal care in England; population data held in the National Neonatal Research Database.ParticipantsExtremely preterm infants born at less than 28 gestational weeks between 2008 and 2015 (n=17 577) grouped based on birth hospital and transfer within 48 hours of birth: upward transfer (non-tertiary to tertiary hospital, n=2158), non-tertiary care (born in non-tertiary hospital; not transferred, n=2668), and controls (born in tertiary hospital; not transferred, n=10 866). Infants were matched on propensity scores and predefined background variables to form subgroups with near identical distributions of confounders. Infants transferred between tertiary hospitals (horizontal transfer) were separately matched to controls in a 1:5 ratio.Main outcome measuresDeath, severe brain injury, and survival without severe brain injury.Results2181 infants, 727 from each group (upward transfer, non-tertiary care, and control) were well matched. Compared with controls, infants in the upward transfer group had no significant difference in the odds of death before discharge (odds ratio 1.22, 95% confidence interval 0.92 to 1.61) but significantly higher odds of severe brain injury (2.32, 1.78 to 3.06; number needed to treat (NNT) 8) and significantly lower odds of survival without severe brain injury (0.60, 0.47 to 0.76; NNT 9). Compared with controls, infants in the non-tertiary care group had significantly higher odds of death (1.34, 1.02 to 1.77; NNT 20) but no significant difference in the odds of severe brain injury (0.95, 0.70 to 1.30) or survival without severe brain injury (0.82, 0.64 to 1.05). Compared with infants in the upward transfer group, infants in the non-tertiary care group had no significant difference in death before discharge (1.10, 0.84 to 1.44) but significantly lower odds of severe brain injury (0.41, 0.31 to 0.53; NNT 8) and significantly higher odds of survival without severe brain injury (1.37, 1.09 to 1.73; NNT 14). No significant differences were found in outcomes between the horizontal transfer group (n=305) and controls (n=1525).ConclusionsIn extremely preterm infants, birth in a non-tertiary hospital and transfer within 48 hours are associated with poor outcomes when compared with birth in a tertiary setting. We recommend perinatal services promote pathways that facilitate delivery of extremely preterm infants in tertiary hospitals in preference to postnatal transfer.

Most ward risk scores were created using subjective opinion in individual hospitals and only use vital signs. To develop and validate a risk score using commonly collected electronic health record data. All patients hospitalized on the wards in five hospitals were included in this observational cohort study. Discrete-time survival analysis was used to predict the combined outcome of cardiac arrest (CA), intensive care unit (ICU) transfer, or death on the wards. Laboratory results, vital signs, and demographics were used as predictor variables. The model was developed in the first 60% of the data at each hospital and then validated in the remaining 40%. The final model was compared with the Modified Early Warning Score (MEWS) using the area under the receiver operating characteristic curve and the net reclassification index (NRI). A total of 269,999 patient admissions were included, with 424 CAs, 13,188 ICU transfers, and 2,840 deaths occurring during the study period. The derived model was more accurate than the MEWS in the validation dataset for all outcomes (area under the receiver operating characteristic curve, 0.83 vs. 0.71 for CA; 0.75 vs. 0.68 for ICU transfer; 0.93 vs. 0.88 for death; and 0.77 vs. 0.70 for the combined outcome; P value < 0.01 for all comparisons). This accuracy improvement was seen across all hospitals. The NRI for the electronic Cardiac Arrest Risk Triage compared with the MEWS was 0.28 (0.18-0.38), with a positive NRI of 0.19 (0.09-0.29) and a negative NRI of 0.09 (0.09-0.09). We developed an accurate ward risk stratification tool using commonly collected electronic health record variables in a large multicenter dataset. Further study is needed to determine whether implementation in real-time would improve patient outcomes.

Background Neurocritical care is devoted to the care of critically ill patients with acute neurological or neurosurgical emergencies. There is limited information regarding epidemiological data, disease characteristics, variability of clinical care, and in-hospital mortality of neurocritically ill patients worldwide. We addressed these issues in the P oint P R evalence I n N eurocritical C ar E (PRINCE) study, a prospective, cross-sectional, observational study. Methods We recruited patients from various intensive care units (ICUs) admitted on a pre-specified date, and the investigators recorded specific clinical care activities they performed on the subjects during their first 7 days of admission or discharge (whichever came first) from their ICUs and at hospital discharge. In this manuscript, we analyzed the final data set of the study that included patient admission characteristics, disease type and severity, ICU resources, ICU and hospital length of stay, and in-hospital mortality. We present descriptive statistics to summarize data from the case report form. We tested differences between geographically grouped data using parametric and nonparametric testing as appropriate. We used a multivariable logistic regression model to evaluate factors associated with in-hospital mortality. Results We analyzed data from 1545 patients admitted to 147 participating sites from 31 countries of which most were from North America (69%, N  = 1063). Globally, there was variability in patient characteristics, admission diagnosis, ICU treatment team and resource allocation, and in-hospital mortality. Seventy-three percent of the participating centers were academic, and the most common admitting diagnosis was subarachnoid hemorrhage (13%). The majority of patients were male (59%), a half of whom had at least two comorbidities, and median Glasgow Coma Scale (GCS) of 13. Factors associated with in-hospital mortality included age (OR 1.03; 95% CI, 1.02 to 1.04); lower GCS (OR 1.20; 95% CI, 1.14 to 1.16 for every point reduction in GCS); pupillary reactivity (OR 1.8; 95% CI, 1.09 to 3.23 for bilateral unreactive pupils); admission source (emergency room versus direct admission [OR 2.2; 95% CI, 1.3 to 3.75]; admission from a general ward versus direct admission [OR 5.85; 95% CI, 2.75 to 12.45; and admission from another ICU versus direct admission [OR 3.34; 95% CI, 1.27 to 8.8]); and the absence of a dedicated neurocritical care unit (NCCU) (OR 1.7; 95% CI, 1.04 to 2.47). Conclusion PRINCE is the first study to evaluate care patterns of neurocritical patients worldwide. The data suggest that there is a wide variability in clinical care resources and patient characteristics. Neurological severity of illness and the absence of a dedicated NCCU are independent predictors of in-patient mortality.

Among nursing home residents with cognitive impairment, burdensome transitions between the nursing home and the hospital or hospice during the last months of life were common, varied according to state, and were associated with a poor quality of care. Health care transitions, such as the hospitalization of nursing home residents, have the potential for fragmentation of care, changes in the management of chronic diseases, duplication of diagnostic workups, and medical errors. 1 – 7 Few previous reports have described health care transitions among nursing home residents who had advanced cognitive impairment. These patients and their family members are especially vulnerable to the adverse consequences resulting from transitions, particularly during end-of-life care. Pertinent sources of distress include the trauma of the physical transfer, increased confusion because of unfamiliar settings and providers, inadequate ability to address the patient's special needs (e.g., assistance with . . .

ObjectivesTo review the effects and safety of high-flow nasal cannula (HFNC) for bronchiolitis.MethodsSix electronic databases including PubMed, EMBASE, Cochrane Central Register of Controlled Trials, China National Knowledge Infrastructure, CQ VIP Database and Wanfang Data were searched from their inception to 1 June 2018. Randomised controlled trials (RCTs) which investigated the effects of HFNC versus other forms of oxygen therapies for bronchiolitis were included.ResultsNine RCTs with 2121 children met the eligibility criteria. There was no significant difference in length of stay in hospital (LOS), length of oxygen supplementation (LOO), transfer to intensive care unit, incidence of intubation, respiratory rate, SpO2 and adverse events in HFNC group compared with standard oxygen therapy (SOT) and nasal continuous positive airway pressure (nCPAP) groups. A significant reduction of the incidence of treatment failure (risk ratio (RR) 0.50, 95% CI 0.40 to 0.62, p<0.01) was observed in HFNC group compared with SOT group, but there was a significant increase of the incidence of treatment failure (RR 1.61, 95% CI 1.06 to 2.42, p0.02) in HFNC group compared with nCPAP group. In subgroup analysis, LOS was significantly decreased in HFNC group compared with SOT group in low-income and middle-income countries.ConclusionThe systematic review suggests HFNC is safe as an initial respiratory management, but the evidence is still lacking to show benefits for children with bronchiolitis compared with SOT or nCPAP.

We investigated the extent to which demographic characteristics, clinical care aspects, and relevant biomarkers predicted sepsis-related mortality among patients transferred from a rural, low-volume emergency department (ED) to an urban, high-volume, level-2 trauma center. We conducted an observational study among adult severe sepsis patients (N = 242) who, within a community-based regional healthcare system, presented to one of the four rural, low-volume EDs and were subsequently transferred to the urban, high-volume, level-2 trauma center, and were identified as septic at either location. We evaluated in-hospital and 30 days after discharge mortality. In-hospital mortality rate was predicted by previous admission to an ICU (OR 5.02, 95 % CI: 1.89–15.94, p = 0.002), identification of sepsis prior to transfer (OR 0.29, 95 % CI: 0.11–0.74, p = 0.01), and a moderately abnormal lactate level (OR 0.22, 95 % CI: 0.05–0.79, p = 0.03). Mortality 30 days after discharge was predicted by previous admission to an ICU (OR: 3.28, 95 % CI: 1.62–6.97, p = 0.001), abnormal red cell distribution width (OR: 2.23, 95 % CI: 1.11–4.60, p = 0.03), identification of sepsis prior to transfer (OR: 0.26, 95 % CI: 0.12–0.54, p < 0.001), and a moderately abnormal lactate (OR: 0.32, 95 % CI: 0.12–0.79, p = 0.02). Early identification of sepsis, as well as attention to prior ICU admission or comorbidities and abnormal red cell distribution width, could facilitate better care and prevent mortality among patients with sepsis who are transferred from a rural, low-volume emergency department to an urban-high volume facility.

All publicly funded hospital discharges in Aotearoa New Zealand are recorded in the National Minimum Dataset (NMDS). Movement of patients between hospitals (and occasionally within the same hospital) results in separate records (discharge events) within the NMDS and if these consecutive health records are not accounted for hospitalization (encounters) rates might be overestimated. The aim of this study was to determine the impact of four different methods to bundle multiple discharge events in the NMDS into encounters on the relative comparison of rural and urban Ambulatory Sensitive Hospitalization (ASH) rates. NMDS discharge events with an admission date between July 1, 2015, and December 31, 2019, were bundled into encounters using either using a) no method, b) an “admission flag”, c) a “discharge flag”, or d) a date-based method. ASH incidence rate ratios (IRRs), the mean total length of stay and the percentage of interhospital transfers were estimated for each bundling method. These outcomes were compared across 4 categories of the Geographic Classification for Health. Compared with no bundling, using the date-based method resulted in an 8.3% reduction (150 less hospitalizations per 100,000 person years) in the estimated incidence rate for ASH in the most rural (R2-3) regions. There was no difference in the interpretation of the rural-urban IRR for any bundling methodology. Length of stay was longer for all bundling methods used. For patients that live in the most rural regions, using a date-based method identified up to twice as many interhospital transfers (5.7% vs 12.4%) compared to using admission flags. Consecutive events within hospital discharge datasets should be bundled into encounters to estimate incidence. This reduces the overestimation of incidence rates and the undercounting of interhospital transfers and total length of stay. •The impact of four methods of bundling health events into encounters was assessed.•A dates-based method limits overcounting and identifies more inter-hospital transfers.•Ambulatory Sensitive Hospitalisation rural-urban differences weren’t impacted.

We evaluated the clinical course of asymptomatic and mildly symptomatic patients with laboratory-confirmed coronavirus disease (COVID-19) admitted to community treatment centers (CTCs) for isolation in South Korea. Of 632 patients, 75 (11.9%) had symptoms at admission, 186 (29.4%) were asymptomatic at admission but developed symptoms during their stay, and 371 (58.7%) remained asymptomatic during their entire clinical course. Nineteen (3.0%) patients were transferred to hospitals, but 94.3% (573/613) of the remaining patients were discharged from CTCs upon virologic remission. The mean virologic remission period was 20.1 days (SD + 7.7 days). Nearly 20% of patients remained in the CTCs for 4 weeks after diagnosis. The virologic remission period was longer in symptomatic patients than in asymptomatic patients. In mildly symptomatic patients, the mean duration from symptom onset to virologic remission was 11.7 days (SD + 8.2 days). These data could help in planning for isolation centers and formulating self-isolation guidelines.

Nursing home residents are often colonized with antibiotic-resistant bacteria. In this trial involving 28 nursing homes, decolonization with chlorhexidine and povidone–iodine reduced the risk of hospitalization for infection.