Search

Aims Few studies have investigated potential consequences of strained surgical resources. The aim of this cohort study was to assess whether a high proportion of concurrent acute surgical admissions, tying up hospital surgical capacity, may lead to delayed surgery and affect mortality for hip fracture patients. Methods This study investigated time to surgery and 60-day post-admission death of patients 70 years and older admitted for acute hip fracture surgery in Norway between 2008 and 2016. The proportion of hospital capacity being occupied by newly admitted surgical patients was used as the exposure. Hip fracture patients admitted during periods of high proportion of recent admissions were compared with hip fracture patients admitted at the same hospital during the same month, on similar weekdays, and times of the day with fewer admissions. Results Among 60,072 patients, mean age was 84.6 years (SD 6.8), 78% were females, and median time to surgery was 20 hours (IQR 11 to 29). Overall, 14% (8,464) were dead 60 days after admission. A high (75th percentile) proportion of recent surgical admission compared to a low (25th percentile) proportion resulted in 20% longer time to surgery (95% confidence interval (CI) 16 to 25) and 20% higher 60-day mortality (hazard ratio 1.2, 95% CI 1.1 to 1.4). Conclusion A high volume of recently admitted acute surgical patients, indicating probable competition for surgical resources, was associated with delayed surgery and increased 60-day mortality. Cite this article: Bone Joint J 2021;103-B(2):264–270.

Purpose A reduction in the length of hospital stay may threaten patient safety. This study aimed to estimate the effect of organizational pressure to discharge on 60-day mortality among hip fracture patients. Patients and methods In this cohort study, hip fracture patients were analyzed as if they were enrolled in a sequence of trials for discharge. A hospital's discharge tendency was defined as the proportion of patients with other acute conditions who were discharged on a given day. Because the hospital's tendency to discharge would affect hip fracture patients in an essentially random manner, this exposure could be regarded as analogous to being randomized to treatment in a clinical trial. The study population consisted of 59,971 Norwegian patients with hip fractures, hospitalized between 2008 and 2016, aged 70 years and older. To calculate the hospital discharge tendency for a given day, we used data from all 5,013,773 other acute hospitalizations in the study period. Results The probability of discharge among hip fracture patients increased by 5.5 percentage points (95% confidence interval (CI)=5.3-5.7) per 10 percentage points increase in hospital discharges of patients with other acute conditions. The increased risk of death that could be attributed to a discharge from organizational causes was estimated to 3.7 percentage points (95% CI=1.4-6.0). The results remained stable under different time adjustments, follow-up periods, and age cut-offs. Conclusion This study showed that discharges from organizational causes may increase the risk of death among hip fracture patients.

Increasing the utilisation of unused capacity in hospitals is a health policy goal, but there is concern that little unused capacity remains. The objective of the study was to examine how healthcare personnel experience and deal with pressure on capacity in the somatic specialist health services.In this qualitative study, we conducted semi-structured interviews with unit heads and doctors and nurses involved in discharging patients in two Norwegian hospital trusts. Nine interviews (both individual and group) with altogether 19 informants were carried out in the period October 2017-February 2018. The interviews were analysed using systematic text condensation.Pressure on hospital capacity was described as continual pressure to treat more patients. The informants used the term 'undercapacity': a situation in which increased demands without sufficient resources were detrimental to something or someone. Elderly patients who had completed their treatment and were waiting for the provision of municipal services were regarded as particularly vulnerable, since they were often overrepresented among the patients moved between departments and wards in order to free up capacity when beds were urgently needed. The hospital staff felt they had little influence on the type of municipal services the patients were offered following discharge.The informants stated that their daily work was negatively affected by undercapacity. Health professionals' perceptions of pressure on hospital capacity constitute vital knowledge in policy formation in the field.

Background: Crowding in emergency departments (EDs) is a challenge globally. To counteract crowding in day-to-day operations, better tools to improve monitoring of the patient flow in the ED is needed. The objective of this study was the development of a continuously updated monitoring system to forecast emergency department (ED)arrivals on a short time-horizon incorporating data from prehospital services. Methods: Time of notification and ED arrival was obtained for all 191,939 arrivals at the ED of a Norwegian university hospital from 2010 to 2018. An arrival notification was an automatically captured time stamp which indicated the first time the ED was notified of an arriving patient, typically by a call from an ambulance to the emergency service communication center. A Poisson time-series regression model for forecasting the number of arrivals on a 1-, 2- and 3-h horizon with continuous weekly and yearly cyclic effects was implemented. We incorporated time of arrival notification by modelling time to arrival as a time varying hazard function. We validated the model on the last full year of data. Results: In our data, 20% of the arrivals had been notified more than 1 hour prior to arrival. By incorporating time of notification into the forecasting model, we saw a substantial improvement in forecasting accuracy, especially on a one-hour horizon. In terms of mean absolute prediction error, we observed around a six percentage-point decrease compared to a simplified prediction model. The increase in accuracy was particularly large for periods with large inflow. Conclusions: The proposed model shows increased predictability in ED patient inflow when incorporating data on patient notifications. This approach to forecasting arrivals can be a valuable tool for logistic, decision making and ED resource management. © The Author(s). 2019Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, andreproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link tothe Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

Background and purpose: There are numerous studies on the weekend effect for hip fracture patients, with conflicting results. We analyzed time of admission and discharge, and the association with mortality and length of hospital stay in more detail. Material and methods: We used data from 61 211 surgically treated hip fractures, 55 211 patients, admitted to Norwegian hospitals 2008-2014. All patients were aged 50 years or older. Data were analyzed with Cox’ and Poisson regression. Results: Mortality within 30 days did not differ substantially by day of admission, although admissions on Sundays and holidays had a slightly increased mortality. The hazard ratios were 1.08 (95% confidence interval (CI) 0.97-1.20) for Sundays, and 1.18 (CI 0.98-1.41) for holidays, relative to Mondays. For patients admitted between 6:00 am and 7:00 am the hazard ratio was 1.41 (CI 1.10-1.80) relative to patients admitted between 2:00 pm and 3:00 pm. Discharges during weekends and holidays were associated with a substantial higher mortality than weekday discharges. Patients admitted from Friday to Sunday generally stayed shorter in hospital than patients admitted during other days. Interpretation: Our results indicate that the discussion on weekday versus weekend admission effects might have distracted attention from other important factors, such as time of day of admission, and day of discharge from hospital treatment. © 2018 The Author(s). Published by Taylor & Francis on behalf of the Nordic Orthopedic Federation. This is an Open Access article distributed under the terms of the Creative Commons Attribution-Non-Commercial License (https://creativecommons.org/licenses/by/4.0)

Background Actigraphy could be an objective alternative to clinical ratings of motor activity in bipolar disorder (BD), which is of importance now that increased activity and energy are added as cardinal symptoms of (hypo)mania in the DSM-5 and commonly used rating scales give inadequate information about motor symptoms. To date, most actigraphy studies have been conducted in groups and/or used mean activity levels as the variable of interest. The novelty of this case series is therefore to indicate the potential of actigraphy and non-parametric analysis as an objective and personalized marker of intra-individual activity patterns in different phases of BD. To our knowledge, this is the first case series that provides an objective assessment of non-linear dynamics in within-person activity patterns during acute BD episodes. Results We report on three cases of bipolar I disorder with 24-h actigraphy recordings undertaken during the first few days of two or more separate admissions for an acute illness episode, including admissions for individuals in different phases of BD, or with different levels of severity in the same phase of illness. For each recording, we calculated mean activity levels over 24 h, but especially focused on key measures of variability and complexity in activity. Intra-individual activity patterns were found to be different according to phase of illness, but showed consistency within the same phase. With increasing psychotic symptoms, there was evidence of a lower overall level and greater irregularity in activity. As such, sample entropy (a measure of irregularity) may have particular utility in characterizing mania and psychotic symptoms, while assessment of the distribution of rest versus activity over 24 h may distinguish between phases of BD within an individual. Conclusions This case series indicates that objective, intra-individual, real-time recordings of patterns of activity may have clinical impact as a valuable adjunct to clinical observation and symptom ratings. We suggest that actigraphy combined with detailed mathematical analysis provides a biological variable that could become an important tool for developing a personalized approach to diagnostics and treatment monitoring in BD. © The Author(s) 2018. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.