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1.
Sci Rep ; 12(1): 15912, 2022 Sep 23.
Article in English | MEDLINE | ID: covidwho-2042339

ABSTRACT

The COVID-19 pandemic has strong effects on most health care systems. Forecasting of admissions can help for the efficient organisation of hospital care. We aimed to forecast the number of admissions to psychiatric hospitals before and during the COVID-19 pandemic and we compared the performance of machine learning models and time series models. This would eventually allow to support timely resource allocation for optimal treatment of patients. We used admission data from 9 psychiatric hospitals in Germany between 2017 and 2020. We compared machine learning models with time series models in weekly, monthly and yearly forecasting before and during the COVID-19 pandemic. A total of 90,686 admissions were analysed. The models explained up to 90% of variance in hospital admissions in 2019 and 75% in 2020 with the effects of the COVID-19 pandemic. The best models substantially outperformed a one-step seasonal naïve forecast (seasonal mean absolute scaled error (sMASE) 2019: 0.59, 2020: 0.76). The best model in 2019 was a machine learning model (elastic net, mean absolute error (MAE): 7.25). The best model in 2020 was a time series model (exponential smoothing state space model with Box-Cox transformation, ARMA errors and trend and seasonal components, MAE: 10.44). Models forecasting admissions one week in advance did not perform better than monthly and yearly models in 2019 but they did in 2020. The most important features for the machine learning models were calendrical variables. Model performance did not vary much between different modelling approaches before the COVID-19 pandemic and established forecasts were substantially better than one-step seasonal naïve forecasts. However, weekly time series models adjusted quicker to the COVID-19 related shock effects. In practice, multiple individual forecast horizons could be used simultaneously, such as a yearly model to achieve early forecasts for a long planning period and weekly models to adjust quicker to sudden changes.


Subject(s)
COVID-19 , COVID-19/epidemiology , Forecasting , Hospitals, Psychiatric , Humans , Pandemics , Retrospective Studies
2.
Circulation: Cardiovascular Quality and Outcomes ; 15, 2022.
Article in English | EMBASE | ID: covidwho-1938113

ABSTRACT

Background: Caregivers of persons with heart failure must manage high levels of patient health care utilization, treatment complexity and often unpredictable stressors associated with intermittent symptom exacerbations and mortality. Interventions have often focused on the needs of the person with HF, not the caregiver. Therefore, we developed an intervention using human-centered design to provide caregiver-targeted support for this population. Objective: Pilot test the feasibility and gauge initial effect size of the Caregiver Support intervention to improve quality of life (mental and physical), caregiver burden, and self-efficacy among family caregivers from baseline to 16 weeks. Methods: The intervention includes five individualized, nurse-led sessions over 10 weeks conducted remotely (due to COVID-19). Intervention components focus on 1) nature of caregiving, 2) life purpose, 3) co-development of an action plan to address caregiver goals to reduce caregiver burden and improve caregiver well-being, 4) exploration of social and community resources to support unmet needs, and 5) building a sustainability plan for addressing future caregiver needs. We tested our approach in a randomized waitlist control pilot trial (N=35) from August 2020 through March 2022. We calculated enrollment and retention rates, described acceptability, and computed intervention effect sizes from baseline to 16 weeks. Results: 35 out of 101 (35%) eligible caregivers enrolled and were majority female (93.3%), White (60%) and spousal caregivers (63.3%). Average age was 59.4 ± 16.6 years. Overall retention was 69%. All intervention participants completed the five core components, reporting high levels of satisfaction and acceptability of activities. Between-group effect sizes (n=21) at 16 weeks suggest improvement in the mental health component of quality of life, caregiver burden, and self-efficacy (effect sizes 0.88, 0.31, and 0.63, respectively). Conclusion: Caregivers found Caregiver Support acceptable and study methods were feasible, despite challenges to engaging during the COVID-19 pandemic. Findings provide foundational evidence that this person-centered behavioral intervention can contribute to enhanced caregiver outcomes.

3.
British Journal of Surgery ; 108:216-216, 2021.
Article in English | Web of Science | ID: covidwho-1539381
4.
Colorectal Disease ; 23(SUPPL 1):29, 2021.
Article in English | EMBASE | ID: covidwho-1457936

ABSTRACT

Purpose: Early in the coronavirus pandemic, guidelines and consensus have been proposed for the management of various general surgical emergencies to help surgeons serve the best interests of patients during an unprecedented time. There has been an agreement that certain conditions such as acute appendicitis should be managed conservatively with antibiotics whereas strong emphasis was put on the importance of timely surgical intervention on perianal and other superficial abscesses. Methods: Using ICD-10 codes, we investigated the impact of COVID-19 on surgical admissions due to perianal, pilonidal abscesses and acute appendicitis as comparison between March and November in 2020 and compared it to the same period in 2019. Results: The total number of surgical admissions due to perianal and pilonidal abscesses decreased by 22.5 and 31.7%, respectively, compared to the same period in 2019. Most of the decline was noted during the first wave, from March to July. Whereas acute appendicitis admissions remained comparatively constant between 2019 and 2020. Conclusion: Despite guidance regarding operative management of abscesses during the pandemic, the total number of surgical admissions due to perianal and pilonidal abscesses was reduced in comparison to the same period in 2019. Most of the decline was noted during the first wave, from March to July. This might result in higher rate of complications presenting at a later time.

6.
Chirurg ; 92(9): 822-829, 2021 Sep.
Article in German | MEDLINE | ID: covidwho-1009112

ABSTRACT

In the situation of a shortage of ventilation beds, ethically justifiable, transparent and comprehensible decisions must be made. This concept proposes that all patients are first intubated depending on necessity and then assessed by a triage team afterwards. In this situation newly admitted COVID patients compete with newly admitted Non-COVID patients as well as patients already treated in intensive care units for a ventilator. The combination of short-term and long-term prognoses should enable the interprofessional triage team to make comprehensible decisions. The aim of the prioritization concept is to save as many human lives as possible and to relieve the treatment team of the difficult decision on prioritization.


Subject(s)
COVID-19 , Hospitalization , Humans , Intensive Care Units , SARS-CoV-2 , Triage
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