An Assessment of the Philippine Hospital Resources as Predictors of the Case Fatality Rate of COVID – 19

In the heightened effects of the pandemic, health resources have been in constant limbo as supplies and availability of hospital resources take a toll as COVID-19 cases surge, resulting in shortages. Thus, health systems are overwhelmed, resulting in a higher fatality rate since the capacity to provide medical attention is diminished. In this paper, hospital resources refer to mechanical ventilators, ICU, isolation, and ward beds which are the critical factors of the case fatality rate (CFR) of COVID-19 in the Philippines. Data were retrieved from the Department of Health (DOH) Case Bulletins from October 26, 2020, to June 30, 2021, with 248 total observations. This research used the Ordinary Least Squares (OLS) Multiple Regression to determine if hospital resources are the predictors of the case fatality rate of COVID-19. Furthermore, the results show a significant relationship between the hospital resources and the case fatality rate of COVID-19 in the Philippines. This study can become a framework for further research concerned about hospital resources as the predictors of case fatality rates of different diseases in a pandemic.

Management measures implemented at the West China Hospital may help prevent and contain COVID-19 and similar outbreaks

This article presents management processes for dealing with the novel coronavirus disease 2019 (COVID-19) outbreak at the West China Hospital of Sichuan University. From January to March 2020, the West China Hospital of Sichuan University established response structures and protocols, as well as integrated out-of-hospital resources, to deal with the COVID-19 outbreak. A total of 8,066 patients were screened and 345 COVID-19 patients were isolated for treatment. Hospital command systems, emergency management protocols, as well as process, space, and personnel management, and strengthening material reserves, and social responsibility strategies were implemented. Outbreak management aspects that required improvement included estimates of the anticipated number of cases, timely collection of patient information and feedback on the effect of outreach and online consultation methods.

Towards long term monitoring: Seizure detection with reduced electroencephalogram channels

Epilepsy is a prevalent condition characterised by recurrent, unpredictable seizures. The diagnosis of epilepsy is by surface electroencephalography (EEG), a time-consuming and uncomfortable process for patients. The diagnosis of seizures using EEG over a brief monitoring period has variable success, dependent on patient tolerance and seizure frequency. Further, the availability of hospital resources and hardware and software specifications inherently limit the capacity to perform long-term data collection whilst maintaining patient comfort. The application and maintenance of the standard number of electrodes restrict recording time to a maximum of approximately ten days. This limited monitoring period also results in limited data for machine learning models for seizure detection and classification. This work examines the literature on the impact of reduced electrodes on data accuracy and reliability in seizure detection. Here we present two electrode ranking models, demonstrating the decline in seizure detection performance associated with reducing electrodes. We assert the need for further research in electrode reduction to advance solutions toward portable, reliable devices that can simultaneously provide patient comfort, long-term monitoring and contribute to multi-modal patient care solutions.

Outcomes of Patients Placed in an Emergency Department Observation Unit of a Comprehensive Cancer Center

PURPOSE Emergency department observation units (EDOUs) have been shown to decrease length of stay and improve cost effectiveness. Yet, compared with noncancer patients, patients with cancer are placed in EDOUs less often. In this study, we aimed to describe patients who were placed in a cancer center's EDOU to discern their clinical characteristics and outcomes. METHODS We performed a retrospective observational study that included all patients age 18 years and older who presented to our emergency department (ED) and were placed in the EDOU between March 1, 2019, and February 29, 2020. The patients' electronic medical records were queried for demographics, comorbidities, diagnosis at the time of placement in the EDOU, length of stay, disposition from the EDOU, ED return within 72 hours after discharge from the EDOU, and mortality outcomes at 14 and 30 days. RESULTS A total of 2,461 visits were eligible for analysis. Cancer-related pain was the main reason for observation in more than one quarter of the visits. The median length of stay in the EDOU was approximately 23 hours, and 69.6% of the patients were discharged. The ED return rate for unscheduled visits at 72 hours was 1.9%. The 14- and 30-day mortality rates were significantly higher for patients who were admitted than for those who were discharged (14 days: 1.7% v 0.3%, P < .001; 30 days: 5.9% v 1.8%, P < .001). CONCLUSION Our data suggest that placing patients with cancer in EDOUs is safe, reduces admissions, and reserves hospital resources for patients who can receive the most benefit without compromising care.

Comparing hospital-resource utilization by an enhanced pneumonia surveillance programme for COVID-19 with pre-pandemic pneumonia admissions – a Singaporean hospital’s experience

Introduction. During the early days of coronavirus disease 2019 (COVID-19) in Singapore, Tan Tock Seng Hospital implemented an enhanced pneumonia surveillance (EPS) programme enrolling all patients who were admitted from the Emergency Department (ED) with a diagnosis of pneumonia but not meeting the prevalent COVID-19 suspect case definition. Hypothesis/Gap Statement. There is a paucity of data supporting the implementation of such a programme. Aims. To compare and contrast our hospital-resource utilization of an EPS programme for COVID-19 infection detection with a suitable comparison group. Methodology. We enrolled all patients admitted under the EPS programme from TTSH’s ED from 7 February 2020 (date of EPS implementation) to 20 March 2020 (date of study ethics application) inclusive. We designated a comparison cohort over a similar duration the preceding year. Relevant demographic and clinical data were extracted from the electronic medical records. Results. There was a 3.2 times higher incidence of patients with an admitting diagnosis of pneumonia from the ED in the EPS cohort compared to the comparison cohort (P<0.001). However, there was no significant difference in the median length of stay of 7 days (P=0.160). Within the EPS cohort, stroke and fluid overload occur more frequently as alternative primary diagnoses. Conclusions. Our study successfully evaluated our hospital-resource utilization demanded by our EPS programme in relation to an appropriate comparison group. This helps to inform strategic use of hospital resources to meet the needs of both COVID-19 related services and essential ‘peace-time’ healthcare services concurrently.

Surgical Case-Mix and Discharge Decisions: Does Within-Hospital Coordination Matter?

How to Assess the Benefits of Coordination in Managing Hospital Resources In providing patient care, hospitals rely on multiple types of resources, such as operating rooms, recovery beds, labs, and diagnostic equipment, that are often controlled and managed as separate entities and by different decision makers. In “Surgical Case-Mix and Discharge Decisions: Does Within-Hospital Coordination Matter?” Hessam Bavafa, Lerzan Örmeci, Sergei Savin, and Vanitha Virudachalam focus on the interaction between “front-end’’ resources, such as operating rooms, and “backroom’’ resources, such as recovery beds, and compare hospital profitability under the fully coordinated, optimal approach to hospital resource management and under alternative decentralized approaches often encountered in practice. The paper identifies settings in which the benefits of coordination are likely to be high as well as settings in which those benefits are at best moderate. In a given hospital, only hospital managers are in a position to estimate with any degree of certainty potential costs of coordinated management of hospital resources, and the paper’s analysis of the benefits of coordination empowers hospital managers to make informed decisions on the desirability of replacing the often decentralized “status quo” by centralized resource management.

How far do they go?: A spatial examination of missing persons from hospitals

PurposeMissing person cases are a global issue impacting policing. Among these, those who abscond from hospitals are especially concerning because these reports require collaboration across services, often strain already limited police and hospital resources and present an elevated level of possible harm due to high prevalence of mental illness, disability and/or addiction. Despite this, to-date, there has been a lack of scholarly attention on this phenomenon from a policing perspective. The present study aims to fill this gap by exploring how far missing hospital patients travel and where they are commonly found.Design/methodology/approachUsing a sample of 731 closed case files (2014–2018) from one police service, we identify spatial behaviour patterns specific to this group of missing persons.FindingsResults suggest that most do not leave the hospital grounds or stay within a 5-km radius. Others were found close to the hospital, within city limits and/or returned of their own volition. By identifying these spatial behaviour patterns associated with missing hospital patients, police can refine probable search areas, allocate resources more efficiently, find the missing faster and develop better-informed responses and collaborative policies.Originality/valueOur research represents the first empirical investigation into missing persons from hospital settings through a spatial perspective. Through descriptive statistical and spatial analyses, we determine the distance between the hospital a given individual was reported missing from and the location of where they were ultimately found.

Limited need for hospital resources among patients brought to hospital by the emergency medical services

Background In Sweden, the majority of patients who are transported to hospital by the emergency medical services (EMS) are relatively old and the majority suffer from comorbidity. About half these patients are admitted to a hospital ward and will stay in hospital. However, the other half will only make a visit to the emergency department (ED). The burden on the ED is extensive and many elderly patients have to stay for many hours in the ED. Aim To describe the patients who are brought to hospital by the EMS, with particular emphasis on those that were discharged from the ED, and to assess the proportion of these patients who did not require hospital resources, which could mean that they were candidates for primary care (PC). Methods An observational analysis of a cohort of patients who were transported to hospital by the EMS in 2016 in the Municipality of Gothenburg. Results In all, 5,326 patients were transported to hospital by the EMS of which 52% were discharged directly from the ED. These patients included 37% assessed as not requiring hospital resources. The three most common causes of contact with the EMS in this subset were abdominal pain (15%), back pain (8%) and non-specified disease (7%). Of these patients, 77% had contact with a physician in the ED, whereas 6% had contact with a nurse and 17% left the ED without any contact. Twenty-six per cent were given advice on follow-up in PC. Conclusions Among patients who were brought to hospital by the EMS, more than half were discharged directly from the ED. Among these patients, 37% were assessed as not requiring hospital resources. These patients comprised 15% of the overall study cohort and may be candidates for primary care.

Modeling COVID-19 care capacity in a major health system

Hospital resources, especially critical care beds and ventilators, have been strained by additional demand throughout the COVID-19 pandemic. Rationing of scarce critical care resources may occur when available resource limits are exceeded. However, the dynamic nature of the COVID-19 pandemic and variability in projections of the future burden of COVID-19 infection pose challenges for optimizing resource allocation to critical care units in hospitals. Connecticut experienced a spike in the number of COVID-19 cases between March and June 2020. Uncertainty about future incidence made it difficult to predict the magnitude and duration of the increased COVID-19 burden on the healthcare system. In this paper, we describe a model of COVID-19 hospital capacity and occupancy that generates estimates of the resources necessary to accommodate COVID-19 patients under infection scenarios of varying severity. We present the model structure and dynamics, procedure for parameter estimation, and publicly available web application where we implemented the tool. We then describe calibration using data from over 3,000 COVID-19 patients seen at the Yale-New Haven Health System between March and July 2020. We conclude with recommendations for modeling tools to inform decision-making using incomplete information during future crises.