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1.
Crit Care Med ; 49(9): 1439-1450, 2021 09 01.
Article in English | MEDLINE | ID: covidwho-1434523

ABSTRACT

OBJECTIVES: To evaluate the impact of ICU surge on mortality and to explore clinical and sociodemographic predictors of mortality. DESIGN: Retrospective cohort analysis. SETTING: NYC Health + Hospitals ICUs. PATIENTS: Adult ICU patients with coronavirus disease 2019 admitted between March 24, and May 12, 2020. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Hospitals reported surge levels daily. Uni- and multivariable analyses were conducted to assess factors impacting in-hospital mortality. Mortality in Hispanic patients was higher for high/very high surge compared with low/medium surge (69.6% vs 56.4%; p = 0.0011). Patients 65 years old and older had similar mortality across surge levels. Mortality decreased from high/very high surge to low/medium surge in, patients 18-44 years old and 45-64 (18-44 yr: 46.4% vs 27.3%; p = 0.0017 and 45-64 yr: 64.9% vs 53.2%; p = 0.002), and for medium, high, and very high poverty neighborhoods (medium: 69.5% vs 60.7%; p = 0.019 and high: 71.2% vs 59.7%; p = 0.0078 and very high: 66.6% vs 50.7%; p = 0.0003). In the multivariable model high surge (high/very high vs low/medium odds ratio, 1.4; 95% CI, 1.2-1.8), race/ethnicity (Black vs White odds ratio, 1.5; 95% CI, 1.1-2.0 and Asian vs White odds ratio 1.5; 95% CI, 1.0-2.3; other vs White odds ratio 1.5, 95% CI, 1.0-2.3), age (45-64 vs 18-44 odds ratio, 2.0; 95% CI, 1.6-2.5 and 65-74 vs 18-44 odds ratio, 5.1; 95% CI, 3.3-8.0 and 75+ vs 18-44 odds ratio, 6.8; 95% CI, 4.7-10.1), payer type (uninsured vs commercial/other odds ratio, 1.7; 95% CI, 1.2-2.3; medicaid vs commercial/other odds ratio, 1.3; 95% CI, 1.1-1.5), neighborhood poverty (medium vs low odds ratio 1.6, 95% CI, 1.0-2.4 and high vs low odds ratio, 1.8; 95% CI, 1.3-2.5), comorbidities (diabetes odds ratio, 1.6; 95% CI, 1.2-2.0 and asthma odds ratio, 1.4; 95% CI, 1.1-1.8 and heart disease odds ratio, 2.5; 95% CI, 2.0-3.3), and interventions (mechanical ventilation odds ratio, 8.8; 95% CI, 6.1-12.9 and dialysis odds ratio, 3.0; 95% CI, 1.9-4.7) were significant predictors for mortality. CONCLUSIONS: Patients admitted to ICUs with higher surge scores were at greater risk of death. Impact of surge levels on mortality varied across sociodemographic groups.


Subject(s)
COVID-19/mortality , Hospital Mortality/trends , Adolescent , Adult , Aged , Analysis of Variance , Female , Hospital Mortality/ethnology , Hospitals, Public/statistics & numerical data , Humans , Intensive Care Units , Male , Middle Aged , New York City/epidemiology , Odds Ratio , Patient Transfer/statistics & numerical data , Retrospective Studies , Young Adult
2.
West J Emerg Med ; 22(3): 561-564, 2021 May 17.
Article in English | MEDLINE | ID: covidwho-1266891

ABSTRACT

INTRODUCTION: During the coronavirus disease 2019 (COVID-19) pandemic, a reduction in emergency department (ED) visits was seen nationally according to the US Centers for Disease Control and Prevention. However, no data currently exists for the impact of ED transfers to a higher level of care during this same time period. The primary objective of the study was to determine whether the COVID-19 pandemic affected the rate of non-COVID-19 transfers from a rural community ED. METHODS: We completed a retrospective chart review of all ED patients who presented to Kingman Regional Medical Center in Kingman, Arizona, from March 1-June 31, 2019 and March 1-June 31, 2020. To ensure changes were not due to seasonal trends, we examined transfer rates from the same four-month period in 2019 and 2020. Patients were included in the study if they were transferred to an outside facility for a higher level of care not related to COVID-19. RESULTS: Between the time periods studied there was a 25.33% (P = 0.001) reduction in total ED volume and a 21.44% (P = 0.009) reduction in ED transfers to a higher level of care. No statistical difference was noted in ED transfer volume following adjustment for decreased ED volumes. Transfers for gastroenterology (45%; P = 0.021), neurosurgery (29.2%; P = 0.029), neurology (76.3%; P < 0.001), trauma (37.5%; P = 0.039), urology (41.8%; P = 0.012), and surgery (56.3%; P = 0.028) all experienced a decrease in transfer rates during the time period studied. When gender was considered, males exhibited an increased rate of transfers to psychiatric facilities (P = 0.018). CONCLUSION: Significant reductions in both ED volume and transfers have coincided with the emergence of the COVID-19 pandemic. Further research is needed to determine how the current pandemic has affected patient care.


Subject(s)
COVID-19/epidemiology , Emergency Service, Hospital/statistics & numerical data , Pandemics , Patient Transfer/statistics & numerical data , Adult , Arizona/epidemiology , Female , Humans , Male , Middle Aged , Retrospective Studies , Rural Population , SARS-CoV-2
3.
Air Med J ; 40(4): 220-224, 2021.
Article in English | MEDLINE | ID: covidwho-1245832

ABSTRACT

OBJECTIVE: There are limited data regarding the typical characteristics of coronavirus disease 2019 (COVID-19) patients requiring interfacility transport or the clinical capabilities of the out-of-hospital transport clinicians required to provide safe transport. The objective of this study is to provide epidemiologic data and highlight the clinical skill set and decision making needed to transport critically ill COVID-19 patients. METHODS: A retrospective chart review of persons under investigation for COVID-19 transported during the first 6 months of the pandemic by Johns Hopkins Lifeline was performed. Patients who required interfacility transport and tested positive for severe acute respiratory syndrome coronavirus 2 by polymerase chain reaction assay were included in the analysis. RESULTS: Sixty-eight patients (25.4%) required vasopressor support, 35 patients (13.1%) were pharmacologically paralyzed, 15 (5.60%) were prone, and 1 (0.75%) received an inhaled pulmonary vasodilator. At least 1 ventilator setting change occurred for 59 patients (22.0%), and ventilation mode was changed for 11 patients (4.10%) during transport. CONCLUSION: The safe transport of critically ill patients with COVID-19 requires experience with vasopressors, paralytic medications, inhaled vasodilators, prone positioning, and ventilator management. The frequency of initiated critical interventions and ventilator adjustments underscores the tenuous nature of these patients and highlights the importance of transport clinician reassessment, critical thinking, and decision making.


Subject(s)
COVID-19/therapy , Clinical Competence , Clinical Decision-Making/methods , Critical Care/methods , Transportation of Patients/methods , Adult , Aged , Aged, 80 and over , COVID-19/diagnosis , Combined Modality Therapy , Critical Care/standards , Critical Care/statistics & numerical data , Critical Illness , Female , Humans , Male , Maryland , Middle Aged , Patient Acuity , Patient Transfer/methods , Patient Transfer/standards , Patient Transfer/statistics & numerical data , Retrospective Studies , Transportation of Patients/standards , Transportation of Patients/statistics & numerical data
4.
Air Med J ; 40(4): 211-215, 2021.
Article in English | MEDLINE | ID: covidwho-1237589

ABSTRACT

OBJECTIVE: As part of the humanitarian response to the coronavirus disease 2019 (COVID-19) pandemic, the German and French Armed Forces provided air transport for patients from overwhelmed regional hospitals in Italy and France. The objective of this study was to analyze the characteristics of the missions and the medical conditions of COVID-19 patients transported during an air medical evacuation on fixed wing aircraft in March and April 2020. METHOD: This was a retrospective analysis of transport records as well as other documents for 58 COVID-19 patients requiring artificial ventilation. RESULTS: The median age of the transported patients was 61.5 years, and 61% of them had preexisting medical conditions. They had been ventilated for a median of 5 days and experienced the first symptoms 18 days before transport. The patients flown out of France had less days of ventilation before flight, a lower end-tidal carbon dioxide level at the beginning of the flight, and a lower Charlson Comorbidity Index. There were also some differences between the ventilation and the flight level flown by the 2 air forces. CONCLUSION: The intensive care transport of ventilated COVID-19 patients requires highly qualified personnel and appropriate equipment and should be planned appropriately.


Subject(s)
Air Ambulances , COVID-19/diagnosis , COVID-19/therapy , Critical Care , Patient Transfer , Aged , Air Ambulances/organization & administration , Air Ambulances/statistics & numerical data , COVID-19/epidemiology , Comorbidity , Critical Care/methods , Critical Care/organization & administration , Critical Care/statistics & numerical data , Europe/epidemiology , Female , Humans , Male , Middle Aged , Pandemics , Patient Transfer/methods , Patient Transfer/organization & administration , Patient Transfer/statistics & numerical data , Retrospective Studies , Severity of Illness Index
5.
Int J Health Policy Manag ; 9(10): 415-418, 2020 10 01.
Article in English | MEDLINE | ID: covidwho-1068305

ABSTRACT

The world is urgently looking for ways to flatten the coronavirus disease 2019 (COVID-19) curve, and many governments have resorted to implementing strict lockdowns, as researchers show the effectiveness of China's approaches in containing the virus. However, this paper argues that the draconian lockdowns instituted in Wuhan, Hubei, China, may have actually contributed to intensifying patient surges and incapacitating local health systems. Medical aids were rushed to Hubei and new hospitals were rapidly built, however, the healthcare system was still unable to match the staggering increase of patients in the early stages of the lockdowns. The paper proposes using patient evacuation to enhance sustainable COVID-19 mitigation during lockdowns. It demonstrates that patients in Hubei could have been transported to other Chinese provinces where hospitals were under-utilized. This could have theoretically saved thousands of lives by reducing inequities between Hubei and the rest of China in healthcare capacity for treating COVID-19 patients.


Subject(s)
COVID-19/prevention & control , COVID-19/therapy , Communicable Disease Control/methods , Health Status Disparities , Patient Transfer/statistics & numerical data , Quarantine/statistics & numerical data , China , Humans , SARS-CoV-2
7.
Diabetes Metab ; 47(4): 101222, 2021 07.
Article in English | MEDLINE | ID: covidwho-1002473

ABSTRACT

BACKGROUND: Our study aimed to compare the clinical outcomes of patients with and without diabetes admitted to hospital with COVID-19. METHODS: This retrospective multicentre cohort study comprised 24 tertiary medical centres in France, and included 2851 patients (675 with diabetes) hospitalized for COVID-19 between 26 February and 20 April 2020. A propensity score-matching (PSM) method (1:1 matching including patients' characteristics, medical history, vital statistics and laboratory results) was used to compare patients with and without diabetes (n = 603 per group). The primary outcome was admission to an intensive care unit (ICU) and/or in-hospital death. RESULTS: After PSM, all baseline characteristics were well balanced between those with and without diabetes: mean age was 71.2 years; 61.8% were male; and mean BMI was 29 kg/m2. A history of cardiovascular, chronic kidney and chronic obstructive pulmonary diseases were found in 32.8%, 22.1% and 6.4% of participants, respectively. The risk of experiencing the primary outcome was similar in patients with or without diabetes [hazard ratio (HR): 1.16, 95% confidence interval (CI): 0.95-1.41; P = 0.14], and was 1.29 (95% CI: 0.97-1.69) for in-hospital death, 1.26 (95% CI: 0.9-1.72) for death with no transfer to an ICU and 1.14 (95% CI: 0.88-1.47) with transfer to an ICU. CONCLUSION: In this retrospective study cohort of patients hospitalized for COVID-19, diabetes was not significantly associated with a higher risk of severe outcomes after PSM. TRIAL REGISTRATION NUMBER: NCT04344327.


Subject(s)
COVID-19/epidemiology , Diabetes Mellitus/epidemiology , Hospital Mortality , Intensive Care Units , Patient Transfer/statistics & numerical data , Aged , Aged, 80 and over , COVID-19/mortality , COVID-19/physiopathology , Comorbidity , Female , France/epidemiology , Humans , Length of Stay , Male , Middle Aged , Propensity Score , Retrospective Studies , SARS-CoV-2
8.
Healthc (Amst) ; 9(1): 100512, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-987773

ABSTRACT

Little is known about the follow-up healthcare needs of patients hospitalized with coronavirus disease 2019 (COVID-19) after hospital discharge. Due to the unique circumstances of providing transitional care in a pandemic, post-discharge providers must adapt to specific needs and limitations identified for the care of COVID-19 patients. In this study, we conducted a retrospective chart review of all hospitalized COVID-19 patients discharged from an Emory Healthcare Hospital in Atlanta, GA from March 26 to April 21, 2020 to characterize their post-discharge care plans. A total of 310 patients were included in the study (median age 58, range: 23-99; 51.0% female; 69.0% African American). The most common presenting comorbidities were hypertension (200, 64.5%), obesity (BMI≥30) (138, 44.5%), and diabetes mellitus (112, 36.1%). The median length of hospitalization was 5 days (range: 0-33). Sixty-seven patients (21.6%) were admitted to the intensive care unit and 42 patients (13.5%) received invasive mechanical ventilation. The most common complications recorded at discharge were electrolyte abnormalities (124, 40.0%), acute kidney injury (86, 27.7%) and sepsis (55, 17.7%). The majority of patients were discharged directly home (281, 90.6%). Seventy-five patients (24.2%) required any home service including home health and home oxygen therapy. The most common follow-up need was an appointment with a primary care provider (258, 83.2%). Twenty-four patients (7.7%) had one or more visit to an ED after discharge and 16 patients (5.2%) were readmitted. To our knowledge, this is the first large study to report on post-discharge medical care for COVID-19 patients.


Subject(s)
COVID-19/therapy , Hospitalization/trends , Patient Discharge/standards , Patient Transfer/standards , Adult , Aged , Female , Hospitalization/statistics & numerical data , Humans , Male , Middle Aged , Patient Discharge/statistics & numerical data , Patient Transfer/methods , Patient Transfer/statistics & numerical data
9.
Biol Sex Differ ; 11(1): 57, 2020 10 16.
Article in English | MEDLINE | ID: covidwho-874072

ABSTRACT

BACKGROUND: Among the unknowns posed by the coronavirus disease 2019 (COVID-19) outbreak, the role of biological sex to explain disease susceptibility and progression is still a matter of debate, with limited sex-disaggregated data available. METHODS: A retrospective analysis was performed to assess if sex differences exist in the clinical manifestations and transitions of care among hospitalized individuals dying with laboratory-confirmed SARS-CoV-2 infection in Italy (February 27-June 11, 2020). Clinical characteristics and the times from symptoms' onset to admission, nasopharyngeal swab, and death were compared between sexes. Adjusted multivariate analysis was performed to identify the clinical features associated with male sex. RESULTS: Of the 32,938 COVID-19-related deaths that occurred in Italy, 3517 hospitalized and deceased individuals with COVID-19 (mean 78 ± 12 years, 33% women) were analyzed. At admission, men had a higher prevalence of ischemic heart disease (adj-OR = 1.76, 95% CI 1.39-2.23), chronic obstructive pulmonary disease (adj-OR = 1.7, 95% CI 1.29-2.27), and chronic kidney disease (adj-OR = 1.48, 95% CI 1.13-1.96), while women were older and more likely to have dementia (adj-OR = 0.73, 95% CI 0.55-0.95) and autoimmune diseases (adj-OR = 0.40, 95% CI 0.25-0.63), yet both sexes had a high level of multimorbidity. The times from symptoms' onset to admission and nasopharyngeal swab were slightly longer in men despite a typical acute respiratory illness with more frequent fever at the onset. Men received more often experimental therapy (adj-OR = 2.89, 95% CI 1.45-5.74) and experienced more likely acute kidney injury (adj-OR = 1.47, 95% CI 1.13-1.90). CONCLUSIONS: Men and women dying with COVID-19 had different clinical manifestations and transitions of care. Identifying sex-specific features in individuals with COVID-19 and fatal outcome might inform preventive strategies.


Subject(s)
Coronavirus Infections/therapy , Patient Transfer/statistics & numerical data , Pneumonia, Viral/therapy , Aged , Aged, 80 and over , Betacoronavirus/isolation & purification , COVID-19 , Comorbidity , Coronavirus Infections/epidemiology , Female , Hospitalization/statistics & numerical data , Humans , Italy/epidemiology , Male , Middle Aged , Multimorbidity , Multivariate Analysis , Pandemics , Pneumonia, Viral/epidemiology , Prevalence , Retrospective Studies , Risk Factors , SARS-CoV-2 , Sex Factors
10.
Air Med J ; 39(5): 404-409, 2020.
Article in English | MEDLINE | ID: covidwho-866388

ABSTRACT

Objective: There is a coronavirus disease 2019 (COVID-19) pandemic. We aimed to describe the characteristics of patients transported by the Royal Flying Doctor Service (RFDS) for confirmed or suspected COVID-19 and to investigate the surge capacity of and operational implications for the RFDS in dealing with COVID-19. Methods: This was a prospective cohort study. To determine the characteristics of patients transported for confirmed or suspected COVID-19, we included patient data from February 2, 2020, to May 6, 2020. To investigate the surge capacity and operational implications for the RFDS in dealing with COVID-19, we built and validated an interactive operations area-level discrete event simulation decision support model underpinned by RFDS air medical activity data from 2015 to 2019 (4 years). This model was subsequently used in a factorial in silico experiment to systematically investigate both the supply of RFDS air medical services and the increased rates of demand for these services for diseases of the respiratory system. Results: The RFDS conducted 291 patient episodes of care for confirmed or suspected COVID-19. This included 288 separate patients, including 136 men and 119 women (sex missing = 33), with a median age of 62.0 years (interquartile range, 43.5-74.9 years). The simulation decision support model we developed is capable of providing dynamic and real-time support for RFDS decision makers in understanding the system's performance under uncertain COVID-19 demand. With increased COVID-19-related demand, the ability of the RFDS to cope will be driven by the number of aircraft available. The simulation model provided each aviation section with estimated numbers of aircraft required to meet a range of anticipated demands. Conclusion: Despite the lack of certainty in the actual level of COVID-19-related demand for RFDS services, modeling demonstrates that the robustness of meeting such demand increases with the number of operational and medically staffed aircraft.


Subject(s)
Air Ambulances/statistics & numerical data , Computer Simulation , Coronavirus Infections/epidemiology , Patient Transfer/statistics & numerical data , Pneumonia, Viral/epidemiology , Surge Capacity , Adult , Aged , Australia/epidemiology , Betacoronavirus , COVID-19 , Cohort Studies , Female , Humans , Male , Middle Aged , Pandemics , Prospective Studies , SARS-CoV-2
11.
World Neurosurg ; 144: e710-e713, 2020 12.
Article in English | MEDLINE | ID: covidwho-773190

ABSTRACT

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) pandemic has set a huge challenge to the delivery of neurosurgical services, including the transfer of patients. We aimed to share our strategy in handling neurosurgical emergencies at a remote center in Borneo island. Our objectives included discussing the logistic and geographic challenges faced during the COVID-19 pandemic. METHODS: Miri General Hospital is a remote center in Sarawak, Malaysia, serving a population with difficult access to neurosurgical services. Two neurosurgeons were stationed here on a rotational basis every fortnight during the pandemic to handle neurosurgical cases. Patients were triaged depending on their urgent needs for surgery or transfer to a neurosurgical center and managed accordingly. All patients were screened for potential risk of contracting COVID-19 prior to the surgery. Based on this, the level of personal protective equipment required for the health care workers involved was determined. RESULTS: During the initial 6 weeks of the Movement Control Order in Malaysia, there were 50 urgent neurosurgical consultations. Twenty patients (40%) required emergency surgery or intervention. There were 9 vascular (45%), 5 trauma (25%), 4 tumor (20%), and 2 hydrocephalus cases (10%). Eighteen patients were operated at Miri General Hospital, among whom 17 (94.4%) survived. Ninety percent of anticipated transfers were avoided. None of the medical staff acquired COVID-19. CONCLUSIONS: This framework allowed timely intervention for neurosurgical emergencies (within a safe limit), minimized transfer, and enabled uninterrupted neurosurgical services at a remote center with difficult access to neurosurgical care during a pandemic.


Subject(s)
Brain Neoplasms/surgery , Craniocerebral Trauma/surgery , Emergencies , Hemorrhagic Stroke/surgery , Hydrocephalus/surgery , Neurosurgery , Neurosurgical Procedures/statistics & numerical data , Patient Transfer/statistics & numerical data , Air Ambulances , Borneo/epidemiology , COVID-19/epidemiology , Central Nervous System Vascular Malformations/surgery , Female , Hospitals, General , Humans , Malaysia/epidemiology , Male , Personal Protective Equipment , Skull Base Neoplasms/surgery , Transportation of Patients , Triage
12.
BMJ Open ; 10(8): e039177, 2020 08 20.
Article in English | MEDLINE | ID: covidwho-725772

ABSTRACT

OBJECTIVE: COVID-19 started spreading widely in China in January 2020. Outpatient fever clinics (FCs), instituted during the SARS epidemic in 2003, were upgraded to serve for COVID-19 screening and prevention of disease transmission in large tertiary hospitals in China. FCs were hoped to relieve some of the healthcare burden from emergency departments (EDs). We aimed to evaluate the effect of upgrading the FC system on rates of nosocomial COVID-19 infection and ED patient attendance at Peking Union Medical College Hospital (PUMCH). DESIGN: A retrospective cohort study. PARTICIPANTS: A total of 6365 patients were screened in the FC. METHODS: The FC of PUMCH was upgraded on 20 January 2020. We performed a retrospective study of patients presenting to the FC between 12 December 2019 and 29 February 2020. The date when COVID-19 was declared an outbreak in Beijing was 20 January 2020. Two groups of data were collected and subsequently compared with each other: the first group of data was collected within 40 days before 20 January 2020; the second group of data was collected within 40 days after 20 January 2020. All necessary data, including patient baseline information, diagnosis, follow-up conditions and the transfer records between the FC and ED, were collected and analysed. RESULTS: 6365 patients were screened in the FC, among whom 2912 patients were screened before 21 January 2020, while 3453 were screened afterward. Screening results showed that upper respiratory infection was the major disease associated with fever. After the outbreak of COVID-19, the number of patients who were transferred from the FC to the ED decreased significantly (39.21% vs 15.75%, p<0.001), and patients generally spent more time in the FC (55 vs 203 min, p<0.001), compared with before the outbreak. For critically ill patients waiting for their screening results, the total length of stay in the FC was 22 min before the outbreak, compared with 442 min after the outbreak (p<0.001). The number of in-hospital deaths of critically ill patients in the FC was 9 out of 29 patients before the outbreak and 21 out of 38 after the outbreak (p<0.05). Nineteen cases of COVID-19 were confirmed in the FC during the period of this study. However, no other patients nor any healthcare providers were cross-infected. CONCLUSION: The workload of the FC increased significantly after the COVID-19 outbreak. New protocols regarding the use of FC likely helped prevent the spread of COVID-19 within the hospital. The upgraded FC also reduced the burden on the ED.


Subject(s)
Coronavirus Infections/diagnosis , Emergency Service, Hospital/organization & administration , Fever/virology , Outpatient Clinics, Hospital/organization & administration , Pneumonia, Viral/diagnosis , Tertiary Care Centers/organization & administration , Workload , Adult , Betacoronavirus , COVID-19 , China/epidemiology , Coronavirus Infections/transmission , Cross Infection/prevention & control , Emergency Service, Hospital/statistics & numerical data , Facilities and Services Utilization , Female , Humans , Length of Stay , Male , Middle Aged , Outpatient Clinics, Hospital/statistics & numerical data , Pandemics , Patient Transfer/statistics & numerical data , Pneumonia, Viral/transmission , Retrospective Studies , SARS-CoV-2 , Tertiary Care Centers/statistics & numerical data
13.
CMAJ Open ; 8(3): E514-E521, 2020.
Article in English | MEDLINE | ID: covidwho-725389

ABSTRACT

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak increases the importance of strategies to enhance urgent medical care delivery in long-term care (LTC) facilities that could potentially reduce transfers to emergency departments. The study objective was to model resource requirements to deliver virtual urgent medical care in LTC facilities. METHODS: We used data from all general medicine inpatient admissions at 7 hospitals in the Greater Toronto Area, Ontario, Canada, over a 7.5-year period (Apr. 1, 2010, to Oct. 31, 2017) to estimate historical patterns of hospital resource use by LTC residents. We estimated an upper bound of potentially avoidable transfers by combining data on short admissions (≤ 72 h) with historical data on the proportion of transfers from LTC facilities for which patients were discharged from the emergency department without admission. Regression models were used to extrapolate future resource requirements, and queuing models were used to estimate physician staffing requirements to perform virtual assessments. RESULTS: There were 235 375 admissions to general medicine wards, and residents of LTC facilities (age 16 yr or older) accounted for 9.3% (n = 21 948) of these admissions. Among the admissions of residents of LTC facilities, short admissions constituted 24.1% (n = 5297), and for 99.8% (n = 5284) of these admissions, the patient received laboratory testing, for 86.9% (n = 4604) the patient received plain radiography, for 41.5% (n = 2197) the patient received computed tomography and for 81.2% (n = 4300) the patient received intravenous medications. If all patients who have short admissions and are transferred from the emergency department were diverted to outpatient care, the average weekly demand for outpatient imaging per hospital would be 2.6 ultrasounds, 11.9 computed tomographic scans and 23.9 radiographs per week. The average daily volume of urgent medical virtual assessments would range from 2.0 to 5.8 per hospital. A single centralized virtual assessment centre staffed by 2 or 3 physicians would provide services similar in efficiency (measured by waiting time for physician assessment) to 7 separate centres staffed by 1 physician each. INTERPRETATION: The provision of acute medical care to LTC residents at their facility would probably require rapid access to outpatient diagnostic imaging, within-facility access to laboratory services and intravenous medication and virtual consultations with physicians. The results of this study can inform efforts to deliver urgent medical care in LTC facilities in light of a potential surge in COVID-19 cases.


Subject(s)
COVID-19/diagnosis , Health Resources/supply & distribution , Physicians/supply & distribution , SARS-CoV-2/genetics , Skilled Nursing Facilities/statistics & numerical data , Telemedicine/statistics & numerical data , Aged , Aged, 80 and over , Ambulatory Care , COVID-19/epidemiology , COVID-19/virology , Cross-Sectional Studies , Diagnostic Imaging/statistics & numerical data , Disease Outbreaks/prevention & control , Disease Outbreaks/statistics & numerical data , Emergency Service, Hospital/statistics & numerical data , Female , Hospitalization/statistics & numerical data , Hospitalization/trends , Humans , Long-Term Care/statistics & numerical data , Male , Middle Aged , Ontario/epidemiology , Patient Transfer/statistics & numerical data , Retrospective Studies , Skilled Nursing Facilities/organization & administration , Workforce/statistics & numerical data
14.
Anaesth Crit Care Pain Med ; 39(3): 361-362, 2020 06.
Article in English | MEDLINE | ID: covidwho-141545

Subject(s)
Betacoronavirus , Coronavirus Infections , Critical Care/organization & administration , Hospitals, Military/organization & administration , Intensive Care Units/organization & administration , Mobile Health Units/organization & administration , Pandemics , Pneumonia, Viral , Respiratory Distress Syndrome/therapy , Aged , Anesthesia, General/statistics & numerical data , Bed Conversion , COVID-19 , Coronavirus Infections/complications , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/transmission , Critical Care/statistics & numerical data , Emergency Medical Dispatch/organization & administration , Female , France/epidemiology , Hospital Bed Capacity, under 100 , Hospital Shared Services/organization & administration , Hospitals, General/organization & administration , Hospitals, Military/statistics & numerical data , Humans , Infectious Disease Transmission, Patient-to-Professional/prevention & control , Intensive Care Units/statistics & numerical data , Intensive Care Units/supply & distribution , Intubation, Intratracheal/statistics & numerical data , Length of Stay/statistics & numerical data , Male , Middle Aged , Mobile Health Units/statistics & numerical data , Occupational Diseases/prevention & control , Pandemics/prevention & control , Patient Admission/statistics & numerical data , Patient Transfer/methods , Patient Transfer/statistics & numerical data , Personal Protective Equipment , Pneumonia, Viral/complications , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/transmission , Procedures and Techniques Utilization , Respiration, Artificial/statistics & numerical data , Respiratory Distress Syndrome/epidemiology , Respiratory Distress Syndrome/etiology , SARS-CoV-2
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