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Peter D, Li SX, Wang Y, Zhang J, Grady J, McDowell K, Norton E, Lin Z, Bernheim S, Venkatesh AK, Fleisher LA, Schreiber M, Suter LG, Triche EW. Pre-COVID-19 hospital quality and hospital response to COVID-19: examining associations between risk-adjusted mortality for patients hospitalised with COVID-19 and pre-COVID-19 hospital quality. BMJ Open 2024; 14:e077394. [PMID: 38553067 PMCID: PMC10982775 DOI: 10.1136/bmjopen-2023-077394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 02/25/2024] [Indexed: 04/02/2024] Open
Abstract
OBJECTIVES The extent to which care quality influenced outcomes for patients hospitalised with COVID-19 is unknown. Our objective was to determine if prepandemic hospital quality is associated with mortality among Medicare patients hospitalised with COVID-19. DESIGN This is a retrospective observational study. We calculated hospital-level risk-standardised in-hospital and 30-day mortality rates (risk-standardised mortality rates, RSMRs) for patients hospitalised with COVID-19, and correlation coefficients between RSMRs and pre-COVID-19 hospital quality, overall and stratified by hospital characteristics. SETTING Short-term acute care hospitals and critical access hospitals in the USA. PARTICIPANTS Hospitalised Medicare beneficiaries (Fee-For-Service and Medicare Advantage) age 65 and older hospitalised with COVID-19, discharged between 1 April 2020 and 30 September 2021. INTERVENTION/EXPOSURE Pre-COVID-19 hospital quality. OUTCOMES Risk-standardised COVID-19 in-hospital and 30-day mortality rates (RSMRs). RESULTS In-hospital (n=4256) RSMRs for Medicare patients hospitalised with COVID-19 (April 2020-September 2021) ranged from 4.5% to 59.9% (median 18.2%; IQR 14.7%-23.7%); 30-day RSMRs ranged from 12.9% to 56.2% (IQR 24.6%-30.6%). COVID-19 RSMRs were negatively correlated with star rating summary scores (in-hospital correlation coefficient -0.41, p<0.0001; 30 days -0.38, p<0.0001). Correlations with in-hospital RSMRs were strongest for patient experience (-0.39, p<0.0001) and timely and effective care (-0.30, p<0.0001) group scores; 30-day RSMRs were strongest for patient experience (-0.34, p<0.0001) and mortality (-0.33, p<0.0001) groups. Patients admitted to 1-star hospitals had higher odds of mortality (in-hospital OR 1.87, 95% CI 1.83 to 1.91; 30-day OR 1.46, 95% CI 1.43 to 1.48) compared with 5-star hospitals. If all hospitals performed like an average 5-star hospital, we estimate 38 000 fewer COVID-19-related deaths would have occurred between April 2020 and September 2021. CONCLUSIONS Hospitals with better prepandemic quality may have care structures and processes that allowed for better care delivery and outcomes during the COVID-19 pandemic. Understanding the relationship between pre-COVID-19 hospital quality and COVID-19 outcomes will allow policy-makers and hospitals better prepare for future public health emergencies.
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Affiliation(s)
- Doris Peter
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
| | - Shu-Xia Li
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Yongfei Wang
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Jing Zhang
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Jacqueline Grady
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
| | - Kerry McDowell
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
| | - Erica Norton
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
| | - Zhenqiu Lin
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Susannah Bernheim
- The Center for Medicare and Medicaid Innovation, Centers for Medicare and Medicaid Services, Baltimore, Maryland, USA
| | - Arjun K Venkatesh
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
- Department of Emergency Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Lee A Fleisher
- Department of Anesthesiology and Critical Care, Perelman School of Medicine, Philadelphia, PA, Philadelphia, PA, USA
| | - Michelle Schreiber
- The Center for Clinical Standards and Quality, Centers for Medicare and Medicaid Services, Baltimore, Maryland, USA
| | - Lisa G Suter
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
- Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut, USA
| | - Elizabeth W Triche
- Center for Outcomes Research and Evaluation, Yale New Haven Health System, New Haven, Connecticut, USA
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Neupane M, De Jonge N, Angelo S, Sarzynski S, Sun J, Rochwerg B, Hick J, Mitchell SH, Warner S, Mancera A, Cooper D, Kadri SS. Measures and Impact of Caseload Surge During the COVID-19 Pandemic: A Systematic Review. Crit Care Med 2024:00003246-990000000-00312. [PMID: 38517234 DOI: 10.1097/ccm.0000000000006263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2024]
Abstract
OBJECTIVES COVID-19 pandemic surges strained hospitals globally. We performed a systematic review to examine measures of pandemic caseload surge and its impact on mortality of hospitalized patients. DATA SOURCES PubMed, Embase, and Web of Science. STUDY SELECTION English-language studies published between December 1, 2019, and November 22, 2023, which reported the association between pandemic "surge"-related measures and mortality in hospitalized patients. DATA EXTRACTION Three authors independently screened studies, extracted data, and assessed individual study risk of bias. We assessed measures of surge qualitatively across included studies. Given multidomain heterogeneity, we semiquantitatively aggregated surge-mortality associations. DATA SYNTHESIS Of 17,831 citations, we included 39 studies, 17 of which specifically described surge effects in ICU settings. The majority of studies were from high-income countries (n = 35 studies) and included patients with COVID-19 (n = 31). There were 37 different surge metrics which were mapped into four broad themes, incorporating caseloads either directly as unadjusted counts (n = 11), nested in occupancy (n = 14), including additional factors (e.g., resource needs, speed of occupancy; n = 10), or using indirect proxies (e.g., altered staffing ratios, alternative care settings; n = 4). Notwithstanding metric heterogeneity, 32 of 39 studies (82%) reported detrimental adjusted odds/hazard ratio for caseload surge-mortality outcomes, reporting point estimates of up to four-fold increased risk of mortality. This signal persisted among study subgroups categorized by publication year, patient types, clinical settings, and country income status. CONCLUSIONS Pandemic caseload surge was associated with lower survival across most studies regardless of jurisdiction, timing, and population. Markedly variable surge strain measures precluded meta-analysis and findings have uncertain generalizability to lower-middle-income countries (LMICs). These findings underscore the need for establishing a consensus surge metric that is sensitive to capturing harms in everyday fluctuations and future pandemics and is scalable to LMICs.
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Affiliation(s)
- Maniraj Neupane
- Clinical Epidemiology Section, Critical Care Medicine Department, National Institutes of Health Clinical Center, Bethesda, MD
- Critical Care Medicine Branch, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Nathaniel De Jonge
- Clinical Epidemiology Section, Critical Care Medicine Department, National Institutes of Health Clinical Center, Bethesda, MD
| | - Sahil Angelo
- Department of Medicine, University of Pittsburgh Medical Center, Pittsburgh, PA
| | - Sadia Sarzynski
- Clinical Epidemiology Section, Critical Care Medicine Department, National Institutes of Health Clinical Center, Bethesda, MD
- Critical Care Medicine Branch, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Junfeng Sun
- Clinical Epidemiology Section, Critical Care Medicine Department, National Institutes of Health Clinical Center, Bethesda, MD
- Critical Care Medicine Branch, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Bram Rochwerg
- Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, ON, Canada
- Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - John Hick
- Department of Emergency Medicine, Hennepin Healthcare, Minneapolis, MN
| | - Steven H Mitchell
- Department of Emergency Medicine, University of Washington, Seattle, WA
| | - Sarah Warner
- Clinical Epidemiology Section, Critical Care Medicine Department, National Institutes of Health Clinical Center, Bethesda, MD
- Critical Care Medicine Branch, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Alex Mancera
- Clinical Epidemiology Section, Critical Care Medicine Department, National Institutes of Health Clinical Center, Bethesda, MD
- Critical Care Medicine Branch, National Heart, Lung, and Blood Institute, Bethesda, MD
| | - Diane Cooper
- Office of Research Services, Division of Library Services, National Institutes of Health, Bethesda, MD
| | - Sameer S Kadri
- Clinical Epidemiology Section, Critical Care Medicine Department, National Institutes of Health Clinical Center, Bethesda, MD
- Critical Care Medicine Branch, National Heart, Lung, and Blood Institute, Bethesda, MD
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Haykal T, Mina J, Fleifel M, Dimassi H, Nasr J, Mahdi A, Harb R, El Hout G, Franjieh E, Mokhbat J, Farra A, Helou M, Husni R. Evolution of COVID-19 infection characteristics in a Lebanese cohort of inpatients during different pandemic periods. Pathog Glob Health 2024; 118:160-169. [PMID: 37482700 PMCID: PMC11141305 DOI: 10.1080/20477724.2023.2239492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/25/2023] Open
Abstract
This study aims to describe COVID-19 patients characteristics, laboratory and imaging results, and the different outcomes of patients admitted to the Lebanese American University Medical Center-Rizk Hospital over a period of 9 months. In this observational retrospective study, data were obtained from electronic medical records of 491 male and female patients from the ages of 17 to 97. Analysis of the patients was performed in 3 periods: August 2020 to October 20 November 202020 to January 2021 and February 2021 to April 2021 corresponding with 3 waves of newly diagnosed cases during this period. The sample showed a male predominance with an average age of 63. The average hospitalization length was 10.1 days. The majority of patients were discharged to quarantine. The distribution of hospitalized cases was significantly correlated to the monthly distribution of newly COVID-19 cases in Lebanon. There was no significant difference in patient's characteristics between the 3 periods of the study (gender, age, body mass index, smoking, and medical conditions). Clinical presentations of the patients varied between the 3 periods. Similarly, the course and outcome of infection varied. Patients received less oxygen during period 1, while more patients were cured during period 3. This study presents the first Lebanese cohort of COVID-19 patients with their medical background, clinical presentation, laboratory results, radiological findings and course of infection with its outcome. It also shows how the relations between the medical manifestation of the COVID-19 pandemic and the socio-political measures of infection control are deeply intertwined.
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Affiliation(s)
- Tony Haykal
- Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Byblos, Lebanon
| | - Jonathan Mina
- Department of Internal Medicine, Staten Island University Hospital, New York, USA
| | - Mohamad Fleifel
- Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Byblos, Lebanon
- Department of Internal Medicine, Lebanese American University Medical Centre-Rizk Hospital, Beirut, Lebanon
| | - Hani Dimassi
- School of Pharmacy, Lebanese American University, Byblos, Lebanon
| | - Janane Nasr
- Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Byblos, Lebanon
- Department of Internal Medicine, Lebanese American University Medical Centre-Rizk Hospital, Beirut, Lebanon
| | - Ahmad Mahdi
- Department of Internal Medicine, Lebanese American University Medical Centre-Rizk Hospital, Beirut, Lebanon
| | - Ranime Harb
- School of Pharmacy, Lebanese American University, Byblos, Lebanon
| | - Ghida El Hout
- Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Byblos, Lebanon
| | - Elissar Franjieh
- Department of Internal Medicine, Lebanese American University Medical Centre-Rizk Hospital, Beirut, Lebanon
| | - Jacques Mokhbat
- Department of Internal Medicine, Lebanese American University Medical Centre-Rizk Hospital, Beirut, Lebanon
| | - Anna Farra
- Department of Internal Medicine, Lebanese American University Medical Centre-Rizk Hospital, Beirut, Lebanon
| | - Mariana Helou
- Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Byblos, Lebanon
| | - Rola Husni
- Gilbert and Rose-Marie Chagoury School of Medicine, Lebanese American University, Byblos, Lebanon
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Meille G, Decker SL, Owens PL, Selden TM. COVID-19 Admission Rates and Changes in US Hospital Inpatient and Intensive Care Unit Occupancy. JAMA HEALTH FORUM 2023; 4:e234206. [PMID: 38038986 PMCID: PMC10692846 DOI: 10.1001/jamahealthforum.2023.4206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 10/02/2023] [Indexed: 12/02/2023] Open
Abstract
Importance The COVID-19 pandemic had unprecedented effects on hospital occupancy, with consequences for hospital operations and patient care. Previous studies of occupancy during COVID-19 have been limited to small samples of hospitals. Objective To measure the association between COVID-19 admission rates and hospital occupancy in different US areas and at different time periods during 2020. Design, Setting, and Participants This cross-sectional study used data from the Healthcare Cost and Utilization Project State Inpatient Databases (2019-2020) for patients in nonfederal acute care hospitals in 45 US states, including the District of Columbia. Data analysis was performed between September 1, 2022, and April 30, 2023. Exposures Each hospital and week in 2020 was categorized based on the number of COVID-19 admissions per 100 beds (<1 [low], 1-4.9, 5-9.9, 10-14.9, or ≥15 [high]). Main Outcomes and Measures The main outcomes were inpatient and intensive care unit (ICU) occupancy. We used regression analysis to estimate the average change in occupancy for each hospital-week in 2020 relative to the same hospital week in 2019. Results This study included 3960 hospitals and 54 355 916 admissions. Of the admissions in the 40 states used for race and ethnicity analyses, 15.7% were for Black patients, 12.9% were for Hispanic patients, 62.5% were for White patients, and 7.2% were for patients of other race or ethnicity; 1.7% of patients were missing these data. Weekly COVID-19 admission rates in 2020 were less than 4 per 100 beds for 63.9% of hospital-weeks and at least 10 in only 15.9% of hospital-weeks. Inpatient occupancy decreased by 12.7% (95% CI, 12.1% to 13.4%) during weeks with low COVID-19 admission rates and increased by 7.9% (95% CI, 6.8% to 9.0%) during weeks with high COVID-19 admission rates. Intensive care unit occupancy rates increased by 67.8% (95% CI, 60.5% to 75.3%) during weeks with high COVID-19 admissions. Increases in ICU occupancy were greatest when weighted to reflect the experience of Hispanic patients. Changes in occupancy were most pronounced early in the pandemic. During weeks with high COVID-19 admissions, occupancy decreased for many service lines, with occupancy by surgical patients declining by 43.1% (95% CI, 38.6% to 47.2%) early in the pandemic. Conclusions and Relevance In this cross-sectional study of US hospital discharges in 45 states in 2020, hospital occupancy decreased during weeks with low COVID-19 admissions and increased during weeks with high COVID-19 admissions, with the largest changes occurring early in the pandemic. These findings suggest that surges in COVID-19 strained ICUs and were associated with large decreases in the number of surgical patients. These occupancy fluctuations may have affected quality of care and hospital finances.
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Affiliation(s)
- Giacomo Meille
- Agency for Healthcare Research and Quality, US Department of Health and Human Services, Rockville, Maryland
| | - Sandra L. Decker
- Agency for Healthcare Research and Quality, US Department of Health and Human Services, Rockville, Maryland
| | - Pamela L. Owens
- Agency for Healthcare Research and Quality, US Department of Health and Human Services, Rockville, Maryland
| | - Thomas M. Selden
- Agency for Healthcare Research and Quality, US Department of Health and Human Services, Rockville, Maryland
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Portela MC, Martins M, Lima SML, de Andrade CLT, de Aguiar Pereira CC. COVID-19 inpatient mortality in Brazil from 2020 to 2022: a cross-sectional overview study based on secondary data. Int J Equity Health 2023; 22:238. [PMID: 37978531 PMCID: PMC10655483 DOI: 10.1186/s12939-023-02037-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Accepted: 10/12/2023] [Indexed: 11/19/2023] Open
Abstract
BACKGROUND In Brazil, the COVID-19 pandemic found the universal and public Unified Health System (SUS) with problems accumulated over time, due, among other reasons, to low investments, and disparities in resource distribution. The preparedness and response of the healthcare system, involving the SUS and a private sector, was affected by large socioeconomic and healthcare access inequities. This work was aimed at offering an overview of COVID-19 inpatient mortality during the pandemic in Brazil, exploring factors associated with its variations and, specifically, differences across public, private (for-profit) and philanthropic (private non-profit) inpatient healthcare units, providers, and non-providers of services to the SUS. METHODS This cross-sectional study used public secondary data. The main data source was the SIVEP-Gripe, which comprises data on severe acute respiratory illness records prospectively collected. We also employed the National Record of Health Establishments, the SUS' Hospitalization Information System and municipalities' data from IBGE. We considered adult COVID-19 hospitalizations registered in SIVEP-Gripe from February 2020 to December 2022 in inpatient healthcare units with a minimum of 100 cases in the period. Data analyses explored the occurrence of inpatient mortality, employing general linear mixed models to identify the effects of patients', health care processes', healthcare units' and municipalities' characteristics on it. RESULTS About 70% of the COVID-19 hospitalizations in Brazil were covered by the SUS, which attended the more vulnerable population groups and had worse inpatient mortality. In general, non-SUS private and philanthropic hospitals, mostly reimbursed by healthcare insurance plans accessible for more privileged socioeconomic classes, presented the best outcomes. Southern Brazil had the best performance among the macro-regions. Black and indigenous individuals, residents of lower HDI municipalities, and those hospitalized out of their residence city presented higher odds of inpatient mortality. Moreover, adjusted inpatient mortality rates were higher in the pandemic peak moments and were significantly reduced after COVID-19 vaccination reaching a reasonable coverage, from July 2021. CONCLUSIONS COVID-19 exposed socioeconomic and healthcare inequalities and the importance and weaknesses of SUS in Brazil. This work indicates the need to revert the disinvestment in the universal public system, a fundamental policy for reduction of inequities in the country.
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Affiliation(s)
- Margareth Crisóstomo Portela
- Department of Health Administration and Planning, Sergio Arouca National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil.
| | - Mônica Martins
- Department of Health Administration and Planning, Sergio Arouca National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil
| | - Sheyla Maria Lemos Lima
- Department of Health Administration and Planning, Sergio Arouca National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil
| | - Carla Lourenço Tavares de Andrade
- Department of Health Administration and Planning, Sergio Arouca National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil
| | - Claudia Cristina de Aguiar Pereira
- Department of Health Administration and Planning, Sergio Arouca National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil
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Oseran AS, Song Y, Xu J, Dahabreh IJ, Wadhera RK, de Lemos JA, Das SR, Sun T, Yeh RW, Kazi DS. Long term risk of death and readmission after hospital admission with covid-19 among older adults: retrospective cohort study. BMJ 2023; 382:e076222. [PMID: 37558240 PMCID: PMC10475839 DOI: 10.1136/bmj-2023-076222] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/07/2023] [Indexed: 08/11/2023]
Abstract
OBJECTIVES To characterize the long term risk of death and hospital readmission after an index admission with covid-19 among Medicare fee-for-service beneficiaries, and to compare these outcomes with historical control patients admitted to hospital with influenza. DESIGN Retrospective cohort study. SETTING United States. PARTICIPANTS 883 394 Medicare fee-for-service beneficiaries age ≥65 years discharged alive after an index hospital admission with covid-19 between 1 March 2020 and 31 August 2022, compared with 56 409 historical controls discharged alive after a hospital admission with influenza between 1 March 2018 and 31 August 2019. Weighting methods were used to account for differences in observed characteristics. MAIN OUTCOME MEASURES All cause death within 180 days of discharge. Secondary outcomes included first all cause readmission and a composite of death or readmission within 180 days. RESULTS The covid-19 cohort compared with the influenza cohort was younger (77.9 v 78.9 years, standardized mean difference -0.12) and had a lower proportion of women (51.7% v 57.3%, -0.11). Both groups had a similar proportion of black beneficiaries (10.3% v 8.1%, 0.07) and beneficiaries with dual Medicaid-Medicare eligibility status (20.1% v 19.2%; 0.02). The covid-19 cohort had a lower comorbidity burden, including atrial fibrillation (24.3% v 29.5%, -0.12), heart failure (43.4% v 49.9%, -0.13), and chronic obstructive pulmonary disease (39.2% v 52.9%, -0.27). After weighting, the covid-19 cohort had a higher risk (ie, cumulative incidence) of all cause death at 30 days (10.9% v 3.9%; standardized risk difference 7.0%, 95% confidence interval 6.8% to 7.2%), 90 days (15.5% v 7.1%; 8.4%, 8.2% to 8.7%), and 180 days (19.1% v 10.5%; 8.6%, 8.3% to 8.9%) compared with the influenza cohort. The covid-19 cohort also experienced a higher risk of hospital readmission at 30 days (16.0% v 11.2%; 4.9%, 4.6% to 5.1%) and 90 days (24.1% v 21.3%; 2.8%, 2.5% to 3.2%) but a similar risk at 180 days (30.6% v 30.6%;-0.1%, -0.5% to 0.3%). Over the study period, the 30 day risk of death for patients discharged after a covid-19 admission decreased from 17.9% to 7.2%. CONCLUSIONS Medicare beneficiaries who were discharged alive after a covid-19 hospital admission had a higher post-discharge risk of death compared with historical influenza controls; this difference, however, was concentrated in the early post-discharge period. The risk of death for patients discharged after a covid-19 related hospital admission substantially declined over the course of the pandemic.
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Affiliation(s)
- Andrew S Oseran
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Division of Cardiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Yang Song
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Jiaman Xu
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Issa J Dahabreh
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- CAUSALab, Department of Epidemiology, and Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Rishi K Wadhera
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Division of Cardiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - James A de Lemos
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Sandeep R Das
- Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Tianyu Sun
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Robert W Yeh
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Division of Cardiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
| | - Dhruv S Kazi
- Richard A. and Susan F. Smith Center for Outcomes Research, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Division of Cardiology, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, USA
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7
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Hayashi K, Nishiura H. Time-dependent risk of COVID-19 death with overwhelmed health-care capacity in Japan, 2020-2022. BMC Infect Dis 2022; 22:933. [PMID: 36510193 PMCID: PMC9744068 DOI: 10.1186/s12879-022-07929-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND It has been descriptively argued that the case fatality risk (CFR) of coronavirus disease (COVID-19) is elevated when medical services are overwhelmed. The relationship between CFR and pressure on health-care services should thus be epidemiologically explored to account for potential epidemiological biases. The purpose of the present study was to estimate the age-dependent CFR in Tokyo and Osaka over time, investigating the impact of caseload demand on the risk of death. METHODS We estimated the time-dependent CFR, accounting for time delay from diagnosis to death. To this end, we first determined the time distribution from diagnosis to death, allowing variations in the delay over time. We then assessed the age-dependent CFR in Tokyo and Osaka. In Osaka, the risk of intensive care unit (ICU) admission was also estimated. RESULTS The CFR was highest among individuals aged 80 years and older and during the first epidemic wave from February to June 2020, estimated as 25.4% (95% confidence interval [CI] 21.1 to 29.6) and 27.9% (95% CI 20.6 to 36.1) in Tokyo and Osaka, respectively. During the fourth wave of infection (caused by the Alpha variant) in Osaka the CFR among the 70s and ≥ 80s age groups was, respectively, 2.3 and 1.5 times greater than in Tokyo. Conversely, despite the surge in hospitalizations, the risk of ICU admission among those aged 80 and older in Osaka decreased. Such time-dependent variation in the CFR was not seen among younger patients < 70 years old. With the Omicron variant, the CFR among the 80s and older in Tokyo and Osaka was 3.2% (95% CI 3.0 to 3.5) and 2.9% (95% CI 2.7 to 3.1), respectively. CONCLUSION We found that without substantial control, the CFR can increase when a surge in cases occurs with an identifiable elevation in risk-especially among older people. Because active treatment options including admission to ICU cannot be offered to the elderly with an overwhelmed medical service, the CFR value can potentially double compared with that in other areas of health care under less pressure.
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Affiliation(s)
- Katsuma Hayashi
- grid.258799.80000 0004 0372 2033Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo-ku, Kyoto, 606-8501 Japan
| | - Hiroshi Nishiura
- grid.258799.80000 0004 0372 2033Graduate School of Medicine, Kyoto University, Yoshidakonoecho, Sakyo-ku, Kyoto, 606-8501 Japan
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8
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Pagnucci N, Ottonello G, Capponi D, Catania G, Zanini M, Aleo G, Timmins F, Sasso L, Bagnasco A. Predictors of events of violence or aggression against nurses in the workplace: A scoping review. J Nurs Manag 2022; 30:1724-1749. [PMID: 35420236 PMCID: PMC9796891 DOI: 10.1111/jonm.13635] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 03/27/2022] [Accepted: 04/12/2022] [Indexed: 02/03/2023]
Abstract
AIM To identify predictors and consequences of violence or aggression events against nurses and nursing students in different work contexts. BACKGROUND Workplace violence against nurses and nursing students is a very common and widespread phenomenon. Actions to manage or prevent violent events could be implemented knowing the risk factors and consequences. However, there is a lack of systematic reviews that summarize knowledge on the predictors and consequences of workplace violence. EVALUATION A scoping review was conducted using electronic databases including APA PsycInfo, CINAHL, Cochrane, Ovid Medline, PubMed and Scopus. KEY ISSUES After full text analysis, 87 papers were included in the current scoping review. Risk factors of horizontal violence were grouped into 'personal' and 'Environmental and organizational', and for violence perpetrated by patients into 'personal', 'Environmental and organizational' and 'Characteristics of the perpetrators'. CONCLUSIONS The results of this scoping review uncover problems that often remain unaddressed, especially where these episodes are very frequent. Workplace violence prevention and management programmes are essential to counter it. IMPLICATIONS FOR NURSING MANAGEMENT The predictors and the consequents identified constitute the body of knowledge necessary for nurse managers to develop and implement policy and system actions to effectively manage or prevent violent events.
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Affiliation(s)
| | | | | | | | - Milko Zanini
- Department of Health SciencesUniversity of GenoaGenoa
| | - Giuseppe Aleo
- Department of Health SciencesUniversity of GenoaGenoa
| | - Fiona Timmins
- School of Nursing, Midwifery & Health SystemsUniversity College DublinDublinIreland
| | - Loredana Sasso
- School of Nursing, Midwifery & Health SystemsUniversity College DublinDublinIreland
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