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Miron VD, Săndulescu O, Streinu-Cercel A, Florea D, Paraschiv S, Bănică L, Vlaicu O, Oțelea D, Bilașco A, Pițigoi D, Streinu-Cercel A, Drăgănescu AC. Age, comorbidity burden and late presentation are significant predictors of hospitalization length and acute respiratory failure in patients with influenza. Sci Rep 2024; 14:15563. [PMID: 38971866 PMCID: PMC11227496 DOI: 10.1038/s41598-024-66550-8] [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: 12/16/2023] [Accepted: 07/02/2024] [Indexed: 07/08/2024] Open
Abstract
Influenza viruses are responsible for a high number of infections and hospitalizations every year. In this study, we aimed to identify clinical and host-specific factors that influence the duration of hospitalization and the progression to acute respiratory failure (ARF) in influenza. We performed an analysis of data from a prospective active influenza surveillance study that was conducted over five seasons (2018/19 to 2022/23). A total of 1402 patients with influenza were included in the analysis, the majority of which (64.5%) were children (under 18 years), and 9.1% were elderly. At least one chronic condition was present in 29.2% of patients, and 9.9% of patients developed ARF. The median hospital stay was 4 days (IQR: 3, 6 days). The most important predictors of prolonged hospital stay and development of ARF were extremes of age (infants and elderly), presence of chronic diseases, particularly the cumulus of at least 3 chronic diseases, and late presentation to hospital. Among the chronic diseases, chronic obstructive pulmonary disease, cardiovascular disease, cancer, diabetes, obesity, and chronic kidney disease were strongly associated with a longer duration of hospitalization and occurrence of ARF. In this context, interventions aimed at chronic disease management, promoting influenza vaccination, and improving awareness and access to health services may contribute to reducing the impact of influenza not only in Romania but globally. In addition, continued monitoring of the circulation of influenza viruses is essential to limit their spread among vulnerable populations.
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Affiliation(s)
- Victor Daniel Miron
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
| | - Oana Săndulescu
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania.
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania.
| | - Anca Streinu-Cercel
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
| | - Dragoș Florea
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
| | - Simona Paraschiv
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
| | - Leontina Bănică
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
| | - Ovidiu Vlaicu
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
| | - Dan Oțelea
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
| | - Anuța Bilașco
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
| | - Daniela Pițigoi
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
| | - Adrian Streinu-Cercel
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
| | - Anca Cristina Drăgănescu
- Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
- National Institute for Infectious Diseases "Prof. Dr. Matei Balș", Bucharest, Romania
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Kim SJ, Medina M, Zhong L, Chang J. Factors Associated With In-Hospital Death Among Pneumonia Patients in US Hospitals From 2016~2019. Int J Health Policy Manag 2023; 12:7390. [PMID: 37579357 PMCID: PMC10702393 DOI: 10.34172/ijhpm.2023.7390] [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: 05/13/2022] [Accepted: 07/09/2023] [Indexed: 08/16/2023] Open
Abstract
BACKGROUND Pneumonia is one of the leading causes of hospital admission in the United States with a global health burden of about 6.8 million hospitalizations and 1.1 million deaths in patients over 65 years old in 2015. This study aimed to identify possible patient and hospital-related risk factors for in-hospital pneumonia death across US hospitals. METHODS The National Inpatient Sample (NIS) was used to identify nationwide pneumonia patients (n=374 766, weighted n=1 873 828) from 2016 to 2019. We examined the characteristics of the study sample and their association with in-hospital death. Multivariate survey logistic regression models were used to identify risk factors. RESULTS During the study periods, in-hospital death rates continuously decreased (2.45% in 2016 to 2.19% in 2019). Descriptive statistics showed that patient and hospital factors had varied in-hospital death rates. Survey logistic regression results suggested that male, very low income, non-Medicare, government hospitals, rural hospitals, and specific hospital regions were associated with higher in-hospital death rates than their reference groups. CONCLUSION Socioeconomic factors, including income and insurance, are associated with pneumonia mortality. Census region, hospital ownership, and rural location are also related to in-hospital mortality. Such findings in underserved, impoverished, and rural areas to identify possible health disparities.
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Affiliation(s)
- Sun Jung Kim
- Department of Health Administration and Management, College of Medical Science, Soonchunhyang University, Asan, Republic of Korea
- Center for Healthcare Management Science, Soonchunhyang University, Asan, Republic of Korea
- Department of Software Convergence, Soonchunhyang University, Asan, Republic of Korea
| | - Mar Medina
- School of Pharmacy, University of Texas at El Paso, El Paso, TX, USA
| | - Lixian Zhong
- Department of Pharmaceutical Sciences, Irma Lerma Rangel School of Pharmacy, Texas A&M University, College Station, TX, USA
| | - Jongwha Chang
- Department of Pharmaceutical Sciences, Irma Lerma Rangel School of Pharmacy, Texas A&M University, College Station, TX, USA
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O’Neill ET, Bosco E, Persico E, Silva JB, Riester MR, Moyo P, van Aalst R, Loiacono MM, Chit A, Gravenstein S, Zullo AR. Correlation of long-term care facility vaccination practices between seasons and resident types. BMC Geriatr 2022; 22:835. [PMID: 36333667 PMCID: PMC9635204 DOI: 10.1186/s12877-022-03540-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 10/18/2022] [Indexed: 11/06/2022] Open
Abstract
Background Influenza vaccination varies widely across long-term care facilities (LTCFs) due to staff behaviors, LTCF practices, and patient factors. It is unclear how seasonal LTCF vaccination varies between cohabitating but distinct short-stay and long-stay residents. Thus, we assessed the correlation of LTCF vaccination between these populations and across seasons. Methods The study design is a national retrospective cohort using Medicare and Minimum Data Set (MDS) data. Participants include U.S. LTCFs. Short-stay and long-stay Medicare-enrolled residents age ≥ 65 in U.S. LTCFs from a source population of residents during October 1st-March 31st in 2013–2014 (3,042,881 residents; 15,683 LTCFs) and 2014–2015 (3,143,174, residents; 15,667 LTCFs). MDS-assessed influenza vaccination was the outcome. Pearson correlation coefficients were estimated to assess seasonal correlations between short-stay and long-stay resident vaccination within LTCFs. Results The median proportion of short-stay residents vaccinated across LTCFs was 70.4% (IQR, 50.0–82.7%) in 2013–2014 and 69.6% (IQR, 50.0–81.6%) in 2014–2015. The median proportion of long-stay residents vaccinated across LTCFs was 85.5% (IQR, 78.0–90.9%) in 2013–2014 and 84.6% (IQR, 76.6–90.3%) in 2014–2015. Within LTCFs, there was a moderate correlation between short-stay and long-stay vaccination in 2013–2014 (r = 0.50, 95%CI: 0.49–0.51) and 2014–2015 (r = 0.53, 95%CI: 0.51–0.54). Across seasons, there was a moderate correlation for LTCFs with short-stay residents (r = 0.54, 95%CI: 0.53–0.55) and a strong correlation for those with long-stay residents (r = 0.68, 95%CI: 0.67–0.69). Conclusions In LTCFs with inconsistent influenza vaccination across seasons or between populations, targeted vaccination protocols for all residents, regardless of stay type, may improve successful vaccination in this vulnerable patient population. Supplementary Information The online version contains supplementary material available at 10.1186/s12877-022-03540-3.
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Affiliation(s)
- Emily T. O’Neill
- grid.40263.330000 0004 1936 9094Department of Health Services, Policy, and Practice, Brown University School of Public Health, 121 South Main Street, Box G-S121-3, Providence, RI 02912 USA ,grid.40263.330000 0004 1936 9094Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI USA
| | - Elliott Bosco
- grid.40263.330000 0004 1936 9094Department of Health Services, Policy, and Practice, Brown University School of Public Health, 121 South Main Street, Box G-S121-3, Providence, RI 02912 USA ,grid.40263.330000 0004 1936 9094Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI USA
| | - Erin Persico
- grid.20431.340000 0004 0416 2242University of Rhode Island College of Pharmacy, Kingston, RI USA
| | - Joe B. Silva
- grid.40263.330000 0004 1936 9094Department of Health Services, Policy, and Practice, Brown University School of Public Health, 121 South Main Street, Box G-S121-3, Providence, RI 02912 USA ,grid.40263.330000 0004 1936 9094Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI USA
| | - Melissa R. Riester
- grid.40263.330000 0004 1936 9094Department of Health Services, Policy, and Practice, Brown University School of Public Health, 121 South Main Street, Box G-S121-3, Providence, RI 02912 USA ,grid.40263.330000 0004 1936 9094Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI USA
| | - Patience Moyo
- grid.40263.330000 0004 1936 9094Department of Health Services, Policy, and Practice, Brown University School of Public Health, 121 South Main Street, Box G-S121-3, Providence, RI 02912 USA ,grid.40263.330000 0004 1936 9094Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI USA
| | - Robertus van Aalst
- grid.417555.70000 0000 8814 392XSanofi, Swiftwater, PA USA ,grid.4494.d0000 0000 9558 4598Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Ayman Chit
- grid.417555.70000 0000 8814 392XSanofi, Swiftwater, PA USA ,grid.17063.330000 0001 2157 2938Leslie Dan Faculty of Pharmacy, University of Toronto, Toronto, ON Canada
| | - Stefan Gravenstein
- grid.40263.330000 0004 1936 9094Department of Health Services, Policy, and Practice, Brown University School of Public Health, 121 South Main Street, Box G-S121-3, Providence, RI 02912 USA ,grid.40263.330000 0004 1936 9094Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI USA ,grid.413904.b0000 0004 0420 4094Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI USA ,grid.40263.330000 0004 1936 9094Department of Medicine, Warren Alpert Medical School, Brown University, Providence, RI USA
| | - Andrew R. Zullo
- grid.40263.330000 0004 1936 9094Department of Health Services, Policy, and Practice, Brown University School of Public Health, 121 South Main Street, Box G-S121-3, Providence, RI 02912 USA ,grid.40263.330000 0004 1936 9094Center for Gerontology and Healthcare Research, Brown University School of Public Health, Providence, RI USA ,grid.413904.b0000 0004 0420 4094Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI USA ,grid.40263.330000 0004 1936 9094Department of Epidemiology, Brown University School of Public Health, Providence, RI USA
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Lapi F, Domnich A, Marconi E, Rossi A, Cricelli C. Adjuvanted versus non-adjuvanted standard-dose influenza vaccines in preventing all-cause hospitalizations in the elderly: a cohort study with nested case-control analyses over 18 influenza seasons. Expert Rev Vaccines 2022; 21:1647-1653. [PMID: 35984048 DOI: 10.1080/14760584.2022.2115362] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
BACKGROUND The higher effectiveness of adjuvanted trivalent influenza vaccine (aTIV) versus non-adjuvanted (na) formulations in preventing all-cause hospitalization has been demonstrated for a single influenza season and in institutionalized elderly only. This study evaluated the relative vaccine effectiveness for aTIV vs. non-adjuvanted trivalent (naTIV) and/or quadrivalent (naQIV) influenza vaccines in preventing all-cause hospitalizations across 18 influenza seasons in primary care. RESEARCH DESIGN AND METHODS Using Health Search Database, a nested case-control analysis was conducted in a cohort of older adults being vaccinated with aTIV or naTIV/naQIV. Conditional logistic regression was adopted to estimate the odds ratio (OR) of all-cause hospitalizations occurred during the epidemic period. RESULTS Of 58,252 patients vaccinated with aTIV and naTIV/naQIV for the first time, 2,504 cases of all-cause hospitalization (3.46 per 1,000 person-weeks) during the 18 influenza seasons were identified. Compared with naTIV/naQIV, aTIV was associated with a 12% reduced the odds of all-cause hospitalizations (OR 0.88; 95% CI: 0.80-0.98). CONCLUSIONS In an 18-season cohort of older adults, aTIV reduced the risk of all-cause hospitalizations when compared with naTIV/naQIV. Our findings confirm additional benefits for adjuvanted influenza vaccines in older adults.
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Affiliation(s)
- Francesco Lapi
- Health Search, Italian College of General Practitioners and Primary Care, Florence, Italy
| | - Alexander Domnich
- Hygiene Unit, San Martino Policlinico Hospital - IRCCS for Oncology and Neurosciences, Genoa, Italy
| | - Ettore Marconi
- Health Search, Italian College of General Practitioners and Primary Care, Florence, Italy
| | - Alessandro Rossi
- Italian College of General Practitioners and Primary Care, Florence, Italy
| | - Claudio Cricelli
- Italian College of General Practitioners and Primary Care, Florence, Italy
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Joean O, Welte T. Vaccination and modern management of chronic obstructive pulmonary disease - a narrative review. Expert Rev Respir Med 2022; 16:605-614. [PMID: 35713962 DOI: 10.1080/17476348.2022.2092099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Chronic obstructive pulmonary disease (COPD) carries a tremendous societal and individual burden, posing significant challenges for public health systems worldwide due to its high morbidity and mortality. Due to aging and multimorbidity but also in the wake of important progress in deciphering the heterogeneous disease endotypes, an individualized approach to the prevention and management of COPD is necessary. AREAS COVERED This article tackles relevant immunization strategies that are available or still under development with a focus on the latest evidence but also controversies around different regional immunization approaches. Further, we present the crossover between chronic lung inflammation and lung microbiome disturbance as well as its role in delineating COPD endotypes. Moreover, the article attempts to underline endotype-specific treatment approaches. Lastly, we highlight non-pharmacologic prevention and management programs in view of the challenges and opportunities of the COVID-19 era. EXPERT OPINION Despite the remaining challenges, personalized medicine has the potential to offer tailored approaches to prevention and therapy and promises to improve the care of patients living with COPD.
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Affiliation(s)
- Oana Joean
- Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany
| | - Tobias Welte
- Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany.,Biomedical Research in Endstage and Obstructive Lung Disease, Member of the German Center for Lung Research, Hannover, Germany
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6
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Moyo P, Bosco E, Bardenheier BH, Rivera-Hernandez M, van Aalst R, Chit A, Gravenstein S, Zullo AR. Variation in influenza vaccine assessment, receipt, and refusal by the concentration of Medicare Advantage enrollees in U.S. nursing homes. Vaccine 2022; 40:1031-1037. [PMID: 35033387 PMCID: PMC8917469 DOI: 10.1016/j.vaccine.2021.12.069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 12/22/2021] [Accepted: 12/30/2021] [Indexed: 11/24/2022]
Abstract
BACKGROUND More older adults enrolled in Medicare Advantage (MA) are entering nursing homes (NHs), and MA concentration could affect vaccination rates through shifts in resident characteristics and/or payer-related influences on preventive services use. We investigated whether rates of influenza vaccination and refusal differ across NHs with varying concentrations of MA-enrolled residents. METHODS We analyzed 2014-2015 Medicare enrollment data and Minimum Data Set clinical assessments linked to NH-level characteristics, star ratings, and county-level MA penetration rates. The independent variable was the percentage of residents enrolled in MA at admission and categorized into three equally-sized groups. We examined three NH-level outcomes including the percentages of residents assessed and appropriately considered for influenza vaccination, received influenza vaccination, and refused influenza vaccination. RESULTS There were 936,513 long-stay residents in 12,384 NHs. Categories for the prevalence of MA enrollment in NHs were low (0% to 3.3%; n = 4131 NHs), moderate (3.4% to 18.6%; n = 4127 NHs) and high (>18.6%; n = 4126 NHs). Overall, 81.3% of long-stay residents received influenza vaccination and 14.3% refused the vaccine when offered. Adjusting for covariates, influenza vaccination rates among long-stay residents were higher in NHs with moderate (1.70 percentage points [pp], 95% confidence limits [CL]: 1.15 pp, 2.24 pp), or high (3.05 pp, 95% CL: 2.45 pp, 3.66 pp) MA versus the lowest prevalence of MA. Influenza vaccine refusal was lower in NHs with moderate (-3.10 pp, 95% CL: -3.53 pp, -2.68 pp), or high (-4.63 pp, 95% CL: -5.11 pp, -4.15 pp) MA compared with NHs with the lowest prevalence of MA. CONCLUSION A higher concentration of long-stay NH residents enrolled in MA was associated with greater influenza vaccine receipt and lower vaccine refusal. As MA becomes a larger share of the Medicare program, and more MA beneficiaries enter NHs, decisionmakers need to consider how managed care can be leveraged to improve the delivery of preventive services like influenza vaccinations in NH settings.
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Affiliation(s)
- Patience Moyo
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, USA; Center for Gerontology and Health Care Research, School of Public Health, Brown University School of Public Health, Providence, RI, USA.
| | - Elliott Bosco
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, USA; Center for Gerontology and Health Care Research, School of Public Health, Brown University School of Public Health, Providence, RI, USA
| | - Barbara H Bardenheier
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, USA; Center for Gerontology and Health Care Research, School of Public Health, Brown University School of Public Health, Providence, RI, USA; Leslie Dan School of Pharmacy, University of Toronto, Ontario, Canada
| | - Maricruz Rivera-Hernandez
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, USA; Center for Gerontology and Health Care Research, School of Public Health, Brown University School of Public Health, Providence, RI, USA
| | - Robertus van Aalst
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, USA; Department of Modelling, Epidemiology, and Data Science, Sanofi Pasteur, Lyon, France; Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Ayman Chit
- Sanofi Pasteur, Swiftwater, PA, USA; Leslie Dan School of Pharmacy, University of Toronto, Ontario, Canada
| | - Stefan Gravenstein
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, USA; Center for Gerontology and Health Care Research, School of Public Health, Brown University School of Public Health, Providence, RI, USA; Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI, USA; Department of Medicine, Alpert Medical School of Brown University, Providence, RI, USA
| | - Andrew R Zullo
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, RI, USA; Center for Gerontology and Health Care Research, School of Public Health, Brown University School of Public Health, Providence, RI, USA; Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, RI, USA; Department of Epidemiology, Brown University School of Public Health, Providence, RI, USA
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7
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Bosco E, van Aalst R, McConeghy KW, Silva J, Moyo P, Eliot MN, Chit A, Gravenstein S, Zullo AR. Estimated Cardiorespiratory Hospitalizations Attributable to Influenza and Respiratory Syncytial Virus Among Long-term Care Facility Residents. JAMA Netw Open 2021; 4:e2111806. [PMID: 34106266 PMCID: PMC8190624 DOI: 10.1001/jamanetworkopen.2021.11806] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
IMPORTANCE Older adults residing in long-term care facilities (LTCFs) are at a high risk of being infected with respiratory viruses, such as influenza and respiratory syncytial virus (RSV). Although these infections commonly have many cardiorespiratory sequelae, the national burden of influenza- and RSV-attributable cardiorespiratory events remains unknown for the multimorbid and vulnerable LTCF population. OBJECTIVE To estimate the incidence of cardiorespiratory hospitalizations that were attributable to influenza and RSV among LTCF residents and to quantify the economic burden of these hospitalizations on the US health care system by estimating their associated cost and length of stay. DESIGN, SETTING, AND PARTICIPANTS This retrospective cohort study used national Medicare Provider Analysis and Review inpatient claims and Minimum Data Set clinical assessments for 6 respiratory seasons (2011-2017). Long-stay residents of LTCFs were identified as those living in the facility for at least 100 days (index date), aged 65 years or older, and with 6 months of continuous enrollment in Medicare Part A were included. Follow-up occurred from the resident's index date until the first hospitalization, discharge from the LTCF, disenrollment from Medicare, death, or the end of the study. Residents could re-enter the sample; thus, long-stay episodes of care were identified. Data analysis was performed between January 1 and September 30, 2020. EXPOSURES Seasonal circulating pandemic 2009 influenza A(H1N1), human influenza A(H3N2), influenza B, and RSV. MAIN OUTCOMES AND MEASURES Cardiorespiratory hospitalizations (eg, asthma exacerbation, heart failure) were identified using primary diagnosis codes. Influenza- and RSV-attributable cardiorespiratory events were estimated using a negative binomial regression model adjusted for weekly circulating influenza and RSV testing data. Length of stay and costs of influenza- and RSV-attributable events were then estimated. RESULTS The study population comprised 2 909 106 LTCF residents with 3 138 962 long-stay episodes and 5 079 872 person-years of follow-up. Overall, 10 939 (95% CI, 9413-12 464) influenza- and RSV-attributable cardiorespiratory events occurred, with an incidence of 215 (95% CI, 185-245) events per 100 000 person-years. The cost of influenza- and RSV-attributable cardiorespiratory events was $91 055 393 (95% CI, $77 885 316-$104 225 470), and the length of stay was 56 858 (95% CI, 48 757-64 968) days. CONCLUSIONS AND RELEVANCE This study found that many cardiorespiratory hospitalizations among LTCF residents in the US were attributable to seasonal influenza and RSV. To minimize the burden these events place on the health care system and residents of LTCFs and to prevent virus transmission, additional preventive measures should be implemented.
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Affiliation(s)
- Elliott Bosco
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, School of Public Health, Brown University School of Public Health, Providence, Rhode Island
| | - Robertus van Aalst
- Modeling, Epidemiology, and Data Science, Sanofi Pasteur, Swiftwater, Pennsylvania
- Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Kevin W. McConeghy
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center of Innovation in Long-term Services and Supports, Providence Veterans Affairs Medical Center, Providence, Rhode Island
| | - Joe Silva
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, School of Public Health, Brown University School of Public Health, Providence, Rhode Island
| | - Patience Moyo
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, School of Public Health, Brown University School of Public Health, Providence, Rhode Island
| | - Melissa N. Eliot
- Center for Gerontology and Healthcare Research, School of Public Health, Brown University School of Public Health, Providence, Rhode Island
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island
| | - Ayman Chit
- Modeling, Epidemiology, and Data Science, Sanofi Pasteur, Swiftwater, Pennsylvania
- Leslie Dan School of Pharmacy, University of Toronto, Toronto, Ontario, Canada
| | - Stefan Gravenstein
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, School of Public Health, Brown University School of Public Health, Providence, Rhode Island
- Center of Innovation in Long-term Services and Supports, Providence Veterans Affairs Medical Center, Providence, Rhode Island
- Department of Medicine, Warren Alpert Medical School, Brown University, Providence, Rhode Island
| | - Andrew R. Zullo
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
- Center for Gerontology and Healthcare Research, School of Public Health, Brown University School of Public Health, Providence, Rhode Island
- Center of Innovation in Long-term Services and Supports, Providence Veterans Affairs Medical Center, Providence, Rhode Island
- Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island
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8
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Silva JBB, Bosco E, Riester MR, McConeghy KW, Moyo P, van Aalst R, Bardenheier BH, Gravenstein S, Baier R, Loiacono MM, Chit A, Zullo AR. Geographic variation in influenza vaccination among U.S. nursing home residents: A national study. J Am Geriatr Soc 2021; 69:2536-2547. [PMID: 34013979 PMCID: PMC8242857 DOI: 10.1111/jgs.17270] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 04/27/2021] [Accepted: 04/28/2021] [Indexed: 11/26/2022]
Abstract
Objectives Estimates of influenza vaccine use are not available at the county level for U.S. nursing home (NH) residents but are critically necessary to guide the implementation of quality improvement programs aimed at increasing vaccination. Furthermore, estimates that account for differences in resident characteristics between counties are unavailable. We estimated risk‐standardized vaccination rates (RSVRs) among short‐ and long‐stay NH residents by U.S. county and identified drivers of geographic variation. Methods We conducted a retrospective cohort study utilizing 100% of 2013–2015 fee‐for‐service Medicare claims, Minimum Data Set assessments, Certification and Survey Provider Enhanced Reports, and Long‐Term Care: Facts on Care in the U.S. We separately evaluated short‐stay (<100 days) and long‐stay (≥100 days) residents aged 65 and older across the 2013–2014 and 2014–2015 influenza seasons. We estimated RSVRs via hierarchical logistic regression adjusting for 32 resident‐level covariates. We then used multivariable linear regression models to assess associations between county‐level NHs predictors and RSVRs. Results The study cohort consisted of 2,817,217 residents in 14,658 NHs across 2798 counties. Short‐stay residents had lower RSVRs than long‐stay residents (2013–2014: median [interquartile range], 69.6% [62.8–74.5] vs 84.0% [80.8–86.4]), and there was wide variation within each population (range, 11.4–89.8 vs 49.1–92.6). Several modifiable facility‐level characteristics were associated with increased RSVRs, including higher registered nurse to total nurse ratio and higher total staffing for licensed practical nurses, speech‐language pathologists, and social workers. Characteristics associated with lower RSVRs included higher percentage of residents restrained, with a pressure ulcer, and NH‐level hospitalizations per resident‐year. Conclusions Substantial county‐level variation in influenza vaccine use exists among short‐ and long‐stay NH residents. Quality improvement interventions to improve vaccination rates can leverage these results to target NHs located in counties with lower risk‐standardized vaccine use.
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Affiliation(s)
- Joe B B Silva
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Elliott Bosco
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Melissa R Riester
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Kevin W McConeghy
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA.,Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, Rhode Island, USA
| | - Patience Moyo
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Robertus van Aalst
- Sanofi Pasteur, Swiftwater, Pennsylvania, USA.,Department of Health Sciences, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Barbara H Bardenheier
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Stefan Gravenstein
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA.,Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, Rhode Island, USA.,Department of Medicine, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Rosa Baier
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA
| | - Matthew M Loiacono
- Sanofi Pasteur, Swiftwater, Pennsylvania, USA.,Leslie Dan School of Pharmacy, University of Toronto, Toronto, Ontario, Canada
| | - Ayman Chit
- Sanofi Pasteur, Swiftwater, Pennsylvania, USA.,Leslie Dan School of Pharmacy, University of Toronto, Toronto, Ontario, Canada
| | - Andrew R Zullo
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island, USA.,Center of Innovation in Long-Term Services and Supports, Providence Veterans Affairs Medical Center, Providence, Rhode Island, USA
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9
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Prieto-Alhambra D, Balló E, Coma E, Mora N, Aragón M, Prats-Uribe A, Fina F, Benítez M, Guiriguet C, Fàbregas M, Medina-Peralta M, Duarte-Salles T. Filling the gaps in the characterization of the clinical management of COVID-19: 30-day hospital admission and fatality rates in a cohort of 118 150 cases diagnosed in outpatient settings in Spain. Int J Epidemiol 2021; 49:1930-1939. [PMID: 33118037 PMCID: PMC7665572 DOI: 10.1093/ije/dyaa190] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/03/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Currently, there is a missing link in the natural history of COVID-19, from first (usually milder) symptoms to hospitalization and/or death. To fill in this gap, we characterized COVID-19 patients at the time at which they were diagnosed in outpatient settings and estimated 30-day hospital admission and fatality rates. METHODS This was a population-based cohort study. Data were obtained from Information System for Research in Primary Care (SIDIAP)-a primary-care records database covering >6 million people (>80% of the population of Catalonia), linked to COVID-19 reverse transcriptase polymerase chain reaction (RT-PCR) tests and hospital emergency, inpatient and mortality registers. We included all patients in the database who were ≥15 years old and diagnosed with COVID-19 in outpatient settings between 15 March and 24 April 2020 (10 April for outcome studies). Baseline characteristics included socio-demographics, co-morbidity and previous drug use at the time of diagnosis, and polymerase chain reaction (PCR) testing and results. Study outcomes included 30-day hospitalization for COVID-19 and all-cause fatality. RESULTS We identified 118 150 and 95 467 COVID-19 patients for characterization and outcome studies, respectively. Most were women (58.7%) and young-to-middle-aged (e.g. 21.1% were 45-54 years old). Of the 44 575 who were tested with PCR, 32 723 (73.4%) tested positive. In the month after diagnosis, 14.8% (14.6-15.0) were hospitalized, with a greater proportion of men and older people, peaking at age 75-84 years. Thirty-day fatality was 3.5% (95% confidence interval: 3.4% to 3.6%), higher in men, increasing with age and highest in those residing in nursing homes [24.5% (23.4% to 25.6%)]. CONCLUSION COVID-19 infections were widespread in the community, including all age-sex strata. However, severe forms of the disease clustered in older men and nursing-home residents. Although initially managed in outpatient settings, 15% of cases required hospitalization and 4% died within a month of first symptoms. These data are instrumental for designing deconfinement strategies and will inform healthcare planning and hospital-bed allocation in current and future COVID-19 outbreaks.
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Affiliation(s)
- Daniel Prieto-Alhambra
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Centre for Statistics in Medicine, NDORMS, University of Oxford
| | - Elisabet Balló
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Sistemes d’Informació dels Serveis d’Atenció Primària (SISAP), Institut Català de la Salut (ICS), Barcelona, Spain
- Equip d’Atenció Primària de Salt, Institut Català de la Salut, Girona, Spain
| | - Ermengol Coma
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Sistemes d’Informació dels Serveis d’Atenció Primària (SISAP), Institut Català de la Salut (ICS), Barcelona, Spain
| | - Núria Mora
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Sistemes d’Informació dels Serveis d’Atenció Primària (SISAP), Institut Català de la Salut (ICS), Barcelona, Spain
| | - María Aragón
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
| | | | - Francesc Fina
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Sistemes d’Informació dels Serveis d’Atenció Primària (SISAP), Institut Català de la Salut (ICS), Barcelona, Spain
| | - Mència Benítez
- Sistemes d’Informació dels Serveis d’Atenció Primària (SISAP), Institut Català de la Salut (ICS), Barcelona, Spain
- Equip d’Atenció Primària Gòtic, Institut Català de la Salut, Barcelona, Spain
| | - Carolina Guiriguet
- Sistemes d’Informació dels Serveis d’Atenció Primària (SISAP), Institut Català de la Salut (ICS), Barcelona, Spain
- Equip d’Atenció Primària Gòtic, Institut Català de la Salut, Barcelona, Spain
| | - Mireia Fàbregas
- Sistemes d’Informació dels Serveis d’Atenció Primària (SISAP), Institut Català de la Salut (ICS), Barcelona, Spain
| | - Manuel Medina-Peralta
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
- Sistemes d’Informació dels Serveis d’Atenció Primària (SISAP), Institut Català de la Salut (ICS), Barcelona, Spain
| | - Talita Duarte-Salles
- Fundació Institut Universitari per a la Recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain
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