Predicting COVID-19 Cases in US Long-Term Care Facilities:An Empirical Study Using Epidemiological Data
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Bester Preis: Fr. 41.91 (€ 42.95)¹ (vom 01.07.2022)1
Predicting COVID-19 Cases in US Long-Term Care Facilities : An Empirical Study Using Epidemiological Data (2020)
~EN PB NW
ISBN: 9783346292032 bzw. 3346292037, vermutlich in Englisch, GRIN Verlag, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
nach der Bestellung gedruckt Neuware -Master's Thesis from the year 2020 in the subject Health - Nursing Science - Nursing Management, grade: 1.0, language: English, abstract: The focus of this paper was to identify factors that increase the probability of COVID-19 cases in nursing homes and to provide an exemplary concept for the application of the findings using machine learning algorithms to allow future research to derive appropriate countermeasures in practice. The findings are based on 13,069 US nursing homes, and the results are mostly consistent with most recent studies around this topic. Thus, this study provides not only additional evidence for previously studied factors based on a larger population of nursing homes with a holistic approach but also complements these with features not yet examined, such as most importantly the competitive environment of a nursing home. The findings show evidence of a relationship between COVID-19 infections and fatalities and (1) the size of a nursing home, (2) a facility's age, (3) whether a nursing home is for-profit, (4) whether a nursing home is urban or rural, (5) the number of federal deficiencies, (6) the total amount of fines, (7) the concentration of residents with Medicaid, (8) the share of residents from a racial or ethnic minority, (9) the excess of beds in the respective county of a nursing home, (10) the number of infections per 100,000 people in a county, and (11) the number of deaths per 100,000 people in a county, (12) the occupancy rate, (13) the overall CMS facility rating, (14) the total reported RN staffing levels, (15) the total reported nurse staffing levels and (16) the Herfindahl Index. 64 pp. Englisch, Books.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
nach der Bestellung gedruckt Neuware -Master's Thesis from the year 2020 in the subject Health - Nursing Science - Nursing Management, grade: 1.0, language: English, abstract: The focus of this paper was to identify factors that increase the probability of COVID-19 cases in nursing homes and to provide an exemplary concept for the application of the findings using machine learning algorithms to allow future research to derive appropriate countermeasures in practice. The findings are based on 13,069 US nursing homes, and the results are mostly consistent with most recent studies around this topic. Thus, this study provides not only additional evidence for previously studied factors based on a larger population of nursing homes with a holistic approach but also complements these with features not yet examined, such as most importantly the competitive environment of a nursing home. The findings show evidence of a relationship between COVID-19 infections and fatalities and (1) the size of a nursing home, (2) a facility's age, (3) whether a nursing home is for-profit, (4) whether a nursing home is urban or rural, (5) the number of federal deficiencies, (6) the total amount of fines, (7) the concentration of residents with Medicaid, (8) the share of residents from a racial or ethnic minority, (9) the excess of beds in the respective county of a nursing home, (10) the number of infections per 100,000 people in a county, and (11) the number of deaths per 100,000 people in a county, (12) the occupancy rate, (13) the overall CMS facility rating, (14) the total reported RN staffing levels, (15) the total reported nurse staffing levels and (16) the Herfindahl Index. 64 pp. Englisch, Books.
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Predicting COVID-19 Cases in US Long-Term Care Facilities (2020)
DE PB NW RP
ISBN: 9783346292032 bzw. 3346292037, in Deutsch, 64 Seiten, GRIN Verlag, Taschenbuch, neu, Nachdruck.
Lieferung aus: Deutschland, Versandkosten nach: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, Moluna GmbH, [5901482].
Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Master s Thesis from the year 2020 in the subject Health - Nursing Science - Nursing Management, grade: 1.0, language: English, abstract: The focus of this p, 2020, Kartoniert / Broschiert, Neuware, Softcover, 107g, 64, Banküberweisung, PayPal.
Von Händler/Antiquariat, Moluna GmbH, [5901482].
Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Master s Thesis from the year 2020 in the subject Health - Nursing Science - Nursing Management, grade: 1.0, language: English, abstract: The focus of this p, 2020, Kartoniert / Broschiert, Neuware, Softcover, 107g, 64, Banküberweisung, PayPal.
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Predicting COVID-19 Cases in US Long-Term Care Facilities:An Empirical Study Using Epidemiological Data (2020)
~EN PB NW RP
ISBN: 9783346292032 bzw. 3346292037, vermutlich in Englisch, GRIN Verlag, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, Ria Christie Collections [59718070], Uxbridge, United Kingdom.
PRINT ON DEMAND Book; New; Fast Shipping from the UK. Books.
PRINT ON DEMAND Book; New; Fast Shipping from the UK. Books.
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Predicting COVID-19 Cases in US Long-Term Care Facilities
~DE PB NW FE
ISBN: 3346292037 bzw. 9783346292032, vermutlich in Deutsch, GRIN Verlag, Taschenbuch, neu, Erstausgabe.
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Predicting COVID-19 Cases in US Long-Term Care Facilities: An Empirical Study Using Epidemiological Data (2020)
~EN PB NW
ISBN: 9783346292032 bzw. 3346292037, vermutlich in Englisch, Grin Verlag, Taschenbuch, neu.
Von Händler/Antiquariat, Welcome Back Books [64434632], Toledo, OH, U.S.A.
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Clean and crisp and new! Books.
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