A new TOPSIS-based approach to evaluate the economic indicators in the healthcare system and the impact of biotechnology

Abstract Background Several vaccines are now clinically available under emergency use authorization in the United States and have demonstrated efficacy against symptomatic COVID-19. The impact of vaccines on asymptomatic SARS-CoV-2 infection is largely unknown. Methods We conducted a retrospective cohort study of consecutive, asymptomatic adult patients (n = 39,156) within a large United States healthcare system who underwent 48,333 pre-procedural SARS-CoV-2 molecular screening tests between December 17, 2020 and February 8, 2021. The primary exposure of interest was vaccination with at least one dose of an mRNA COVID-19 vaccine. The primary outcome was relative risk of a positive SARS-CoV-2 molecular test among those asymptomatic persons who had received at least one dose of vaccine, as compared to persons who had not received vaccine during the same time period. Relative risk was adjusted for age, sex, race/ethnicity, patient residence relative to the hospital (local vs. non-local), healthcare system regions, and repeated screenings among patients using mixed effects log-binomial regression. Results Positive molecular tests in asymptomatic individuals were reported in 42 (1.4%) of 3,006 tests performed on vaccinated patients and 1,436 (3.2%) of 45,327 tests performed on unvaccinated patients (RR=0.44 95% CI: 0.33-0.60; p<.0001). Compared to unvaccinated patients, the risk of asymptomatic SARS-CoV-2 infection was lower among those >10 days after 1 st dose (RR=0.21; 95% CI: 0.12-0.37; p<.0001) and >0 days after 2 nd dose (RR=0.20; 95% CI: 0.09-0.44; p<.0001) in the adjusted analysis. Conclusions COVID-19 vaccination with an mRNA-based vaccine showed a significant association with a reduced risk of asymptomatic SARS-CoV-2 infection as measured during pre-procedural molecular screening. The results of this study demonstrate the impact of the vaccines on reduction in asymptomatic infections supplementing the randomized trial results on symptomatic patients.

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Big data and artificial intelligence for health system sustainability: The case of Veneto Region

MANAGEMENT CONTROL ◽

10.3280/maco2021-001-s1003 ◽

2021 ◽

pp. 31-52

Author(s):

Grazia Dicuonzo ◽

Francesca Donofrio ◽

Antonio Fusco ◽

Vittorio Dell’Atti

Keyword(s):

Artificial Intelligence ◽

Big Data ◽

Healthcare System ◽

Care Delivery ◽

Research Question ◽

Health Agency ◽

Time Frame ◽

Structured Interviews ◽

Case Study Methodology ◽

The Impact

This paper investigates the digitalization challenges facing the Italian healthcare system. The aim of the paper is to support healthcare organizations as they take advantage of the potential of big data and artificial intelligence (AI) to promote sustainable healthcare systems. Both the development of innovative processes in the management of health care activities and the introduction of healthcare forecasting systems are valuable resources for clinical and care activities and enable a more efficient use of inputs in essential-level care delivery. By examining an innovative project developed by the Regional Social Health Agency (ARSS) of Veneto, this study analyses the impact of big data and AI on the sustainability of a healthcare system. In order to answer the research question, we used a case study methodology. We conducted semi-structured interviews with key members of the organizational group involved in the case. The results show that the implementation of AI algorithms based on big data in healthcare both improves the interpretation and processing of data, and reduces the time frame necessary for clinical processes, having a positive effect on sustainability.

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The impact of improving the sales management system enterprises of the automotive industry on economic indicators

10.18411/lj-01-2021-53 ◽

2021 ◽

Author(s):

D.R. Grigor'eva ◽

G.A. Gareeva ◽

R.R. Basyrov ◽

L.F. Tagirova

Keyword(s):

Automotive Industry ◽

Management System ◽

Sales Management ◽

Economic Indicators ◽

The Impact

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Regression Analysis of the Impact of Demographic and Economic Indicators on the Status of Pension Provision in Different World Countries

Business Inform ◽

10.32983/2222-4459-2020-5-183-189 ◽

2020 ◽

Vol 5 (508) ◽

pp. 183-189

Author(s):

K. I. Demchenko ◽

Keyword(s):

Regression Analysis ◽

Economic Indicators ◽

The Status ◽

The Impact

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Opportunities and Challenges for Interpreting Rare Variation in Clinically Important Genes

10.20944/preprints202011.0599.v1 ◽

2020 ◽

Author(s):

Gregory McInnes ◽

Andrew G. Sharo ◽

Megan L. Koleske ◽

Julie E. H. Brown ◽

Matthew Norstad ◽

...

Keyword(s):

Healthcare System ◽

Protein Function ◽

Rare Variants ◽

Clinical Importance ◽

Computational Prediction ◽

Ethical Challenges ◽

Inborn Errors ◽

Rare Variation ◽

Learning Healthcare System ◽

The Impact

Genome sequencing is enabling precision medicine—tailoring treatment to the unique constellation of variants in an individual’s genome. The impact of recurrent pathogenic variants is often understood, leaving a long tail of rare genetic variants that are uncharacterized. The problem of uncharacterized rare variation is especially acute when it occurs in genes of known clinical importance with functionally consequent frequent variants and associated mechanisms. Variants of unknown significance (VUS) in these genes are discovered at a rate that outpaces current ability to classify them using databases of previous cases, experimental evaluation, and computational predictors. Clinicians are thus left without guidance about the significance of variants that may have actionable consequences. Computational prediction of the impact of rare genetic variation is increasingly becoming an important capability. In this paper, we review the technical and ethical challenges of interpreting the function of rare variants in two settings: inborn errors of metabolism in newborns, and pharmacogenomics. We propose a framework for a genomic learning healthcare system with an initial focus on early-onset treatable disease in newborns and actionable pharmacogenomics. We argue that (1) a genomic learning healthcare system must allow for continuous collection and assessment of rare variants, (2) emerging machine learning methods will enable algorithms to predict the clinical impact of rare variants on protein function, and (3) ethical considerations must inform the construction and deployment of all rare-variation triage strategies, particularly with respect to health disparities arising from unbalanced ancestry representation.

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The Impact of Errors in the Area of Taxable Expenses and Revenues on Economic Indicators

Journal of Competitiveness ◽

10.7441/joc.2019.01.03 ◽

2019 ◽

Vol 11 (1) ◽

pp. 41-51

Author(s):

Eva Kolarova ◽

◽

Vendula Kolarova ◽

David Homola ◽

◽

...

Keyword(s):

Economic Indicators ◽

The Impact

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THE IMPACT OF M&A TRANSACTIONS ON THE GROWTH OF THE BANKS’ MARKET VALUE

Financial and credit activity problems of theory and practice ◽

10.18371/fcaptp.v5i40.244871 ◽

2021 ◽

Vol 5 (40) ◽

pp. 45-54

Author(s):

L. Prymostka ◽

N. Pantielieieva ◽

I. Krasnova ◽

V. Lavreniuk ◽

O. Lytvynenko

Keyword(s):

Economic Development ◽

Mergers And Acquisitions ◽

Banking Sector ◽

Jel Classification ◽

Economic Indicators ◽

Level Of Economic Development ◽

Banking Business ◽

Economic Trends ◽

The Impact ◽

The Relationship

Abstract. The globalization of markets, the need to comply with modern economic trends and introduce new technological solutions to increase the profitability of the banking business have significantly intensified the processes of mergers and acquisitions in the banking sector. M&A processes are long and complex, their results are difficult to forecast in lack of actual detailed research. The diversity of the results of the available research requires updating the data based on larger volumes of transactions and larger time intervals. The purpose of the article is to substantiate two hypotheses: first, the impact of M&A agreements especially on the increase in the value of banks; and impact of factors that show economic development level on the value of banks. The object of the study is the relationship between the value of commercial banks in domestic and foreign financial markets, M&A agreements, as well as economic indicators published by the World Bank and measuring the level of economic development of countries. The article uses statistical modeling method. The constructed model of linear regression allows to state that the fact of influence of M&A on growth of cost of consolidated banks is fair for 54.8% of cases. The study shows that the M&A processes have the greatest impact on the value of banks in the interval of 3—5 years after the conclusion of the agreement. Analysis of the relationship between economic indicators and the growth of bank value shows that the greatest impact on the value of banks has percent of the growth of GDP and GDP per capita, but the low value of the determinant at 22.9% indicates a low dependence of bank value on the level of economic indicators in general. It was found that external factors do not directly affect the growth in the value of banks in the process of M&A transactions. The question of expanding the system of factors that will influence the M&A processes and, as a consequence, the value of the banks, will be the subject of further research. Keywords: globalization of markets, mergers and acquisitions of banks, consolidation, M&A dynamic, market capitalization, bank value. JEL Classification Е44, Е47, G14 Formulas: 2; fig.: 4; tabl.: 4; bibl.: 14.

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