Intensive COVID-19 testing associated with reduced mortality - an ecological analysis of 108 countries

BackgroundIntensive screening and testing for COVID-19 could facilitate early detection and isolation of infected persons and thereby control the size of the epidemic. It could also facilitate earlier and more targeted therapy. These factors could plausibly reduce attributable mortality which was the hypothesis tested in this study.MethodsLinear regression was used to assess the country-level association between COVID-19 attributable mortality per 100 000 inhabitants (mortality/capita) and COVID-19 tests/capita (number of tests/100 000 inhabitants) controlling for the cumulative number of COVID-19 infections/100 000 inhabitants (cases/capita), the age of the epidemic (number of days between first case reported and 8 April), national health expenditure per capita and WHO world region.ResultsThe COVID-19 mortality rate varied between 0.3 and 3110 deaths/100 000 inhabitants (median 30, IQR 8–105). The intensity of testing per 100 000 also varied considerably (median 21,970, IQR 2,735–89,095) as did the number of COVID-19 cases per 100 000 (median 1,600, IQR 340–4,760 cases/100 000). In the multivariate model, the COVID-19 mortality rate was negatively associated with tests/capita (Coef. –0.036, 95% CI –0.047- –0.025) and positively associated with cases/capita (Coef. 0.093, 95% CI 0.819- 1.034).ConclusionsThe results are compatible with the hypothesis that intensive testing and isolation could play a role in reducing COVID-10 mortality rates.

Analysis of novel FAGM(1,1,tα) model to forecast health expenditure of China

PurposeThe purpose of this paper is to study a fractional grey model FAGM(1,1,tα) based on the GM(1,1,tα) model and the fractional accumulated generating operation, and then predict the national health expenditure, the government health expenditure and the out-of-pocket health expenditure of China.Design/methodology/approachThe presented univariate grey model is systematically studied by using the grey modelling technique, the fractional accumulated generating operation and the trapezoid approximation formula of definite integral. The optimal system parametersrandαare evaluated by the particle swarm optimisation algorithm.FindingsThe expressions of the time response function and the restored values of this model are derived. The GM(1,1), NGM(1,1,k,c) and GM(1,1,tα) models are particular cases of the FAGM(1,1,tα) model with deterministicrandα. Compared with other forecasting models, the results of the FAGM(1,1,tα) model have higher precision.Practical implicationsThe superiority of the new model has high potential to be used in the medicine and health fields and others. Results can provide a guideline for government decision making.Originality/valueThe univariate fractional grey model FAGM (1,1,tα) successfully studies the China’s health expenditure.

Prevalence and costs of defensive medicine: a national survey of Italian physicians

Objective To identify the prevalence of the practice of defensive medicine among Italian hospital physicians, its costs and the reasons for practising defensive medicine and possible solutions to reduce the practice of defensive medicine. Methods Cross-sectional web survey. Main outcome measures Number of physicians reporting having engaged in any defensive medicine behaviour in the previous year. Results A total of 1313 physicians completed the survey. Ninety-five per cent believed that defensive medicine would increase in the near future. The practice of defensive medicine accounted for approximately 10% of total annual Italian national health expenditure. Conclusions Defensive medicine is a significant factor in health care costs without adding any benefit to patients. The economic burden of defensive medicine on health care systems should provide a substantial stimulus for a prompt review of this situation in a time of economic crisis. Malpractice reform, together with a systematic use of evidence-based clinical guidelines, is likely to be the most effective way to reduce defensive medicine.