Simplified Acute Physiology Score 3 Performance in Austrian COVID-19 Patients with and Without Diabetes

Background: TheSimplified Acute Physiology Score 3 (SAPS 3) is routinely used in intensive care units (ICUs) to predict in-hospital mortality. However, its predictive performance has not been widely evaluated in Coronavirus disease 19 (COVID-19) patients.This studyevaluated and comparedthe performance of SAPS 3for predicting in-hospital mortalityinCOVID-19patients with and without diabetesin Austria.Methods: This study analyzed the Austrian national public health institute (GÖG) data ofCOVID-19patients admitted to ICUs (N=5,850)fromMarch 2020 to March 2021.The SAPS 3 score was calculated and the predicted in-hospital mortality was estimatedusingthreelogit regression equations: standard equation, Central European equation, and Austrian equation recalibrated for COVID-19 patients. Concordance between observed and predicted mortalities was assessed using the standardized mortality ratio (SMR). Discrimination was assessed using the C-statistic. The DeLong test was applied to compare discrimination between diabetes and non-diabetes patients. Accuracy was assessed using the Brier score andcalibration using the calibration plot and Hosmer-Lemeshow test. Results: Theobservedin-hospital mortality was 38.9% in all patients, 42.9% in diabetes, and 37.3% innon-diabetes patients. Themean ±SD SAPS 3 score was 57.4 ±13.2 in all patients,58.8 ±12.9 in diabetes, and 56.8 ±13.2 in non-diabetes patients.The SMR was significantly greater than 1 for standard and Central European equations, while it was close to 1 for the Austrian equation in all, diabetes, and non-diabetes patients. TheC-statistics was 0.69 with aninsignificant (P=0.193) difference between diabetes (0.70)and non-diabetes (0.68)patients. The Brier score was >0.20 for all SAPS 3 equations. Calibration was unsatisfactory for both standard and Central European equations in all cohorts, whereas it was satisfactory for the Austrian equation in diabetes patients.Conclusions:The SAPS 3 score demonstratedlow discrimination and accuracy in COVID-19 patients in Austria with aninsignificant difference between diabetes and non-diabetes patients. All three equations of SAPS 3 were miscalibrated particularly in non-diabetes patients, while the Austrian equation demonstrated satisfactory calibration in diabetes patients. These findingssuggest that both uncalibrated and calibrated versions ofSAPS 3 should be used with caution in COVID-19 patients.

COVID-19 In-Hospital Mortality in People with Diabetes Is Driven by Comorbidities and Age—Propensity Score-Matched Analysis of Austrian National Public Health Institute Data

Background: It is a matter of debate whether diabetes alone or its associated comorbidities are responsible for severe COVID-19 outcomes. This study assessed the impact of diabetes on intensive care unit (ICU) admission and in-hospital mortality in hospitalized COVID-19 patients. Methods: A retrospective analysis was performed on a countrywide cohort of 40,632 COVID-19 patients hospitalized between March 2020 and March 2021. Data were provided by the Austrian data platform. The association of diabetes with outcomes was assessed using unmatched and propensity-score matched (PSM) logistic regression. Results: 12.2% of patients had diabetes, 14.5% were admitted to the ICU, and 16.2% died in the hospital. Unmatched logistic regression analysis showed a significant association of diabetes (odds ratio [OR]: 1.24, 95% confidence interval [CI]: 1.15–1.34, p < 0.001) with in-hospital mortality, whereas PSM analysis showed no significant association of diabetes with in-hospital mortality (OR: 1.08, 95%CI: 0.97–1.19, p = 0.146). Diabetes was associated with higher odds of ICU admissions in both unmatched (OR: 1.36, 95%CI: 1.25–1.47, p < 0.001) and PSM analysis (OR: 1.15, 95%CI: 1.04–1.28, p = 0.009). Conclusions: People with diabetes were more likely to be admitted to ICU compared to those without diabetes. However, advanced age and comorbidities rather than diabetes itself were associated with increased in-hospital mortality in COVID-19 patients.

The Financial Burden of Surgery for Congenital Malformations—The Austrian Perspective

Neonatal “surgical” malformations are associated with higher costs than major “non-surgical” birth defects. We aimed to analyze the financial burden on the Austrian health system of five congenital malformations requiring timely postnatal surgery. The database of the Austrian National Public Health Institute for the period from 2002 to 2014 was reviewed. Diagnosis-related group (DRG) points assigned to hospital admissions containing five congenital malformations coded as principal diagnosis (esophageal atresia, duodenal atresia, congenital diaphragmatic hernia, gastroschisis, and omphalocele) were collected and compared to all hospitalizations for other reasons. Out of 3,518,625 total hospitalizations, there were 1664 admissions of patients with the selected malformations. The annual mean number was 128 (SD 17, range 110–175). The mean cost of the congenital malformations per hospital admission expressed in DRG points was 26,588 (range 0–465,772, SD 40,702) and was significantly higher compared to the other hospitalizations (n = 3,516,961; mean DRG 2194, range 0–834,997; SD 6161; p < 0.05). Surgical conditions requiring timely postnatal surgery place a significant financial burden on the healthcare system. The creation of a dedicated national register could allow for better planning of resource allocation, for improving the outcome of affected children, and for optimizing costs.

A Life Quality Architectural Approach to Enhance Digital Skills Training

The paper presents the demand for professional services and skills in the health sector. The Erasmus+ DIGI4ME project aims to enhance digital skills trainings. An analysis of the Romanian health information system was conducted based on the interviews of the National Public Health Institute of Romania with stakeholders. According to the incidents which occurred in hospitals around the world, a system based on sensors is proposed to mitigate the problems which can appear. The testing of the system was done in laboratory conditions and the reports display the evolution of the measured environmental parameters. The software solution can determine medical professionals to enhance their digital skills and trigger creative ideas to improve the experience of their patients.

Pitfalls of rubella serology while on the brink of elimination: evaluation of national data, Belgium, 2017

Background In Belgium, rubella serology is frequently requested in women of childbearing age, despite high vaccination coverage and a near-absence of congenital rubella cases. Different test kits are available and should be standardised by an international standard preparation. Aim To analyse and compare rubella serology practices in Belgian laboratories. Methods As part of the mandatory External Quality Assessment programme for rubella serology in Belgium, the national public health institute, Sciensano, sent a voluntary questionnaire concerning anti-rubella IgM/IgG analyses in women aged 15 to 45 years in 2017 to 130 laboratories. Results The questionnaire response rate was 83.8% (109/130). The majority of 169,494 IgG analyses were performed on Roche (55%), Abbott (17%) and Diasorin (13%) analysers. Not all laboratories used the proposed international cut-off of 10 IU/mL. Assumed median seroprevalence ranged from 76.3% with Liaison (Diasorin) to 96.3% with Modular (Roche). Despite very low rubella incidence in Belgium, 93 laboratories performed 85,957 IgM analyses, with 748 positive and 394 grey zone results. The National Reference Centre for Measles, Mumps and Rubella virus and the National Reference Centre for Congenital infections did not confirm any positive rubella cases in 2017. Conclusion This retrospective analysis shows that rubella serology results may differ considerably according to the assay used. It is therefore important to use the same test when comparing results or performing follow-up testing. The number of anti-rubella IgM analyses was very high. Incorrect use of IgM for screening women of childbearing age can lead to unwarranted anxiety and overuse of confirmation tests.

Reading between the lines: A qualitative case study of national public health institute functions and attributes in the Joint External Evaluation

National Public Health Institutes (NPHIs) are national-level institutions that can lead and coordinate a country’s public health system. The Africa Centres for Disease Control and Prevention (Africa CDC) considers NPHI development critical to strengthening public health systems in Africa. This paper describes how Joint External Evaluation (JEE) reports demonstrate the role NPHIs can play in supporting the goals of IHR compliance and global health security. This study is a secondary document-based qualitative analysis of JEE reports from 11 countries in the WHO AFRO region (Botswana, Ethiopia, Liberia, Mozambique, Namibia, Nigeria, Rwanda, Sierra Leone, South Africa, Uganda, and Zambia). Researchers found three distinct thematic areas: i) core public health functions, ii) governance, and iii) coordination, collaboration, and communication. These themes and their interlinkages, both in pairs and all three, were of importance in displaying the roles that NPHIs could play in the strengthening of health systems. The data suggests that NPHIs, though not always explicitly mentioned in the data, may have a vital role in strengthening health systems across Africa and their governments’ goals of achieving IHR compliance.

Gender equity in scientific publishing: Analysis of publications in the Journal of Health Monitoring

Background The importance of gender- and sex-sensitive reporting and communication in science has been widely acknowledged in the past years. At the same time, a 'gendered system' of scientific publishing is increasingly discussed, given the underrepresentation of women as first and last authors, reviewers, on editorial boards and in editorial key positions. Against this background, the Journal of Health Monitoring (JoHM) - a scientific online journal published by the Federal Health Reporting at the Robert Koch Institute, Germany's national public health institute - took stock of the proportion of women among authors and reviewers. Methods Articles published in the JoHM between its founding in 2016 and the last issue in 2019 were included. Descriptive analysis was performed on the proportion of women in first and last authorship, stratified by publication format, and the proportion of peer reviews performed by women. Results A total of 145 articles were included in the analysis, comprising the categories Focus, Fact sheet, Concepts & Methods, Proceedings, Abstract and Editorial. The percentage of articles with first authorship by women was 66% (95/145), ranging from 53% for Focus articles (n = 16/30) to all of the Editorials (n = 6/6). 49% of last authors were female (n = 66/135). Overall, 42% of all reviews were performed by women (n = 96/233). Conclusions With almost two third of the publications analysed, first authorship of women in the JoHM is high. However, the proportion of female last authors and reviewers is lower in comparison. Next to professional qualification, gender should be taken into account when editors select reviewers. Overall, discussion should be stimulated on adequate representation of women in all areas of scientific publishing, given the relevance of visible merits in publishing for the building of scientific careers. Key messages Publications in the Journal of Health Monitoring have a high percentage of female first authors; in comparison, the percentage of last authorship and peer reviews by women is lower. An adequate representation of women in all areas of scientific publishing is essential, given the significance of publishing for merit in science and research.

Dutch public health policy during the COVID-19 pandemic of the first half of 2020. Answers to questions on public health activities January–June 2020

The authorities’ first responses were the classification of COVID-19 as Group A-disease in the sense of the Law on Public Health, scaling up of regular crisis control structures, installation of an Outbreak Management Team OMT and a “National Operational Team-Corona”. COVID-surveillance is done by the RIVM (National Public Health Institute), and is based on data from Municipal Public Health Services (GGDs) supplemented with additional (inter)national sources. The OMT is the main advisory body regarding preventive measures and includes experts from relevant medical specialisms. Organisations of medical professionals gave separate advices. Sanctions to preventive measures can be fines and closure of accommodations. Initially, 80% of the population trusted the government’s messages and “intelligent lockdown” strategy. The Prime Minister’s addresses to the people were highly appreciated. However, at slow-down of the outbreak (May-June) society’s trust crumbled (“quarantine-fatigue”). The initial testing policy was very restricted and contrary to WHO’s adagium “Test, test, test!”. In June the Minister of Health announced that a capacity of 30.000 tests per day was achieved, to be scaled up to 70.000. The crises management’s primary concern was to increase the (ICU-)bed capacity and was achieved by transforming regular wards into COVID-care, setting-up external “Corona-wards” in hotels, and regional, interregional and crossborder spreading of COVID-patients. This focus on ICU-bed capacity was criticized, as half of the death cases and extreme equipment shortages occurred in other sectors (nursing homes, homecare, homes for the elderly, psychiatry, mental handicaps). Transformation of hospital wards also led to waiting lists for non-COVID care. End of June the government presented a step-by-step easing of the lockdown in which a fine-tuned epidemiological surveillance dashboard and the continuation of economical support for the economic sector are the backbones.

Disease modeling for public health: added value, challenges, and institutional constraints

Public health policymakers face increasingly complex questions and decisions and need to deal with an increasing quantity of data and information. For policy advisors to make use of scientific evidence and to assess available intervention options effectively and therefore indirectly for those deciding on and implementing public health policies, mathematical modeling has proven to be a useful tool. In some areas, the use of mathematical modeling for public health policy support has become standard practice at various levels of decision-making. To make use of this tool effectively within public health organizations, it is necessary to provide good infrastructure and ensure close collaboration between modelers and policymakers. Based on experience from a national public health institute, we discuss the strategic requirements for good modeling practice for public health. For modeling to be of maximal value for a public health institute, the organization and budgeting of mathematical modeling should be transparent, and a long-term strategy for how to position and develop mathematical modeling should be in place.