What can we learn from the effects of the COVID-19 pandemic on hospital care for children in Germany?

The COVID-19 pandemic created substantial disruptions in the delivery of health services around the world. Reductions in hospital admissions have been reported for several conditions in the adult population; less evidence currently exists for children. To what extent such changes reflect a risk for patients due to unmet care needs, or a “correction” of previous overprovision of care has not been thoroughly examined yet. Based on complete national hospital discharge data, we compare the top 30 diagnoses for which children were hospitalised in 2019, 2020 and 2021 in Germany. We also analyse the development of monthly admissions between January 2019 and December 2021 for three tracers of variable urgency and severity. Total admissions were approximately 20% lower in 2020 and 2021 compared to 2019. The composition of the most frequent diagnoses did not change dramatically across years, although changes in rank were observed. The number of admissions for acute lymphoblastic leukaemia (tracer 1) showed a slight increasing trend and a periodicity prima vista unrelated to pandemic factors. Appendicitis admissions (tracer 2) decreased by about 9% in 2020 and a further 8% in 2021, while tonsillectomies/adenoidectomies (tracer 3) decreased by more than 40% in 2020 and a further 30% in 2021; for these tracers, monthly changes are in line with pandemic waves. Observed variations in child hospitalisations reflect the effects of pandemic mitigation measures and/or changes in demand. In Germany, inpatient care for critical conditions appears to have been largely upheld, potentially at the expense of elective treatments. Complementary data on ambulatory care and health outcomes would enable a better understanding of change in healthcare patterns and effects on children's health.

Health services during Covid-19: What do we know of the degree of service disruption and size of the backlogs?

Since the onset of the COVID-19 pandemic, there have been concerns that shifting health system capacities towards acute COVID-19 cases can affect the provision of non-COVID-19 essential health services, causing severe disruptions and lack of care. Examples of this have been seen during other epidemic outbreaks, such as the 2014-2016 Ebola outbreak in West Africa. To capture the degree of service disruption across the European and Central Asian region, we analysed data from the World Health Organization's Pulse Survey on the Continuity of Essential Health Services, conducted in three rounds in 2020 and 2021. The key findings include:

– Health service provision has been heavily disrupted in virtually all countries. 91% of countries reported service disruptions in late 2021, indicating that health services continue to be disrupted at large scale.

– Service discontinuation has been substantial across all levels of care and in most service areas, often resulting in delays and cancellations of elective and emergency procedures, routine visits, prescription renewals, and referrals to specialty care. This has led to growing backlogs and record waiting times for services.

– Countries have been affected to varying degrees and report different levels of service disruption, size of the backlog, recovery of services aiming for pre-pandemic levels, and interventions to manage waiting lists.

The findings indicate that even as health systems are better learning to care for acute COVID-19 patients, the pandemic's impact on essential health services is massive and likely to affect the care for people's health and well-being post the acute phase of the public health emergency. Measuring the size of backlogs and implementing innovative care solutions are urgent and paramount.

How can we monitor the impact of national health information systems? Results from a scoping review

Background

National health information (HI) systems provide data on population health, the determinants of health and health system performance within countries. The evaluation of these systems has traditionally focused on statistical practices and procedures, and not on data use or reuse for policy and practice. This limits the capacity to assess the impact of HI systems on healthcare provision, management and policy-making. On the other hand, the field of Knowledge Translation (KT) has developed frameworks to guide evidence into practice.

Methods

A scoping review of the KT literature to identify the essential mechanisms and determinants of KT that could help monitor the impact of HI systems.

Results

We examined 79 publications and we identified over 100 different KT frameworks but none of these were focused on HI systems per se. There were specific recommendations on disseminating evidence to stakeholders at the institutional and organizational level, and on sustaining the use of evidence in practice and the broader community setting.

Conclusions

We developed a new model, the HI-Impact framework, in which four domains are essential for mapping the impact of national HI systems: (i) HI Evidence Quality, (ii) HI System Responsiveness, (iii) Stakeholder Engagement and (iv) Knowledge Integration. A comprehensive impact assessment of HI systems requires addressing the use of HI in public health decision-making, health service delivery and in other sectors which might have not been considered previously. Monitoring Stakeholder Engagement and Knowledge Integration certifies that the use of HI in all policies is an explicit point of assessment.

Delegation of medical services to specially trained medical practice assistants

Background

Germany is one of the countries most affected by demographic change. Meaning the shift towards the population being older is growing. At the same time, the number of doctors is declining. In order to ensure adequate care in Germany, the delegation of medical services to specially trained medical practice assistants (MPAs) is currently discussed. The aim of this study was to assess the attitudes of the German population towards medical delegation.

Methods

The analysis was based on a population survey of 6.105 German-speaking residents aged 18 years and over. Associations between respondents’ attitudes towards the delegation and social determinants (age, gender, education, employment status, region, self-rated health) were assessed using standardised questionnaires. Bi- and multivariate (logistic regression) analyses were performed.

Results

In case of a chronic disease half of the German-speaking population (51. 8%) would accept getting treated by a MPA. More older participants (65 years and above) than younger participants (18 to 34 years old) (OR: 1,64; KI [1,24-2,18]), more lower than higher educated participants (OR: 1,20; KI [1,04-1,39]) and more non-German than German participants (OR: 1,61; KI [1,24-2,10]) are significantly more likely to not accept medical delegation in case of a chronic disease. Discussion: In the debate on delegation models the present results should be taken into account in order to be able to address relevant target-groups. Further qualitative studies that investigate the reasons for the critical view on delegation are recommended.

Key messages

Approximately 50% of the German-speaking study population would accept treatment by a MPA for chronic disease. Especially older study participants, lower educated people and non-German participants would not accept medical delegation in case of a chronic disease.

The Health-Information Impact Index: a tool to monitor the uptake of evidence in policy and practice

Background

The optimal use of data and evidence from national health information systems is paramount in public health. However, current tools to evaluate health information systems focus on data quality and availability rather than measuring how data are used by key stakeholders. This limits capacity to monitor the impact of evidence on health care management and health policy making.

Methods

Based on an extensive literature review we developed a new model, the Health Information (HI)-Impact framework, to monitor the impact of health information in health policy and practice. We further conducted a web-based Delphi survey between February and April 2019 among European public health professionals working in health policy, health care, research, and health monitoring to develop the HI-Impact Index.

Results

In the HI-Impact framework, four domains are essential for mapping public health data availability, dissemination, and use: (1) Health Information and Evidence Quality, (2) Health Information System Responsiveness, (3) Stakeholder Engagement, and (4) Knowledge Integration. This last domain has a broader reach on the determinants of health and reflects the use of evidence by community partners and across sectors. In the DELPHI survey, 127 experts from 38 European countries selected 30 criteria to integrate in the HI-Impact Index. This tool could be used by European public health agencies to monitor the impact of their information products, and inform national strategies for evidence-based public health.

Conclusions

It is crucial for routine health information systems to create a culture of accountability in the use of evidence. Data on the determinants and consequences of ill-health as well as stakeholder engagement in leveraging evidence for intervention are explicit points to consider for a full quality assessment of national health information systems, and a sustainable impact on health outcomes.

Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing

Biogas production from renewable resources is attracting increased attention as an alternative energy source due to the limited availability of traditional fossil fuels. Many countries are promoting the use of alternative energy sources for sustainable energy production. In this study, a metagenome from a production-scale biogas fermenter was analysed employing Roche's GS FLX Titanium technology and compared to a previous dataset obtained from the same community DNA sample that was sequenced on the GS FLX platform. Taxonomic profiling based on 16S rRNA-specific sequences and an Environmental Gene Tag (EGT) analysis employing CARMA demonstrated that both approaches benefit from the longer read lengths obtained on the Titanium platform. Results confirmed Clostridia as the most prevalent taxonomic class, whereas species of the order Methanomicrobiales are dominant among methanogenic Archaea. However, the analyses also identified additional taxa that were missed by the previous study, including members of the genera Streptococcus, Acetivibrio, Garciella, Tissierella, and Gelria, which might also play a role in the fermentation process leading to the formation of methane. Taking advantage of the CARMA feature to correlate taxonomic information of sequences with their assigned functions, it appeared that Firmicutes, followed by Bacteroidetes and Proteobacteria, dominate within the functional context of polysaccharide degradation whereas Methanomicrobiales represent the most abundant taxonomic group responsible for methane production. Clostridia is the most important class involved in the reductive CoA pathway (Wood-Ljungdahl pathway) that is characteristic for acetogenesis. Based on binning of 16S rRNA-specific sequences allocated to the dominant genus Methanoculleus, it could be shown that this genus is represented by several different species. Phylogenetic analysis of these sequences placed them in close proximity to the hydrogenotrophic methanogen Methanoculleus bourgensis. While rarefaction analyses still indicate incomplete coverage, examination of the GS FLX Titanium dataset resulted in the identification of additional genera and functional elements, providing a far more complete coverage of the community involved in anaerobic fermentative pathways leading to methane formation.

WebCARMA: a web application for the functional and taxonomic classification of unassembled metagenomic reads

Background

Metagenomics is a new field of research on natural microbial communities. High-throughput sequencing techniques like 454 or Solexa-Illumina promise new possibilities as they are able to produce huge amounts of data in much shorter time and with less efforts and costs than the traditional Sanger technique. But the data produced comes in even shorter reads (35-100 basepairs with Illumina, 100-500 basepairs with 454-sequencing). CARMA is a new software pipeline for the characterisation of species composition and the genetic potential of microbial samples using short, unassembled reads.

Results

In this paper, we introduce WebCARMA, a refined version of CARMA available as a web application for the taxonomic and functional classification of unassembled (ultra-)short reads from metagenomic communities. In addition, we have analysed the applicability of ultra-short reads in metagenomics.

Conclusions

We show that unassembled reads as short as 35 bp can be used for the taxonomic classification of a metagenome. The web application is freely available at http://webcarma.cebitec.uni-bielefeld.de.

EMMA 2--a MAGE-compliant system for the collaborative analysis and integration of microarray data

Background

Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems.

Results

The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services.

Conclusion

Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.

Panta rhei (QAlign2): an open graphical environment for sequence analysis

MOTIVATION

The first version of the graphical multiple sequence alignment environment QAlign was published in 2003. Heavy response from the molecular-biological user community clearly demonstrated the need for such a platform.

RESULTS

Panta rhei extends QAlign by several features. Major redesigns on the user interface, for instance, allow users to flexibily compose views for multiple projects. The new sequence viewer handles datasets with arbitrarily many and arbitrarily large sequences that may still be edited by guided block moving. More distance-based algorithms are available to interactively reconstruct phylogenetic trees which can now also be zoomed and navigated graphicaly.

AVAILABILITY

Executables and the JAVA source code are available under the Apache license at http://gi.cebitec.uni-bielefeld.de/qalign

CONTACT

qalign@cebitec.uni-bielefeld.de.