Evaluation of a direct-to-patient telehealth service in Germany (docdirekt) based on routine data

2021 ◽  
Author(s):  
Christoph Strumann ◽  
Jost Steinhäuser
Keyword(s):  
Routine Data ◽  
Telehealth Service

scholarly journals The psychosocial response to a terrorist attack at Manchester Arena, 2017: a process evaluation

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Daniel Hind ◽  
Kate Allsopp ◽  
Prathiba Chitsabesan ◽  
Paul French
Keyword(s):  
Young People ◽  
Process Evaluation ◽  
Terrorist Attack ◽  
Health Sector ◽  
Routine Data ◽  
Recovery Phase ◽  
Normalisation Process Theory ◽  
Structured Interviews ◽  
Framework Analysis ◽  
Response Phase

Abstract Background A 2017 terrorist attack in Manchester, UK, affected large numbers of adults and young people. During the response phase (first seven weeks), a multi-sector collaborative co-ordinated a decentralised response. In the subsequent recovery phase they implemented a centralised assertive outreach programme, ‘The Resilience Hub’, to screen and refer those affected. We present a process evaluation conducted after 1 year. Methods Case study, involving a logic modelling approach, aggregate routine data, and semi-structured interviews topic guides based on the Inter-Agency Collaboration Framework and May’s Normalisation Process Theory. Leaders from health, education and voluntary sectors (n = 21) and frontline Resilience Hub workers (n = 6) were sampled for maximum variation or theoretically, then consented and interviewed. Framework analysis of transcripts was undertaken by two researchers. Results Devolved government, a collaborative culture, and existing clinical networks meant that, in the response phase, a collaboration was quickly established between health and education. All but one leader evaluated the response positively, although they were not involved in pre-disaster statutory planning. However, despite overwhelming positive feedback there were clear difficulties. (1) Some voluntary sector colleagues felt that it took some time for them to be involved. (2) Other VCSE organisations were accused of inappropriate, harmful use of early intervention. (3) The health sector were accused of overlooking those below the threshold for clinical treatment. (4) There was a perception that there were barriers to information sharing across organisations, which was particularly evident in relation to attempts to outreach to first responders and other professionals who may have been affected by the incident. (5) Hub workers encountered barriers to referring people who live outside of Greater Manchester. After 1 year of the recovery phase, 877 children and young people and 2375 adults had completed screening via the Resilience Hub, 79% of whom lived outside Greater Manchester. Conclusions The psychosocial response to terrorist attacks and other contingencies should be planned and practiced before the event, including reviews of communications, protocols, data sharing procedures and workforce capacity. Further research is needed to understand how the health and voluntary sectors can best collaborate in the wake of future incidents.

scholarly journals Record linkage of routine data with cohorts’ data of infants under European and Portuguese law

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
J Doetsch ◽  
I Lopes ◽  
R Redinha ◽  
H Barros
Keyword(s):  
Big Data ◽  
Data Processing ◽  
Data Protection ◽  
Record Linkage ◽  
Data Science ◽  
Personal Data ◽  
Routine Data ◽  
Cohort Data ◽  
Education Data ◽  
Explicit Consent

Abstract The usage and exchange of “big data” is at the forefront of the data science agenda where Record Linkage plays a prominent role in biomedical research. In an era of ubiquitous data exchange and big data, Record Linkage is almost inevitable, but raises ethical and legal problems, namely personal data and privacy protection. Record Linkage refers to the general merging of data information to consolidate facts about an individual or an event that are not available in a separate record. This article provides an overview of ethical challenges and research opportunities in linking routine data on health and education with cohort data from very preterm (VPT) infants in Portugal. Portuguese, European and International law has been reviewed on data processing, protection and privacy. A three-stage analysis was carried out: i) interplay of threefold law-levelling for Record Linkage at different levels; ii) impact of data protection and privacy rights for data processing, iii) data linkage process' challenges and opportunities for research. A framework to discuss the process and its implications for data protection and privacy was created. The GDPR functions as utmost substantial legal basis for the protection of personal data in Record Linkage, and explicit written consent is considered the appropriate basis for the processing sensitive data. In Portugal, retrospective access to routine data is permitted if anonymised; for health data if it meets data processing requirements declared with an explicit consent; for education data if the data processing rules are complied. Routine health and education data can be linked to cohort data if rights of the data subject and requirements and duties of processors and controllers are respected. A strong ethical context through the application of the GDPR in all phases of research need to be established to achieve Record Linkage between cohort and routine collected records for health and education data of VPT infants in Portugal. Key messages GDPR is the most important legal framework for the protection of personal data, however, its uniform approach granting freedom to its Member states hampers Record Linkage processes among EU countries. The question remains whether the gap between data protection and privacy is adequately balanced at three legal levels to guarantee freedom for research and the improvement of health of data subjects.

scholarly journals Comparing Charlson and Elixhauser comorbidity indices with different weightings to predict in-hospital mortality: an analysis of national inpatient data

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Narayan Sharma ◽  
René Schwendimann ◽  
Olga Endrich ◽  
Dietmar Ausserhofer ◽  
Michael Simon
Keyword(s):  
Hospital Mortality ◽  
Patient Population ◽  
Generalized Additive Models ◽  
Routine Data ◽  
Predictive Performance ◽  
Population Based ◽  
Mortality Prediction ◽  
Additive Models ◽  
General Hospitals ◽  
Net Reclassification Improvement

Abstract Background Understanding how comorbidity measures contribute to patient mortality is essential both to describe patient health status and to adjust for risks and potential confounding. The Charlson and Elixhauser comorbidity indices are well-established for risk adjustment and mortality prediction. Still, a different set of comorbidity weights might improve the prediction of in-hospital mortality. The present study, therefore, aimed to derive a set of new Swiss Elixhauser comorbidity weightings, to validate and compare them against those of the Charlson and Elixhauser-based van Walraven weights in an adult in-patient population-based cohort of general hospitals. Methods Retrospective analysis was conducted with routine data of 102 Swiss general hospitals (2012–2017) for 6.09 million inpatient cases. To derive the Swiss weightings for the Elixhauser comorbidity index, we randomly halved the inpatient data and validated the results of part 1 alongside the established weighting systems in part 2, to predict in-hospital mortality. Charlson and van Walraven weights were applied to Charlson and Elixhauser comorbidity indices. Derivation and validation of weightings were conducted with generalized additive models adjusted for age, gender and hospital types. Results Overall, the Elixhauser indices, c-statistic with Swiss weights (0.867, 95% CI, 0.865–0.868) and van Walraven’s weights (0.863, 95% CI, 0.862–0.864) had substantial advantage over Charlson’s weights (0.850, 95% CI, 0.849–0.851) and in the derivation and validation groups. The net reclassification improvement of new Swiss weights improved the predictive performance by 1.6% on the Elixhauser-van Walraven and 4.9% on the Charlson weights. Conclusions All weightings confirmed previous results with the national dataset. The new Swiss weightings model improved slightly the prediction of in-hospital mortality in Swiss hospitals. The newly derive weights support patient population-based analysis of in-hospital mortality and seek country or specific cohort-based weightings.

scholarly journals Socio-economic consequences of mental distress: quantifying the impact of self-reported mental distress on the days of incapacity to work and medical costs in a two-year period: a longitudinal study in Germany

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Gerhard Müller ◽  
Manuela Bombana ◽  
Monika Heinzel-Gutenbrenner ◽  
Nikolaus Kleindienst ◽  
Martin Bohus ◽  
...  
Keyword(s):  
Mental Disorders ◽  
Mental Distress ◽  
Linear Models ◽  
Longitudinal Research ◽  
Depression Scale ◽  
Routine Data ◽  
Medical Costs ◽  
First Year ◽  
Second Year ◽  
The Impact

Abstract Background Mental disorders are related to high individual suffering and significant socio-economic burdens. However, it remains unclear to what extent self-reported mental distress is related to individuals’ days of incapacity to work and their medical costs. This study aims to investigate the impact of self-reported mental distress for specific and non-specific days of incapacity to work and specific and non-specific medical costs over a two-year span. Method Within a longitudinal research design, 2287 study participants’ mental distress was assessed using the Hospital Anxiety and Depression Scale (HADS). HADS scores were included as predictors in generalized linear models with a Tweedie distribution with log link function to predict participants’ days of incapacity to work and medical costs retrieved from their health insurance routine data during the following two-year period. Results Current mental distress was found to be significantly related to the number of specific days absent from work and medical costs. Compared to participants classified as no cases by the HADS (2.6 days), severe case participants showed 27.3-times as many specific days of incapacity to work in the first year (72 days) and 10.3-times as many days in the second year (44 days), and resulted in 11.4-times more medical costs in the first year (2272 EUR) and 6.2-times more in the second year (1319 EUR). The relationship of mental distress to non-specific days of incapacity to work and non-specific medical costs was also significant, but mainly driven from specific absent days and specific medical costs. Our results also indicate that the prevalence of presenteeism is considerably high: 42% of individuals continued to go to work despite severe mental distress. Conclusions Our results show that self-reported mental distress, assessed by the HADS, is highly related to the days of incapacity to work and medical costs in the two-year period. Reducing mental distress by improving preventive structures for at-risk populations and increasing access to evidence-based treatments for individuals with mental disorders might, therefore, pay for itself and could help to reduce public costs.

Identification of MIB producers and odor risk assessment using routine data: A case study of an estuary drinking water reservoir

2021 ◽  
Vol 192 ◽  
pp. 116848
Author(s):  
Ming Su ◽  
Yiping Zhu ◽  
Zeyu Jia ◽  
Tingting Liu ◽  
Jianwei Yu ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Drinking Water ◽  
Water Reservoir ◽  
Routine Data ◽  
Drinking Water Reservoir

scholarly journals Design of a prospective follow-up study on early parenthood and smoking behaviour during pregnancy in Finnish primary healthcare

2021 ◽  
pp. 140349482110224
Author(s):  
Mikael O. Ekblad ◽  
Hanna P. Wallin ◽  
Marjukka Pajulo ◽  
Päivi E. Korhonen
Keyword(s):  
Pregnant Women ◽  
Study Design ◽  
Primary Healthcare ◽  
Routine Data ◽  
Smoking Behaviour ◽  
Self Report ◽  
Health Clinic ◽  
Follow Up Study ◽  
Study Population

Aims: The primary aim of the study is to explore different factors affecting parents’ smoking behaviour, and especially how smoking may be connected with individual differences in the psychological process of becoming a parent. In the current paper, we present the study design together with basic information on the study population. Methods: The Central Satakunta Maternity and Child Health Clinic (KESALATU) Study is an ongoing prospective follow-up study in primary healthcare of the Satakunta region of southwest Finland. Families were recruited during their first maternity clinic visit between 1 September 2016 and 31 December 2019, and participation will continue until the child is 1.5 years of age. The study combines different sources and types of data: e.g. routine data obtained from primary healthcare clinic records, specific parental self-report data and data from a new exhaled carbon monoxide meter indicating maternal smoking. The data are collected using frequently repeated assessments both during pregnancy and postnatally. The methods cover the following areas of interest: family background factors (including smoking and alcohol use), self-reported parental–foetal/infant attachment and mentalization, self-reported stress, depression and quality of life. Results: 589 pregnant women and their partners were asked to participate in the study during the collection time period. The final study population consisted of 248 (42.1%) pregnant women and 160 (27.1%) partners. Conclusions: The new methods and study design have the potential to increase our understanding about the link between early parenting psychology, prenatal psychosocial risk factors and parental health behaviour.

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