Health estimate differences between six independent web surveys: different web surveys, different results?

Most general population web surveys are based on online panels maintained by commercial survey agencies. Many of these panels are based on non-probability samples. However, survey agencies differ in their panel selection and management strategies. Little is known if these different strategies cause differences in survey estimates. This paper presents the results of a systematic study designed to analyze the differences in web survey results between agencies. Six different survey agencies were commissioned with the same web survey using an identical standardized questionnaire covering factual health items. Five surveys were fielded at the same time. A calibration approach was used to control the effect of demographics on the outcome. Overall, the results show differences between probability and non-probability surveys in health estimates, which were reduced but not eliminated by weighting. Furthermore, the differences between non-probability surveys before and after weighting are larger than expected between random samples from the same population.

[Knowledge and attitudes towards sharing of health data: Results of a population survey]. / Wissen und Einstellung zur Speicherung und Nutzung von Gesundheitsdaten: Ergebnisse einer Bevölkerungsbefragung.

OBJECTIVE: The article tackles various issues arising in the context of the process of digitalization in the health sector. The communication and availability of health data, health registers, the electronic health record, consent procedures for the transfer of data and access to health data for research are considered. METHODS: The study is based on a computer-assisted telephone survey (dual-frame) of a random sample of adult people living in Germany. Data was collected in the period between June 01 and June 27, 2022 (n = 1,308). RESULTS: The level of knowledge concerning the transmission of health data to health insurers is good, whereas the existence of central death-, vaccination- and health registers as well as the access to health data by treating physicians is overestimated. The general acceptance of medical registers is very high. Half the population is unfamiliar with the electronic health record, and the willingness to use it is rather low. An opt-in procedure is preferred when transferring data, and more than eighty percent would release data in their electronic health file for research purposes. Three quarters would consent that their health data be handed over to general research, especially if reserach facilities were situated at German universities, under the condition that their data be treated confidentiallly. The willingness to release data correlates with the level of trust in the press as well as in universities and colleges and decreases when a data leak is considered to be serious. DISCUSSION AND CONCLUSION: In Germany, as in other European countries, we observe a great willingness of people to release health data for research purposes. However, the propensity to use the electronic health file is comparatively low, as is the acceptance of an opt-out procedure, which in the literature is considered a prerequisite for the successful implementation of electronic health records in other countries. Unsurprisingly, a general trust in research and government agencies that process health data is a key factor.

Analyzing factors determining vaccination willingness against COVID-19 in Germany 2020.

The study is based on a German single-topic population survey on vaccination willingness against COVID-19 (VWC) by the authors (2020, n = 2014). The single-topic survey allowed us to test several competing explanations for VWC, as discussed in the literature. The VWC in the sample was 67.3%. Logistic regression was used to identify factors affecting VWC. Being at high risk from COVID-19 and having received flu vaccination have a positive impact on VWC. Perceived VWC of friends has a strong positive effect on respondents' VWC. Bivariate relationships of gender, age, and level of education with VWC were no longer significant in a multivariate analysis. Trust in alternative medicine and belief in conspiracy theories have a negative effect on VWC.

Thirty-three myths and misconceptions about population data: from data capture and processing to linkage.

Databases covering all individuals of a population are increasingly used for research and decision-making. The massive size of such databases is often mistaken as a guarantee for valid inferences. However, population data have characteristics that make them challenging to use. Various assumptions on population coverage and data quality are commonly made, including how such data were captured and what types of processing have been applied to them. Furthermore, the full potential of population data can often only be unlocked when such data are linked to other databases. Record linkage often implies subtle technical problems, which are easily missed. We discuss a diverse range of myths and misconceptions relevant for anybody capturing, processing, linking, or analysing population data. Remarkably, many of these myths and misconceptions are due to the social nature of data collections and are therefore missed by purely technical accounts of data processing. Many are also not well documented in scientific publications. We conclude with a set of recommendations for using population data.

Microsimulation of an educational attainment register to predict future record linkage quality.

Introduction: Population wide educational attainment registers are necessary for educational planning and research. Regular linking of databases is needed to build and update such a register. Without availability of unique national identification numbers, record linkage must be based on quasi-identifiers such as name, date of birth and sex. However, the data protection principle of data minimization aims to minimize the set of identifiers in databases. Objectives: Therefore, the German Federal Ministry of Research and Education commissioned a study to inform legislation on the minimum set of identifiers required for a national educational register. Methods: To justify our recommendations empirically, we implemented a microsimulation of about 20 million people. The simulated register accumulates changes and errors in identifiers due to migration, regional mobility, marriage, school career and mortality, thereby allowing the study of errors on longitudinal datasets. Updated records were linked yearly to the simulated register using several linkage methods. Clear-text methods as well as privacy-preserving (PPRL) methods were compared. Results: The results indicate linkage bias if only the primary identifiers are available in the register. More detailed identifiers, including place of birth, are required to minimize linkage bias. The amount of information available to identify a person for matching is more critical for linkage quality than the record linkage method applied. Differences in linkage quality between the best procedures (probabilistic linkage and multiple matchkeys) are minor. Conclusions: Microsimulation is a valuable tool for designing record linkage procedures. By modelling the processes resulting in changes or errors in quasi-identifiers, predicting data quality to be expected after the implementation of a register seems possible.

On the effectiveness of graph matching attacks against privacy-preserving record linkage.

Linking several databases containing information on the same person is an essential step of many data workflows. Due to the potential sensitivity of the data, the identity of the persons should be kept private. Privacy-Preserving Record-Linkage (PPRL) techniques have been developed to link persons despite errors in the identifiers used to link the databases without violating their privacy. The basic approach is to use encoded quasi-identifiers instead of plain quasi-identifiers for making the linkage decision. Ideally, the encoded quasi-identifiers should prevent re-identification but still allow for a good linkage quality. While several PPRL techniques have been proposed so far, Bloom filter-based PPRL schemes (BF-PPRL) are among the most popular due to their scalability. However, a recently proposed attack on BF-PPRL based on graph similarities seems to allow individuals' re-identification from encoded quasi-identifiers. Therefore, the graph matching attack is widely considered a serious threat to many PPRL-approaches and leads to the situation that BF-PPRL schemes are rejected as being insecure. In this work, we argue that this view is not fully justified. We show by experiments that the success of graph matching attacks requires a high overlap between encoded and plain records used for the attack. As soon as this condition is not fulfilled, the success rate sharply decreases and renders the attacks hardly effective. This necessary condition does severely limit the applicability of these attacks in practice and also allows for simple but effective countermeasures.

Evaluation of the aerodynamic performance of the counter rotating turbo fan COBRA by means of experimental and numerical data.

In the present study, steady numerical simulations performed on the counter rotating turbo fan (CRTF) COBRA are compared with experimental data carried at the CIAM C-3A test-bench in Moscow. For this purpose, a systematic analysis of the measurement uncertainties was performed for the global aerodynamic performances of the CRTF, namely, the massflow, the total pressure ratio, the isentropic efficiency, as well as the torque ratio applied on both fan rows. Several numerical models are investigated to highlight their effects on the aforementioned predicted quantities. Differences in modeling consist in grid resolutions and the use of two turbulence models popular in the turbomachinery community. To match as much as possible the experiment running conditions, the performance map of the CRTF is simulated using the exact measured speed ratio and massflow. The comparisons show good estimations of the numerical simulation over the entire performance map. The main differences between the turbulence models occur at part-speed close to stall conditions. More surprisingly at aerodynamic design point, the importance of the turbulence modeling on the predicted torque ratio has been pointed out.

[Parents' Willingness to Vaccinate with a COVID-19 Vaccine]. / Impfbereitschaft von Eltern mit einem COVID-19-Vakzin: Die Rolle von Elternschaft und Geschlecht.

BACKGROUND: Parents are faced with a vaccination decision in the context of their own vaccination and that of their children with a COVID-19 vaccine. At present, there is no (complete) vaccination recommendation. RESEARCH QUESTION: The study investigates the willingness to vaccinate of parents of minors and people without children who are minors, in which gender differences in particular are examined. METHODS: The study is based on a random sample (telephone survey, n = 2,014, collected between 12 November and 10 December 2020). The evaluation is primarily based on the sub-sample of people with minors in the household (n = 461). RESULTS: Parents of minors consistently show a lower willingness to be vaccinated with a COVID-19 vaccine than respondents without minors (54.1% vs 71.1%). Fathers show a stronger willingness to be vaccinated than mothers. Furthermore, men are more willing to get their own child vaccinated with a COVID-19 vaccine than are women. CONCLUSIONS: Among parents and especially mothers, a considerable misrepresentation of vaccination risks and frequent beliefs in vaccination conspiracy theories can be observed. Clear and easily understandable information on the effects and side effects of vaccination with a COVID-19 vaccine by relevant institutions and physicians is recommended.

[Factors Influencing Willingness to be Vaccinated with a COVID-19 Vaccine: Results of a CATI Population Survey]. / Impfbereitschaft mit einem COVID-19-Vakzin und Einflussfaktoren. Ergebnisse einer telefonischen Bevölkerungsbefragung.

OBJECTIVE: The study examines the willingness to be vaccinated with a COVID-19 vaccine using a random sample of the general population and its determinants (perceived risks of disease, perceived side effects and general attitudes towards vaccination, trust in institutions, socio-structural factors, influence of social reference groups). METHODS: The study was based on a telephone, one-topic population survey (n=2,014) on willingness to be vaccinated (before the approval of a COVID-19 vaccine in Germany in November/December 2020). RESULTS: The willingness to be vaccinated was about 67% and increased with the proportion of peers and acquaintances who were willing to be vaccinated and had trust in the Robert Koch Institute; willingness was higher in members of a risk group, and in cases where there was an expectation of dangerous consequences of an infection. Experience with infection among the respondents or in peer-groups increased the willingness to be vaccinated. Men had a higher willingness to be vaccinated. The willingness to be vaccinated increased consistently with the level of formal education (with the exception of people with a technical college entrance qualification). Overestimating the likelihood of severe side effects of influenza vaccinations reduced the willingness to be vaccinated against COVID-19. Findings of considerable overestimations of the frequency of serious vaccination side effects were striking. CONCLUSION: Implications for a target group-appropriate information campaign and risk communication are derived. Efforts to promote the willingness of the population to be vaccinated should focus in particular on disadvantaged population groups.

Locational privacy-preserving distance computations with intersecting sets of randomly labeled grid points.

BACKGROUND: We introduce and study a recently proposed method for privacy-preserving distance computations which has received little attention in the scientific literature so far. The method, which is based on intersecting sets of randomly labeled grid points, is henceforth denoted as ISGP allows calculating the approximate distances between masked spatial data. Coordinates are replaced by sets of hash values. The method allows the computation of distances between locations L when the locations at different points in time t are not known simultaneously. The distance between [Formula: see text] and [Formula: see text] could be computed even when [Formula: see text] does not exist at [Formula: see text] and [Formula: see text] has been deleted at [Formula: see text]. An example would be patients from a medical data set and locations of later hospitalizations. ISGP is a new tool for privacy-preserving data handling of geo-referenced data sets in general. Furthermore, this technique can be used to include geographical identifiers as additional information for privacy-preserving record-linkage. To show that the technique can be implemented in most high-level programming languages with a few lines of code, a complete implementation within the statistical programming language R is given. The properties of the method are explored using simulations based on large-scale real-world data of hospitals ([Formula: see text]) and residential locations ([Formula: see text]). The method has already been used in a real-world application. RESULTS: ISGP yields very accurate results. Our simulation study showed that-with appropriately chosen parameters - 99 % accuracy in the approximated distances is achieved. CONCLUSION: We discussed a new method for privacy-preserving distance computations in microdata. The method is highly accurate, fast, has low computational burden, and does not require excessive storage.

[What is the Optimal Minimum Provider Volume in the Provision of Care for Preterm Infants with a Birth Weight below 1250 g in Germany?] / Wie hoch ist die optimale Mindestmenge für die Behandlung Frühgeborener mit einem Geburtsgewicht unter 1250 g in Deutschland?

INTRODUCTION: Numerous studies have investigated volume-outcome relationships in the treatment of very low birth weight infants. However, studies addressing the identification of optimal thresholds when introducing minimum provider volumes for treatment of these infants do not exist. METHODS: Publicly available data (www.perinatalzentren.org) of more than 56,000 infants weighing less than 1250 g at birth (NB<1250) and treated in level-1 perinatal centers (highest level in Germany) between 2010 and 2018 was used for statistical analysis. Potentially avoidable deaths after the introduction of minimum provider volumes were calculated by deducting observed deaths from estimated deaths based on logistic regression models for every existing empirical provider volume. Various smoothing functions were used to ascertain optimal thresholds for minimum provider volumes. RESULTS: Independent of the observation period or smoothing technique, the highest number of potentially avoidable deaths was observed for minimum provider volumes of 50-60 NB<1250 per year. Introducing a minimum provider volume of 50 without a transition period would reduce the number of level-1 perinatal centers to a quarter of the current number in Germany. Approximately 60% of NB<1250 would have to be reallocated. CONCLUSION: Analyses of resulting geographical distances are needed in the preparation of minimum provider volumes for treatment of NB<1250 in Germany. Such analyses should include perinatal centers expected to reach minimum provider volumes after subsequent reallocation in the future.

Sociodemographic differences in linkage error: an examination of four large-scale datasets.

BACKGROUND: Record linkage is an important tool for epidemiologists and health planners. Record linkage studies will generally contain some level of residual record linkage error, where individual records are either incorrectly marked as belonging to the same individual, or incorrectly marked as belonging to separate individuals. A key question is whether errors in linkage quality are distributed evenly throughout the population, or whether certain subgroups will exhibit higher rates of error. Previous investigations of this issue have typically compared linked and un-linked records, which can conflate bias caused by record linkage error, with bias caused by missing records (data capture errors). METHODS: Four large administrative datasets were individually de-duplicated, with results compared to an available 'gold-standard' benchmark, allowing us to avoid methodological issues with comparing linked and un-linked records. Results were compared by gender, age, geographic remoteness (major cities, regional or remote) and socioeconomic status. RESULTS: Results varied between datasets, and by sociodemographic characteristic. The most consistent findings were worse linkage quality for younger individuals (seen in all four datasets) and worse linkage quality for those living in remote areas (seen in three of four datasets). The linkage quality within sociodemographic categories varied between datasets, with the associations with linkage error reversed across different datasets due to quirks of the specific data collection mechanisms and data sharing practices. CONCLUSIONS: These results suggest caution should be taken both when linking younger individuals and those in remote areas, and when analysing linked data from these subgroups. Further research is required to determine the ramifications of worse linkage quality in these subpopulations on research outcomes.

Protecting Record Linkage Identifiers Using a Language Model for Patient Names.

Linking information across databases fosters new research in the medical sciences. Recent European privacy regulations recommend encrypting personal identifiers used for linking. Bloom filter based methods are an increasingly popular Record Linkage method. However, basic Bloom filter encodings are prone to cryptographic attacks. Therefore, hardening methods against these attacks are required. In this paper, a new method for such a hardening method for Privacy-preserving Record Linkage (PPRL) technique is presented. By using a Markov chain-based language model of bigrams of identifiers during the encryption, protection against attacks is increased. Based on real-world mortality data, we compare unencrypted and state of the art PPRL methods with the results of the proposed hardening method.

Evaluating privacy-preserving record linkage using cryptographic long-term keys and multibit trees on large medical datasets.

BACKGROUND: Integrating medical data using databases from different sources by record linkage is a powerful technique increasingly used in medical research. Under many jurisdictions, unique personal identifiers needed for linking the records are unavailable. Since sensitive attributes, such as names, have to be used instead, privacy regulations usually demand encrypting these identifiers. The corresponding set of techniques for privacy-preserving record linkage (PPRL) has received widespread attention. One recent method is based on Bloom filters. Due to superior resilience against cryptographic attacks, composite Bloom filters (cryptographic long-term keys, CLKs) are considered best practice for privacy in PPRL. Real-world performance of these techniques using large-scale data is unknown up to now. METHODS: Using a large subset of Australian hospital admission data, we tested the performance of an innovative PPRL technique (CLKs using multibit trees) against a gold-standard derived from clear-text probabilistic record linkage. Linkage time and linkage quality (recall, precision and F-measure) were evaluated. RESULTS: Clear text probabilistic linkage resulted in marginally higher precision and recall than CLKs. PPRL required more computing time but 5 million records could still be de-duplicated within one day. However, the PPRL approach required fine tuning of parameters. CONCLUSIONS: We argue that increased privacy of PPRL comes with the price of small losses in precision and recall and a large increase in computational burden and setup time. These costs seem to be acceptable in most applied settings, but they have to be considered in the decision to apply PPRL. Further research on the optimal automatic choice of parameters is needed.

Combining Different Privacy-Preserving Record Linkage Methods for Hospital Admission Data.

Record linkage (RL) is the process of identifying pairs of records that correspond to the same entity, for example the same patient. The basic approach assigns to each pair of records a similarity weight, and then determines a certain threshold, above which the two records are considered to be a match. Three different RL methods were applied under privacy-preserving conditions on hospital admission data: deterministic RL (DRL), probabilistic RL (PRL), and Bloom filters. The patient characteristics like names were one-way encrypted (DRL, PRL) or transformed to a cryptographic longterm key (Bloom filters). Based on one year of hospital admissions, the data set was split randomly in 30 thousand new and 1,5 million known patients. With the combination of the three RL-methods, a positive predictive value of 83 % (95 %-confidence interval 65 %-94 %) was attained. Thus, the application of the presented combination of RL-methods seem to be suited for other applications of population-based research.

Impact of standardized patients on the training of medical students to manage emergencies.

BACKGROUND: Teaching emergency management should educate medical students not only for facts and treatment algorithms but also for time effective physical examination, technical skills, and team interaction. We tested the hypothesis, that using standardized emergency patients would be more effective in transmitting knowledge and skills compared with a more traditional teaching approach. METHODS: Medical students (n = 242) in their fourth (second clinical) year were randomized to receive either training on standardized patients simulating 3 emergency settings ("acute chest pain," "stroke," and "acute dyspnea/asthma") or traditional small group seminars. Before and after the respective training pathways, the students' knowledge base (multiple-choice examination) and practical performance (objective structured clinical examination using 3 different emergency scenarios) were assessed. RESULTS: Teaching using standardized patients resulted in a significant albeit small improvement in objective structured clinical examination scores (61.2 ±â€Š3 for the standardized patient trained group vs 60.3 ±â€Š3.5 for the traditional seminar group; P = 0.017, maximum achievable score: 66), but no difference in the written examination scores (27.4 ±â€Š2.4 vs 27.0 ±â€Š4.4; P = 0.341; maximum achievable score: 30). CONCLUSION: Teaching management of emergencies using standardized patients can improve medical students' performance in clinical tests, and a change from traditional seminars in favor of practice sessions with standardized patients does not compromise the learning of medical facts.

Anonymisation of geographical distance matrices via Lipschitz embedding.

BACKGROUND: Anonymisation of spatially referenced data has received increasing attention in recent years. Whereas the research focus has been on the anonymisation of point locations, the disclosure risk arising from the publishing of inter-point distances and corresponding anonymisation methods have not been studied systematically. METHODS: We propose a new anonymisation method for the release of geographical distances between records of a microdata file--for example patients in a medical database. We discuss a data release scheme in which microdata without coordinates and an additional distance matrix between the corresponding rows of the microdata set are released. In contrast to most other approaches this method preserves small distances better than larger distances. The distances are modified by a variant of Lipschitz embedding. RESULTS: The effects of the embedding parameters on the risk of data disclosure are evaluated by linkage experiments using simulated data. The results indicate small disclosure risks for appropriate embedding parameters. CONCLUSION: The proposed method is useful if published distance information might be misused for the re-identification of records. The method can be used for publishing scientific-use-files and as an additional tool for record-linkage studies.

Improving the use of self-generated identification codes.

In panel studies on sensitive topics, respondent-generated identification codes are often used to link records across surveys. However, usually a substantial number of cases are lost due to the codes. These losses may cause biased estimates. Using more components and linking the codes by the Levenshtein string distance function will reduce the losses. In a simulation study and two field experiments, the proposed procedure outperforms the methods previously applied.