BACKGROUND: People with severe or profound intellectual and motor disabilities (SPIMD) experience numerous serious physical health problems and comorbidities. Knowledge regarding the prevalence of these problems is needed in order to detect and treat them at an early stage. Data concerning these problems in individuals with SPIMD are limited. Therefore, the aim of this study was to determine the prevalence of reported physical health problems in adults with SPIMD through a review of medical records and care plans.METHOD: We conducted a cross-sectional study employing data obtained from medical and support records. A sample of adults with SPIMD was recruited in eight residential care settings. Physical health problems that had occurred during the previous 12 months or were chronic were recorded.RESULTS: The records of 99 participants were included. A wide range of physical health problems were found with a mean of 12 problems per person. Very high prevalence rates (>50%) were found for constipation, visual impairment, epilepsy, spasticity, deformations, incontinence and reflux.CONCLUSIONS: The results suggest that people with SPIMD simultaneously experience numerous, serious physical health problems. The reliance on reported problems may cause an underestimation of the prevalence of health problems with less visible signs and symptoms such as osteoporosis and thyroid dysfunction.
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OBJECTIVE: The increasing prevalence of diabetes suggests a gap between real world and controlled trial effectiveness of lifestyle interventions, but real-world investigations are rare. Electronic medical registration facilitates research on real-world effectiveness, although such investigations may require specific methodology and statistics. We investigated the effects of real-world primary care for patients with type 2 diabetes mellitus (T2DM). STUDY DESIGN AND SETTING: We used medical records of patients (n=2,549) with T2DM from 10 primary health care centers. A mixed-effects regression model for repeated measurements was used to evaluate the changes in weight and Hemoglobin A1c (HbA1c) over time. RESULTS: There was no statistically significant change in weight (+0.07 kg, P=0.832) and HbA1c (+0.03%, P=0.657) during the observation period of 972 days. Most patients maintained their physical activity level (70%), and 54 % had an insufficient activity level. The variability in the course of weight and HbA1c was because of differences between patients and not between health care providers. CONCLUSION: Despite effective lifestyle interventions in controlled trial settings, we found that real-world primary care is only able to stabilize weight and HbA1c in patients with T2DM over time. Medical registration can be used to monitor the actual effectiveness of interventions in primary care.
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The Junior Adverse Drug Event Manager (J-ADEM) team is a multifaceted intervention focusing on real-life education for medical students that has been shown to assist healthcare professionals in managing and reporting suspected adverse drug reactions (ADRs) to the Netherlands Pharmacovigilance Centre Lareb. The aim of this study was to quantify and describe the ADRs reported by the J-ADEM team and to determine the clinical potential of this approach. The J-ADEM team consisted of medical students tasked with managing and reporting ADRs in hospitalized patients. All ADRs screened and reported by J-ADEM team were recorded anonymously, and categorized and analysed descriptively. From August 2018 through January 2020, 209 patients on two wards in an academic hospital were screened for ADR events. The J-ADEM team reported 101 ADRs. Although most ADRs (67%) were first identified by healthcare professionals and then reported by the J-ADEM team, the team also reported an additional 33 not previously identified serious ADRs. In 10% of all reported ADRs, the J-ADEM team helped optimize ADR treatment. The ADR reports were largely well-documented (78%), and ADRs were classified as type A (66%), had a moderate or severe severity (85%) and were predominantly avoidable reactions (69%). This study shows that medical students are able to screen patients for ADRs, can identify previously undetected ADRs and can help optimize ADR management. They significantly increased (by 300%) the number of ADR reports submitted, showing that the J-ADEM team can make a valuable clinical contribution to hospital care.
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The modern economy is largely data-driven and relies on the processing and sharing of data across organizations as a key contributor to its success. At the same time, the value, amount, and sensitivity of processed data is steadily increasing, making it a major target of cyber-attacks. A large fraction of the many reported data breaches happened in the healthcare sector, mostly affecting privacy-sensitive data such as medical records and other patient data. This puts data security technologies as a priority item on the agenda of many healthcare organizations, such as of the Dutch health insurance company Centraal Ziekenfonds (CZ). In particular when it comes to sharing data securely, practical data protection technologies are lacking as they mostly focus on securing the link between two organizations while being completely oblivious of what is happening with the data after sharing. For CZ, searchable encryption (SE) technologies that allow to share data in encrypted form, while enabling the private search on this encrypted data without the need to decrypt, are of particular interest. Unfortunately, existing efficient SE schemes completely leak the access pattern (= pattern of encrypted search results, e.g. identifiers of retrieved items) and the search pattern (= pattern of search queries, e.g. frequency of same queries), making them susceptible to leakage-abuse attacks that exploit this leakage to recover what has been queried for and/or (parts of) the shared data itself. The SHARE project will investigate ways to reduce the leakage in searchable encryption in order to mitigate the impact of leakage-abuse attacks while keeping the performance-level high enough for practical use. Concretely, we propose the construction of SE schemes that allow the leakage to be modeled as a statistic released on the queries and shared dataset in terms of ε-differential privacy, a well-established notion that informally says that, after observing the statistic, you learn approximately (determined by the ε-parameter) the same amount of information about an individual data item or query as if the item was not present in the dataset or the query has not been performed. Naturally, such an approach will produce false positives and negatives in the querying process, affecting the scheme’s performance. By calibrating the ε-parameter, we can achieve various leakage-performance trade-offs tailored to the needs of specific applications. SHARE will explore the idea of differentially-private leakage on different parts of SE with different search capabilities, starting with exact-keyword-match SE schemes with differentially-private leakage on the access pattern only, up to schemes with differentially-private leakage on the access and search pattern as well as on the shared dataset itself, allowing for more expressive query types like fuzzy match, range, or substring queries. SHARE comes with an attack lab in which we investigate existing and new types of leakage-abuse attacks to assess the mitigation-potential of our proposed combination of differential privacy with cryptographic guarantees in searchable encryption. To stimulate commercial exploitation of SHARE-results, our consortium partners CZ and TNO will take the lead on applying and evaluating our envisioned technologies in various healthcare use-cases.
The goal of UPIN is to develop and evaluate a scalable distributed system that enables users to cryptographically verify and easily control the paths through which their data travels through an inter-domain network like the Internet, both in terms of router-to-router hops as well as in terms of router attributes (e.g., their location, operator, security level, and manufacturer). UPIN will thus provide the solution to a very relevant and current problem, namely that it is becoming increasingly opaque for users on the Internet who processes their data (e.g., in terms of service providers their data passes through as well as what jurisdictions apply) and that they have no control over how it is being routed. This is a risk for people’s privacy (e.g., a malicious network compromising a user’s data) as well as for their safety (e.g., an untrusted network disrupting a remote surgery). Motivating examples in which (sensitive) user data typically travels across the Internet without user awareness or control are: - Internet of Things for consumers: sensors such as sleep trackers and light switches that collect information about a user’s physical environment and send it across the Internet to remote services for analysis. - Medical records: health care providers requiring medical information (e.g., health records of patients or remote surgery telemetry) to travel between medical institutions according to specified agreements. - Intelligent transport systems: communication plays a crucial role in future autonomous transportation systems, for instance to avoid freight drones colliding or to ensure smooth passing of trucks through busy urban areas. The UPIN project is novel in three ways: 1. UPIN gives users the ability to control and verify the path that their data takes through the network all the way to the destination endpoint, both in terms of hops and attributes of routers traversed. UPIN accomplishes this by adding and improving remote attestation techniques for on-path routers to existing path verification mechanisms, and by adopting and further developing in-packet path selection directives for control. 2. We develop and simulate data and control plane protocols and router extensions to include the UPIN system in inter-domain networking systems such as IP (e.g., using BGP and segment routing) and emerging systems such as SCION and RINA. 3. We evaluate the scalability and performance of the UPIN system using a multi-site testbed of open programmable P4 routers, which is necessary because UPIN requires novel packet processing functions in the data plane. We validate the system using the earlier motivating examples as use cases. The impact we target is: - Increased trust from users (individuals and organizations) in network services because they are able to verify how their data travels through the network to the destination endpoint and because the UPIN APIs enable novel applications that use these network functions. - More empowered users because they are able to control how their data travels through inter-domain networks, which increases self-determination, both at the level of individual users as well as at the societal level.
