The scalability and the strategy for EMR database encryption techniques

EMR (Electronic Medical Record) is an emerging technology that is highly-blended between non-IT and IT area. One methodology is to link the non-IT and IT area is to construct databases. Nowadays, it supports before and after-treatment for patients and should satisfy all stakeholders such as practitioners, nurses, researchers, administrators and financial departments and so on. In accordance with the database maintenance, DAS (Data as Service) model is one solution for outsourcing. However, there are some scalability and strategy issues when we need to plan to use DAS model properly. We constructed three kinds of databases such as plan-text, MS built-in encryption which is in-house model and custom AES (Advanced Encryption Standard) - DAS model scaling from 5K to 2560K records. To perform custom AES-DAS better, we also devised Bucket Index using Bloom Filter. The simulation showed the response times arithmetically increased in the beginning but after a certain threshold, exponentially increased in the end. In conclusion, if the database model is close to in-house model, then vendor technology is a good way to perform and get query response times in a consistent manner. If the model is DAS model, it is easy to outsource the database, however, some techniques like Bucket Index enhances its utilization. To get faster query response times, designing database such as consideration of the field type is also important. This study suggests cloud computing would be a next DAS model to satisfy the scalability and the security issues.

Development of an EMR implementation framework for public hospitals in Saudi Arabia

An Electronic Medical Record (EMR) is a system that has been embraced by healthcare providers worldwide. However, the implementation success of EMRs has varied widely. Studies have identified both barriers to and facilitators for implementing EMRs within healthcare organisations. In Saudi Arabia (SA), the majority of healthcare providers manage patient records manually. As public hospitals are a major provider of health services in SA and have been shown to face more EMR implementation barriers than private hospitals, there is a need for an implementation framework to guide EMR implementation in Saudi public hospitals. This doctoral project therefore aimed to develop an evidence-based EMR implementation framework for public hospitals in SA informed by those who work at the micro-implementation level and the macro-implementation level and the extant literature sensitive to the cultural, resource-related, and technological, organisational, and environmental issues of SA.

Production of niobium powder by electronically mediated reaction (EMR) using calcium as a reductant

Explored in this study is an electronically mediated reaction (EMR) route for the production of niobium powder using calcium as a reductant for niobium oxide (Nb2O5). Feed material, Nb2O5, and reductant calcium alloy containing aluminum and nickel were charged into electronically isolated locations in a molten salt (e.g. CaCl2) at 1173 K. The current flow through an external path between the feed and reductant locations was monitored. A current approximately 0.4 A was measured during the reaction in the external circuit connecting cathode and anode location. Niobium powder with low aluminum and nickel content was obtained although liquid Ca–Al–Ni alloy was used as the reductant. This clearly demonstrates that niobium metal powder can be produced by an electronically mediated reaction (EMR), without direct physical contact between feed (Nb2O5) and reductant (calcium). Mechanism of calciothermic reduction of Nb2O5 in the molten salt is discussed using an isothermal chemical potential diagram.

Effect of Size Reduction on Magnetic Ordering in Sm1-x Ca (x) MnO3 (x=0.35, 0.65 and 0.92) Manganites: Magnetic and EMR Studies

We have employed the highly sensitive electron magnetic resonance technique complimented by magnetization measurements to study the impact of size reduction on the magnetic ordering in nanosized Sm1-x Ca (x) MnO3 (x = 0.35, 0.65 and 0.92). In the bulk form, x = 0.35 sample shows a charge ordering transition at 235 K followed by a mixed magnetic phase, the sample with x = 0.65 exhibits charge order below 275 K and shows an antiferromagnetic insulator phase below 135 K while that with x = 0.92 has a ferromagnetic-cluster glass ground state. Thus, a comparative study of magnetic ground states of bulk and nanoparticles (diameter similar to 25 nm) enables us to investigate size-induced effects on different types of magnetic ordering. It is seen that in the bulk samples the temperature dependences of the EPR parameters are quite different from each other. This difference diminishes for the nanosamples where all the three samples show qualitatively similar behavior. The magnetization measurements corroborate this conclusion.

Learning vector representation of medical objects via EMR-driven nonnegative restricted Boltzmann machines (eNRBM)

Electronic medical record (EMR) offers promises for novel analytics. However, manual feature engineering from EMR is labor intensive because EMR is complex - it contains temporal, mixed-type and multimodal data packed in irregular episodes. We present a computational framework to harness EMR with minimal human supervision via restricted Boltzmann machine (RBM). The framework derives a new representation of medical objects by embedding them in a low-dimensional vector space. This new representation facilitates algebraic and statistical manipulations such as projection onto 2D plane (thereby offering intuitive visualization), object grouping (hence enabling automated phenotyping), and risk stratification. To enhance model interpretability, we introduced two constraints into model parameters: (a) nonnegative coefficients, and (b) structural smoothness. These result in a novel model called eNRBM (EMR-driven nonnegative RBM). We demonstrate the capability of the eNRBM on a cohort of 7578 mental health patients under suicide risk assessment. The derived representation not only shows clinically meaningful feature grouping but also facilitates short-term risk stratification. The F-scores, 0.21 for moderate-risk and 0.36 for high-risk, are significantly higher than those obtained by clinicians and competitive with the results obtained by support vector machines.

Ensino médio em rede (EMR): reflexões de uma professora sobre a formação continuada de professores

Pós-graduação em Educação - IBRC

Ôr le-ʿēt ʿerev : le-hā'îr ʿênê Yiśrā'ēl we-yir'û bi-neḥāmôt Ṣiyyôn ... li-šemôr et kōl miṣwôtāw ... ; dos lichṭ kign abnd tzaiṭ ...

baʿal ham-meḥabbēr ... Yôḥānān Qimḥî

Dynamic field measurements with an EMR magnetometer in the pulsed beam switching magnet /

"AEC Contract AT(04-3)-400."

EMR Interaction with Water

Resources created at the University of Southampton for the module Remote Sensing for Earth Observation

EMR Interaction with Water

Resources created at the University of Southampton for the module Remote Sensing for Earth Observation

A time-variant medical data trustworthiness assessment model

Electronic Health Record (EHR) systems are being introduced to overcome the limitations associated with paper-based and isolated Electronic Medical Record (EMR) systems. This is accomplished by aggregating medical data and consolidating them in one digital repository. Though an EHR system provides obvious functional benefits, there is a growing concern about the privacy and reliability (trustworthiness) of Electronic Health Records. Security requirements such as confidentiality, integrity, and availability can be satisfied by traditional hard security mechanisms. However, measuring data trustworthiness from the perspective of data entry is an issue that cannot be solved with traditional mechanisms, especially since degrees of trust change over time. In this paper, we introduce a Time-variant Medical Data Trustworthiness (TMDT) assessment model to evaluate the trustworthiness of medical data by evaluating the trustworthiness of its sources, namely the healthcare organisation where the data was created and the medical practitioner who diagnosed the patient and authorised entry of this data into the patient’s medical record, with respect to a certain period of time. The result can then be used by the EHR system to manipulate health record metadata to alert medical practitioners relying on the information to possible reliability problems.

Sharing with care : an information accountability perspective

Health information sharing has become a vital part of modern healthcare delivery. E-health technologies provide efficient and effective ways of sharing medical information, but give rise to issues that neither the medical professional nor the consumers have control over. Information security and patient privacy are key impediments that hinder sharing information as sensitive as health information. Health information interoperability is another issue which hinders the adoption of available e health technologies. In this paper we propose a solution for these problems in terms of information accountability, the HL7 interoperability standard and social networks for manipulating personal health records.

Improving trust and securing data accessibility for e-health decision making by using data encryption techniques

In the medical and healthcare arena, patients‟ data is not just their own personal history but also a valuable large dataset for finding solutions for diseases. While electronic medical records are becoming popular and are used in healthcare work places like hospitals, as well as insurance companies, and by major stakeholders such as physicians and their patients, the accessibility of such information should be dealt with in a way that preserves privacy and security. Thus, finding the best way to keep the data secure has become an important issue in the area of database security. Sensitive medical data should be encrypted in databases. There are many encryption/ decryption techniques and algorithms with regard to preserving privacy and security. Currently their performance is an important factor while the medical data is being managed in databases. Another important factor is that the stakeholders should decide more cost-effective ways to reduce the total cost of ownership. As an alternative, DAS (Data as Service) is a popular outsourcing model to satisfy the cost-effectiveness but it takes a consideration that the encryption/ decryption modules needs to be handled by trustworthy stakeholders. This research project is focusing on the query response times in a DAS model (AES-DAS) and analyses the comparison between the outsourcing model and the in-house model which incorporates Microsoft built-in encryption scheme in a SQL Server. This research project includes building a prototype of medical database schemas. There are 2 types of simulations to carry out the project. The first stage includes 6 databases in order to carry out simulations to measure the performance between plain-text, Microsoft built-in encryption and AES-DAS (Data as Service). Particularly, the AES-DAS incorporates implementations of symmetric key encryption such as AES (Advanced Encryption Standard) and a Bucket indexing processor using Bloom filter. The results are categorised such as character type, numeric type, range queries, range queries using Bucket Index and aggregate queries. The second stage takes the scalability test from 5K to 2560K records. The main result of these simulations is that particularly as an outsourcing model, AES-DAS using the Bucket index shows around 3.32 times faster than a normal AES-DAS under the 70 partitions and 10K record-sized databases. Retrieving Numeric typed data takes shorter time than Character typed data in AES-DAS. The aggregation query response time in AES-DAS is not as consistent as that in MS built-in encryption scheme. The scalability test shows that the DBMS reaches in a certain threshold; the query response time becomes rapidly slower. However, there is more to investigate in order to bring about other outcomes and to construct a secured EMR (Electronic Medical Record) more efficiently from these simulations.

Brownfield re-development : Perceptions and risk mitigation strategies

Scarcity of large parcels of land in well-serviced areas has motivated people to re-develop brownfield land. Most of brownfield land has high risk of contamination from wide range of industrial activities such as gas works, factories, railway land and waste tips. In addition, people who live in brownfield re-development areas may be exposed to health hazards. This paper discusses public perceptions on the brownfield sites and also the risk and mitigation strategy to promote brownfield re-development. Data is gathered from face to face survey of fifty respondents who work in Brisbane Central Business District (CBD) and interview with an expert on remediation of contaminated land. From this preliminary study, it is found that majority of the population are not aware of any brownfield sites near their residence and those who are aware showed very little concern on their proximity to the site. Further discussion on the paper based on a simple cross tabulation analysis. The main risk mitigation strategy of re-development of brownfield site is by updating the registration through Environmental Management Register (EMR) and Contaminated Land Register (CLR). In addition, insurance may offer to cover cost overruns on remediation cost.