Suchergebnisse

The linkage of Electronic Medical Records, Administrative and other data sources is highly valuable for research and health system monitoring. Once linked, combined resources can be analyzed to provide the answers to a variety of health questions that otherwise could not be answered. However, legislative and administrative barriers, including lengthy processes for data sharing agreements, may preclude timely linkage which is a key requirement during pandemics.
ObjectiveTo develop a method using a patient's health trajectory to probabilistically link primary care Electronic Medical Record (EMR) data with administrative and other data, without the need to transfer large datasets or identifiable information. To determine the legislative feasibility, accuracy and validity of this linkage process.
Study DesignIdentify data strings that do not directly identify patients and could be used as unique linkage variables. The data strings, which we are calling dataprints, are sufficiently similar over time in different databases. One example in Ontario, Canada, is the pattern of submitted health claims. For every patient seen by a family physician, there exists a unique pattern of dates/billing codes/diagnoses over time. These unique patterns are reasonably similar in EMR and administrative datasets. We will apply an algorithm which turns the string in the selected dataprints to an irreversibly hashed code for each person. The hashed code and no additional information will be provided by both data controllers to a trusted-third party who will determine which records match and send a mapping table to both. This enables analyses to be run in parallel, without divulging any direct person identifiers.
DatasetIndividuals contained in the University of Toronto Practice Based Research Network (UTOPIAN).
Outcome MeasuresLinkage quality will be assessed by the number of true matches and represented by sensitivity, specificity and positive and negative predictive values.
ResultsThe method will be evaluated against a validated, deterministically linked reference standard at North York General Hospital using de-identified EMR and hospital data. Results will inform processes to enable analyses across datasets while adhering to privacy legislation.

Limited classroom instruction time is a binding constraint for professors teaching economics. Time requirements necessary to learn economics also impose similar constraints on students. The topic of this paper is the presentation of an environment that can both increase the economic content delivered during classroom instruction and increase the potential for students' learning economics outside the classroom. The methodology is two fold: HyperLecturing, a classroom presentation style where computer resources serve as instructional aides; and Linkages, an emphasis on interdisciplinary connections to other course material in a student's repertoire. The specific setting in this paper is Intermediate Macroeconomic Theory, but the methodology generalizes to any course in economics.

Nomination: Costs and benefits of party membership reconsidered by Wolfgang C. Müller, p.169 Reflections: Party as linkage by Richard S. Katz, p171

IntroductionPrivacy preserving record linkage (PPRL) resolves privacy concerns because of its capabilities to link encrypted identifiers. It encrypts identifiers using bloom filters and performs record matching based on encrypted data using dice coefficient similarity. Matching data based on hashed identifiers impacts the performance of linkage due to loss of information.
Objectives and ApproachWe propose a technique to optimize the bloom filter parameters and examine if the optimal parameters increase the performance of the linkage in terms of precision, recall, and f-measure. Let us consider a set of string values and calculate the similarity between any two of them using the Jaro-Winkler method. Now let us encrypt the string values using bloom filters and calculate the similarity between any two of them using the dice coefficient technique. Optimal parameters of bloom filters are those that minimize the difference between the calculated similarities using Jaro-Winkler vs. the calculated similarities using the dice coefficient technique.
ResultsUsing publically available data, several first name and last name datasets each comprising 1000 unique values were generated. The following values for bloom filter parameters were considered: q in q-grams (q=1,2,3), bit array length (l=50,100,200,500,1000), number of hash functions (k=5,10,20,50). The following five setups of bloom filters were able to minimize the difference between the calculated similarities on encrypted data using the dice coefficient technique, and the calculated similarities on unencrypted data using the Jaro-Winkler method: q=1,l=1000,k=50/q=1,l=500,k=20/ q=2,l=1000,k=50/ q=3,l=500,k=50. These setups were considered to perform data linkage over 10 synthetically-generated datasets. Results show that PPRL was able to achieve similar performance compared to data linkage over unencrypted data.
Conclusion/ImplicationsThis study showed that optimal parameters of bloom filters minimized loss of information resulting from data encryption. Experimental findings indicated that PPRL using optimal parameters of bloom filters achieves almost the same performance as data linkage on unencrypted data in terms of precision, recall, and f-measure.

Disaster management has historically focused on reactive approaches, but a shift to proactive approaches is crucial for addressing concerns raised by the changing environment. A prime reason for the absence of proactive approaches in disaster/hazard management is the uncertainty or ambiguity present in the links between the environment and the hazards. This is the first book to focus on explicit linkages between the changing environment and disasters and suggests better approaches towards disaster management. A ready-reference for field practitioners it combines academic research and field practices and covers areas such as: elements of environmental entry (water-related disasters, desertification and land degradation, typhoon risk management, catastrophic flood and forest management, and coastal issues); impacts of environment and disaster (livelihoods impacts, human health: post-disaster waste management); and strategies, planning and the way forward (climate change adaptation as a planning tool, urban planning and land use planning, mangrove management as a coastal planning tool, and environment disaster education and risk communication).

Disaster management has historically focused on reactive approaches, but a shift to proactive approaches is crucial for addressing concerns raised by the changing environment. A prime reason for the absence of proactive approaches in disaster/hazard management is the uncertainty or ambiguity present in the links between the environment and the hazards. This is the first book to focus on explicit linkages between the changing environment and disasters and suggests better approaches towards disaster management. A ready-reference for field practitioners it combines academic research and field practices and covers areas such as: elements of environmental entry (water-related disasters, desertification and land degradation, typhoon risk management, catastrophic flood and forest management, and coastal issues); impacts of environment and disaster (livelihoods impacts, human health: post-disaster waste management); and strategies, planning and the way forward (climate change adaptation as a planning tool, urban planning and land use planning, mangrove management as a coastal planning tool, and environment disaster education and risk communication).

THREE DIFFERENT FORMS OF LINKAGE ARE DISCUSSED: COERCED LINKAGE, THREAT-INDUCED LINKAGE, AND MUTUAL LINKAGE. AUTHOR NOTES THAT LINKAGE IS A CENTRAL ANALYTIC PROBLEM WITH AN ISSUE APPROACH TO INTERNATIONAL POLITICS.