Tagless indoor positioning and object tracking using a wireless sensor network

This project seeks to implement a passive indoor positioning and tracking platform using Wi-Fi signals. It is well known that RF wave can be blocked by an object which results in signal attenuation [1 - 2]. The principle of this proposal is based on this phenomenon when the line-of-sight (LOS) link is blocked by an object. Hence, when a grid of such LOS links is tresspassed, it can be detected and tracked within the region

Tagless indoor positioning and object tracking using a wireless sensor network

This project seeks to implement a passive indoor positioning and tracking platform using Wi-Fi signals. It is well known that RF wave can be blocked by an object which results in signal attenuation [1 - 2]. The principle of this proposal is based on this phenomenon when the line-of-sight (LOS) link is blocked by an object. Hence, when a grid of such LOS links is tresspassed, it can be detected and tracked within the region

Identifying risk factors for healthcare-associated infections from electronic medical record home address data

<p>Abstract</p> <p>Background</p> <p>Residential address is a common element in patient electronic medical records. Guidelines from the U.S. Centers for Disease Control and Prevention specify that residence in a nursing home, skilled nursing facility, or hospice within a year prior to a positive culture date is among the criteria for differentiating healthcare-acquired from community-acquired methicillin-resistant <it>Staphylococcus aureus </it>(MRSA) infections. Residential addresses may be useful for identifying patients residing in healthcare-associated settings, but methods for categorizing residence type based on electronic medical records have not been widely documented. The aim of this study was to develop a process to assist in differentiating healthcare-associated from community-associated MRSA infections by analyzing patient addresses to determine if residence reported at the time of positive culture was associated with a healthcare facility or other institutional location.</p> <p>Results</p> <p>We identified 1,232 of the patients (8.24% of the sample) with positive cultures as probable cases of healthcare-associated MRSA based on residential addresses contained in electronic medical records. Combining manual review with linking to institutional address databases improved geocoding rates from 11,870 records (79.37%) to 12,549 records (83.91%). Standardization of patient home address through geocoding increased the number of matches to institutional facilities from 545 (3.64%) to 1,379 (9.22%).</p> <p>Conclusions</p> <p>Linking patient home address data from electronic medical records to institutional residential databases provides useful information for epidemiologic researchers, infection control practitioners, and clinicians. This information, coupled with other clinical and laboratory data, can be used to inform differentiation of healthcare-acquired from community-acquired infections. The process presented should be extensible with little or no added data costs.</p

Multihospital Infection Prevention Collaborative: Informatics Challenges and Strategies to Prevent MRSA

We formed a collaborative to spread effective MRSA prevention strategies. We conducted a two-phase, multisite, quasi-experimental study of seven hospital systems (11 hospitals) in IN, MT, ME and Ontario, Canada over six years. Patients with prior MRSA were identified at admission using regional health information exchange data. We developed a system to return an alert message indicating a prior history of MRSA, directed to infection preventionists and admissions. Alerts indicated the prior anatomic site, and the originating institution. The combined approach of training and coaching, implementation of MRSA registries, notifying hospitals on admission of previously infected or colonized patients, and change strategies was effective in reducing MRSA infections over 80%. Further research and development of electronic surveillance tools is needed to better integrate the varied data source and support preventing MRSA infections. Our study supports the importance of hospitals collaborating to share data and implement effective strategies to prevent MRSA

Consenting to health record linkage: evidence from a multi-purpose longitudinal survey of a general population

Background: The British Household Panel Survey (BHPS) is the first long-running UK longitudinal survey with a non-medical focus and a sample covering the whole age range to have asked for permission to link to a range of administrative health records. This study determines whether informed consent led to selection bias and reflects on the value of the BHPS linked with health records for epidemiological research. Methods. Multivariate logistical regression is used, with whether the respondent gave consent to data linkage or not as the dependent variable. Independent variables were entered as four blocks; (i) a set of standard demographics likely to be found in most health registration data, (ii) a broader set of socio-economic characteristics, (iii) a set of indicators of health conditions and (iv) information about the use of health services. Results: Participants aged 16-24, males and those living in England were more likely to consent. Consent is not biased with respect to socio-economic characteristics or health. Recent users of GP services are underrepresented among consenters. Conclusions: Whilst data could only be linked for a minority of BHPS participants, the BHPS offers a great range of information on people's life histories, their attitudes and behaviours making it an invaluable source for epidemiological research. © 2012 Knies et al; licensee BioMed Central Ltd

A regional informatics platform for coordinated antibiotic resistant infection tracking, alerting and prevention

Background. We developed and assessed the impact of a patient registry and electronic admission notification system relating to regional antimicrobial resistance (AMR) on regional AMR infection rates over time. We conducted an observational cohort study of all patients identified as infected or colonized with methicillin-resistant Staphylococcus aureus (MRSA) and/or vancomycin-resistant enterococci (VRE) on at least 1 occasion by any of 5 healthcare systems between 2003 and 2010. The 5 healthcare systems included 17 hospitals and associated clinics in the Indianapolis, Indiana, region. Methods. We developed and standardized a registry of MRSA and VRE patients and created Web forms that infection preventionists (IPs) used to maintain the lists. We sent e-mail alerts to IPs whenever a patient previously infected or colonized with MRSA or VRE registered for admission to a study hospital from June 2007 through June 2010. Results. Over a 3-year period, we delivered 12 748 e-mail alerts on 6270 unique patients to 24 IPs covering 17 hospitals. One in 5 (22%–23%) of all admission alerts was based on data from a healthcare system that was different from the admitting hospital; a few hospitals accounted for most of this crossover among facilities and systems. Conclusions. Regional patient registries identify an important patient cohort with relevant prior antibiotic-resistant infection data from different healthcare institutions. Regional registries can identify trends and interinstitutional movement not otherwise apparent from single institution data. Importantly, electronic alerts can notify of the need to isolate early and to institute other measures to prevent transmission

Design patterns for the development of electronic health record-driven phenotype extraction algorithms

AbstractBackgroundDesign patterns, in the context of software development and ontologies, provide generalized approaches and guidance to solving commonly occurring problems, or addressing common situations typically informed by intuition, heuristics and experience. While the biomedical literature contains broad coverage of specific phenotype algorithm implementations, no work to date has attempted to generalize common approaches into design patterns, which may then be distributed to the informatics community to efficiently develop more accurate phenotype algorithms.MethodsUsing phenotyping algorithms stored in the Phenotype KnowledgeBase (PheKB), we conducted an independent iterative review to identify recurrent elements within the algorithm definitions. We extracted and generalized recurrent elements in these algorithms into candidate patterns. The authors then assessed the candidate patterns for validity by group consensus, and annotated them with attributes.ResultsA total of 24 electronic Medical Records and Genomics (eMERGE) phenotypes available in PheKB as of 1/25/2013 were downloaded and reviewed. From these, a total of 21 phenotyping patterns were identified, which are available as an online data supplement.ConclusionsRepeatable patterns within phenotyping algorithms exist, and when codified and cataloged may help to educate both experienced and novice algorithm developers. The dissemination and application of these patterns has the potential to decrease the time to develop algorithms, while improving portability and accuracy

Full Reference Image Quality Metrics and their Performance

This paper mainly aims to study the performance of objective assessment methods of image quality. It take into consideration the correlations between each objective assessment and the subjective assessment in order to determine objective test performance. Three objective assessment methods used in this study are the Structural Similarity (SSIM) index, the Peak Signal-to-Noise Ratio (PSNR) and the Mean Squared Error (MSE) calculating algorithm. The resulting data indicate what type of objective assessment was most suitable for which type of impairment imposed upon an image. This is clarified using the Pearson Correlation Coefficient as described in the paper. As an overall, SSIM index had the best correlation characteristics to the subjective assessment, followed by the MSE calculating algorithm. From this study, a better understanding of the requirements for developing an efficient image quality assessment method was gained