Global ETD Search

61	ADOPTION AND USAGE OF ELECTRONIC MEDICAL RECORDS IN CANADIAN FAMILY PRACTICE: ARE SMALL PRACTICES AT A DISADVANTAGE? Chaudhury, Rafi A. 10 1900 (has links) <p>Canadian primary care practices lag behind their counterparts in the United States and Europe in adopting Electronic Medical Record (EMR) systems to facilitate care. Although there is a considerable volume of cross-national conceptual literature focused on system design and barriers to adoption, there is little in the way of research on the unique problems faced by Canadian physicians within the publicly financed and privately provided system of healthcare delivery. This study uses a survey of Canadian physicians to investigate differences in perceptions of EMR value between two groups who have implemented these systems: “small practice” physicians, i.e. those with a maximum of 2 full-time physicians and “large practice” physicians, or those with three or more full-time physicians. A Mann-Whitney U Test conducted on survey item responses of the two groups finds that “small practice” physicians feel significantly less positive about EMRs with regards to ease of use, time savings and effective patient management.</p> / Master of Science (MSc) EMR Electronic Medical Records Primary Care Family Physician Small Practice Community Health and Preventive Medicine Databases and Information Systems Health and Medical Administration Health Policy Health Services Administration Community Health and Preventive Medicine
62	Discovering Implant Terms in Medical Records Jerdhaf, Oskar January 2021 (has links) Implant terms are terms like "pacemaker" which indicate the presence of artifacts in the body of a human. These implant terms are key to determining if a patient can safely undergo Magnetic Resonance Imaging (MRI). However, to identify these terms in medical records is time-consuming, laborious and expensive, but necessary for taking the correct precautions before an MRI scan. Automating this process is of great interest to radiologists as it ideally saves time, prevents mistakes and as a result saves lives. The electronic medical records (EMR) contain the documented medical history of a patient, including any implants or objects that an individual would have inside their body. Information about such objects and implants are of great interest when determining if and how a patient can be scanned using MRI. This information is unfortunately not easily extracted through automatic means. Due to their sparse presence and the unusual structure of medical records compared to most written text, makes it very difficult to automate using simple means. By leveraging the recent advancements in Artificial Intelligence (AI), this thesis explores the ability to identify and extract such terms automatically in Swedish EMRs. For the task of identifying implant terms in medical records a generally trained Swedish Bidirectional Encoder Representations from Transformers (BERT) model is used, which is then fine-tuned on Swedish medical records. Using this model a variety of approaches are explored two of which will be covered in this thesis. Using this model a variety of approaches are explored, namely BERT-KDTree, BERT-BallTree, Cosine Brute Force and unsupervised NER. The results show that BERT-KDTree and BERT-BallTree are the most rewarding methods. Results from both methods have been evaluated by domain experts and appear promising for such an early stage, given the difficulty of the task. The evaluation of BERT-BallTree shows that multiple methods of extraction may be preferable as they provide different but still useful terms. Cosine brute force is deemed to be an unrealistic approach due to computational and memory requirements. The NER approach was deemed too impractical and laborious to justify for this study, yet is potentially useful if not more suitable given a different set of conditions and goals. While there is much to be explored and improved, these experiments are a clear indication that automatic identification of implant terms is possible, as a large number of implant terms were successfully discovered using automated means. AI Machine Learning Medical Records Patient Records Medical Record Electronic Records Electronic Medical Records BERT EMR Implant Terms Implants Term Terms Term Discovery Artificial Intelligence Word Similarity Word Similarity word-similarity embeddings word embeddings word-embeddings transformers KDTREE BALLTREE NER AI Artificiel Intelligens Maskininlärning Patient Journal Medicinsk Journal Elektronisk Medicinsk Journal Termer BERT KDTREE BALLTREE NER liknande ord transformers EMR
63	Prescribing cotrimoxazole prophylactic therapy (CPT) before and after an electronic medical record system implementation in two selected hospitals in Malawi Gadabu, Oliver Jintha 11 1900 (has links) Opportunistic infections (OIs) have been identified as a leading cause of poor outcomes in the ARV therapy (ART) programme. In order to reduce OIs, the Malawi, MoH introduced routine prescription of cotrimoxazole preventive therapy (CPT) in 2005. The MoH also started scaling up a point-of-care electronic medical record (EMR) system in 2007 to improve monitoring and evaluation. This study had the following objectives: i) to quantify prescription of CPT before and after implementing EMR; ii) to compare the difference in CPT prescription before and after implementing EMR. A historically controlled study design was used to compare CPT prescriptions one year before, and one year after implementation of the EMR at two health facilities. The data indicated that there was a significant (P <0.001) decrease in CPT prescribing at one health facility and a significant increase in CPT prescription at another. / Health Studies / M.A. (Public Health) Point-of-care EMR Clinical practice guidelines Cotrimoxazole prophylactic therapy Clinical decision support Electronic medical record Adherence Opportunistic infections Resource limited setting Clinicians 614.5993920096897 AIDS (Disease) -- Malawi -- Prevention HIV infections -- Malawi -- Prevention
64	Prescribing cotrimoxazole prophylactic therapy (CPT) before and after an electronic medical record system implementation in two selected hospitals in Malawi Gadabu, Oliver Jintha 11 1900 (has links) Opportunistic infections (OIs) have been identified as a leading cause of poor outcomes in the ARV therapy (ART) programme. In order to reduce OIs, the Malawi, MoH introduced routine prescription of cotrimoxazole preventive therapy (CPT) in 2005. The MoH also started scaling up a point-of-care electronic medical record (EMR) system in 2007 to improve monitoring and evaluation. This study had the following objectives: i) to quantify prescription of CPT before and after implementing EMR; ii) to compare the difference in CPT prescription before and after implementing EMR. A historically controlled study design was used to compare CPT prescriptions one year before, and one year after implementation of the EMR at two health facilities. The data indicated that there was a significant (P <0.001) decrease in CPT prescribing at one health facility and a significant increase in CPT prescription at another. / Health Studies / M.A. (Public Health) Point-of-care EMR Clinical practice guidelines Cotrimoxazole prophylactic therapy Clinical decision support Electronic medical record Adherence Opportunistic infections Resource limited setting Clinicians Processes 614.5993920096897 AIDS (Disease) -- Malawi -- Prevention HIV infections -- Malawi -- Prevention
65	Emergency physician documentation quality and cognitive load : comparison of paper charts to electronic physician documentation Chisholm, Robin Lynn January 2014 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / Reducing medical error remains in the forefront of healthcare reform. The use of health information technology, specifically the electronic health record (EHR) is one attempt to improve patient safety. The implementation of the EHR in the Emergency Department changes physician workflow, which can have negative, unintended consequences for patient safety. Inaccuracies in clinical documentation can contribute, for example, to medical error during transitions of care. In this quasi-experimental comparison study, we sought to determine whether there is a difference in document quality, error rate, error type, cognitive load and time when Emergency Medicine (EM) residents use paper charts versus the EHR to complete physician documentation of clinical encounters. Simulated patient encounters provided a unique and innovative environment to evaluate EM physician documentation. Analysis focused on examining documentation quality and real-time observation of the simulated encounter. Results demonstrate no change in document quality, no change in cognitive load, and no change in error rate between electronic and paper charts. There was a 46% increase in the time required to complete the charting task when using the EHR. Physician workflow changes from partial documentation during the patient encounter with paper charts to complete documentation after the encounter with electronic charts. Documentation quality overall was poor with an average of 36% of required elements missing which did not improve during residency training. The extra time required for the charting task using the EHR potentially increases patient waiting times as well as clinician dissatisfaction and burnout, yet it has little impact on the quality of physician documentation. Better strategies and support for documentation are needed as providers adopt and use EHR systems to change the practice of medicine. Medical records -- Access control Electronic records -- Access control Emergency medical services Emergency physicians Medical informatics -- Standards Medicine -- Documentation Medical records -- Management Human information processing -- Research Medical errors -- Reporting Communication in medicine
66	Indianapolis Emergency Medical Service and the Indiana Network for Patient Care: Evaluating the Patient Match Process Park, Seong Cheol 03 January 2014 (has links) Indiana University-Purdue University Indianapolis (IUPUI) / In 2009, Indianapolis Emergency Medical Service (I-EMS, formerly Wishard Ambulance Service) launched an electronic medical record system within their ambulances and started to exchange patient data with the Indiana Network for Patient Care (INPC). This unique system allows EMS personnel in an ambulance to get important medical information prior to the patient’s arrival to the accepting hospital from incident scene. In this retrospective cohort study, we found EMS personnel made 3,021 patient data requests (14%) of 21,215 EMS transports during a one-year period, with a “success” match rate of 46%, and a match “failure” rate of 17%. The three major factors for causing match “failure” were (1) ZIP code 55%, (2) Patient Name 22%, and (3) Birth Date 12%. This study shows that the ZIP code is not a robust identifier in the patient identification process and Non-ZIP code identifiers may be a better choice due to inaccuracies and changes of the ZIP code in a patient’s record. EMS Match Identifier INPC Ambulance Medical Record EMR Exchange Indiana Network for Patient Care Knowledge management -- Research Computer algorithms -- Research

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