Matching Items (16)
Description
With the recent rise in opioid overdose and death1<br/><br/>, chronic opioid therapy (COT) programs using<br/>Center of Disease Control (CDC) guidelines have been implemented across the United States8<br/>.<br/>Primary care clinicians at Mayo Clinic initiated a COT program in September of 2017, during the<br/>use of Cerner Electronic Health Record (EHR) system. Study metrics included provider<br/>satisfaction and perceptions regarding opioid prescription. Mayo Clinic transitioned its EHR<br/>system from Cerner to Epic in October 2018. This study aims to understand if provider perceptions<br/>about COT changed after the EHR transition and the reasons underlying those perceptions.
ContributorsPonnapalli, Sravya (Author) / Murcko, Anita (Thesis director) / Wallace, Mark (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Research Objective Social determinants of health (SDOH) are the conditions in one’s living environment that affect health, functioning, and quality of life. Total joint arthroplasty (TJA) is a surgical procedure to replace a damaged joint with an artificial joint. TJA complications include acute myocardial infarction, pneumonia, sepsis, surgical site bleeding, pulmonary embolism, or periprosthetic joint infection. Previous research demonstrates that Black race, Hispanic ethnicity and poverty were negatively associated with TJA outcomes in veterans. The goal of this mixed methods quality improvement study is to determine if SDOHs affect TJA complications at a health system in the Phoenix metropolitan area. Methodology For this study, records from patients who underwent hip or knee TJAs at any of the four system facilities between 2/2019-2/2020 were included. Demographics and clinical data were extracted from the electronic health record (EHR) via Midas+ Care Management with SDOH variables from case manager notes corresponding to food, utilities, housing and transportation insecurities, and interpersonal safety. Complications were identified using ICD-10 codes. SDOH for individuals with and without complications were compared. A multinomial logistic regression was performed in SPSS to identify significant variables. Semi-structured interviews with case managers (n=2), orthopedic surgeons(n=5), and primary care physicians (n=4) were performed to explore care team interactions with SDOH. Interview notes were coded and analyzed based on response frequency and themes. Results Of 2,520 patients who underwent TJA, 50 (1.98%) experienced a TJA complication. Of those, 38% screened positive for an SDOH. For those without a TJA complication, 27% screened positive for an SDOH (p=0.093). Most interview participants identified a correlation between socioeconomic status and surgical outcomes. They also recognized that language barriers for Spanish-speaking individuals and family involvement post-discharge are significant factors in TJA outcomes. Conclusions This single system mixed methods retrospective quality improvement study demonstrates that patients who screen positive for an SDOH are more likely to experience a TJA complication. We recommend that SDOH assessments be obtained for all patients undergoing TJA, be available to care teams, and be incorporated into care plans to improve outcomes.
ContributorsRemmers, Lauryn Madison (Author) / Murcko, Anita (Thesis director) / Radhakrishnan, Priya (Committee member) / Kalpas, Edward (Committee member) / Barrett, The Honors College (Contributor) / College of Health Solutions (Contributor)
Created2021-12
Description
Translating research has been a goal of the Department of Health and Human Services since 1999. Through two years of iteration and interview with our community members, we have collected insights into the barriers to accomplishing this goal. Liberating Science is a think-tank of researchers and scientists who seek to create a more transparent process to accelerate innovation starting with behavioral health research.
ContributorsRaghani, Pooja Sioux (Author) / Hekler, Eric (Thesis director) / Buman, Matthew (Committee member) / Pruthi, Virgilia Kaur (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / Biomedical Informatics Program (Contributor)
Created2014-05
Description
Methane (CH4) is very important in the environment as it is a greenhouse gas and important for the degradation of organic matter. During the last 200 years the atmospheric concentration of CH4 has tripled. Methanogens are methane-producing microbes from the Archaea domain that complete the final step in breaking down organic matter to generate methane through a process called methanogenesis. They contribute to about 74% of the CH4 present on the Earth's atmosphere, producing 1 billion tons of methane annually. The purpose of this work is to generate a preliminary metabolic reconstruction model of two methanogens: Methanoregula boonei 6A8 and Methanosphaerula palustris E1-9c. M. boonei and M. palustris are part of the Methanomicrobiales order and perform hydrogenotrophic methanogenesis, which means that they reduce CO2 to CH4 by using H2 as their major electron donor. Metabolic models are frameworks for understanding a cell as a system and they provide the means to assess the changes in gene regulation in response in various environmental and physiological constraints. The Pathway-Tools software v16 was used to generate these draft models. The models were manually curated using literature searches, the KEGG database and homology methods with the Methanosarcina acetivorans strain, the closest methanogen strain with a nearly complete metabolic reconstruction. These preliminary models attempt to complete the pathways required for amino acid biosynthesis, methanogenesis, and major cofactors related to methanogenesis. The M. boonei reconstruction currently includes 99 pathways and has 82% of its reactions completed, while the M. palustris reconstruction includes 102 pathways and has 89% of its reactions completed.
ContributorsMahendra, Divya (Author) / Cadillo-Quiroz, Hinsby (Thesis director) / Wang, Xuan (Committee member) / Stout, Valerie (Committee member) / Barrett, The Honors College (Contributor) / Computing and Informatics Program (Contributor) / School of Life Sciences (Contributor) / Biomedical Informatics Program (Contributor)
Created2014-05
Description
This study focused on the connection between the EnvZ/OmpR two-component regulatory system and the iron homeostasis system in Escherichia coli, specifically how a mutant form of EnvZ11/OmpR is able to reduce the expression of fepA::lacZ, a reporter gene fusion in E. coli. FepA is one of several outer membrane siderophore receptors that allow extracellular siderophores bound to iron to enter the cells to power various biological processes. Previous studies have shown that in E. coli cells that expressed a mutant allele of envZ, called envZ11, which led to altered expression of various iron genes including down regulation of fepA::lacZ. The wild type EnvZ/OmpR system is not considered to regulate iron genes, but because these envz11 strains had downregulated fepA::lacZ, this study was undertaken to understand the connection and mechanisms of this downregulation. A large number of Lac+ revertants were obtained from the B32-2483 strain (envz11 and fepA::lacZ) and 7 Lac+ revertants that had reversion mutations not directly correcting the envZ11 allele were further characterized. With P1 phage transduction genetic mapping that involved moving a kanamycin resistance marker linked to fepA::lacZ, two Lac+ revertants were found to have their reversion mutations in the fepA promoter region, while the other five revertants had their mutations mapping outside the fepA region. These two revertants underwent DNA sequencing and found to carry two different single base pair mutations in two different locations of the fepA promoter region. Each one is in the Fur repressor binding region, but one also may have affected the Shine-Dalgarno region involved in translation initiation. All 7 reveratants underwent beta-galactosidase assays to measure fepA::lacZ expression. The two revertants that had mutations in the fepA promoter region had significantly increased fepA activity, with the revertant with the Shine-Dalgarno mutation having the most elevated fepA expression. The other 5 revertants that did not map in the fepA region had fepA expression elevated to the same level as that found in the wild type EnvZ/OmpR background. The data suggest that the negative effect of envZ11 can be overcome by multiple mechanisms, including directly correcting the envZ11 allele or changing the fepA promoter region.
ContributorsKalinkin, Victor Arkady (Co-author) / Misra, Rajeev (Co-author, Thesis director) / Mason, Hugh (Committee member) / Foy, Joseph (Committee member) / Biomedical Informatics Program (Contributor) / School of Life Sciences (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Glioblastoma (GBM) is an extremely malignant form of brain cancer characterized by rapid progression and poor patient survival. Even after standard of care treatments, less than ten percent of patients with this disease survive five years. More effective therapeutic options are urgently needed to improve outcomes for patients with GBM. Adequate drug delivery is a critical challenge in GBM treatment, as drugs delivered systemically must be able to penetrate the blood brain barrier (BBB) and reach the tumor at therapeutic levels. To address this, we developed a resource to catalog BBB penetration information for investigational agents currently in clinical trials in cancer. Using an in silico prediction model and manual annotation to capture existing knowledge from the published literature, BBB content for ~500 investigational drugs was added to the investigational database tool. In addition to BBB content, the database also includes information on the gene targets of the included therapies. The investigational database tool was used to identify investigational agents that (1) may have increased activity against GBM based on the presence of a specific mutation in the tumor sample and (2) have evidence suggesting the compounds may penetrate the BBB. By prioritizing investigational agents for further study based on evidence for BBB penetration, this resource can help the GBM research community pursue more effective treatments for GBM.
ContributorsHerring, Emily Lora (Author) / Coursen, Jerry (Thesis director) / Byron, Sara (Committee member) / Biomedical Informatics Program (Contributor) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Concept maps are teaching tools used to encourage students to utilize active learning strategies and to take responsibility for their own learning. The purpose of this two-semester study is to evaluate the use of concept maps in a junior-level Biomaterials classroom. The maps are assessed based on students' attitude, achievement, and persistence. No significant correlation was determined between concept map score and achievement (correlation coefficient = 0.1739 in the first semester, 0.2208 in the first set of the second semester, and 0.0829 in the second set of the second semester), though further studies should be completed to support the effects of concept mapping. Statistically significant increases in student attitude regarding concept mapping cost, interest, and utility between the two semesters were found (p = 0.013, p = 0.105, p = 0.002, p = 0.083 overall). Persistence was moderately high throughout the entire study (98% in the first semester and 100% in the second semester).
ContributorsHolm, Mikayle Ashlyn (Author) / Ankeny, Casey (Thesis director) / Graham, Kaely (Committee member) / Harrington Bioengineering Program (Contributor) / Biomedical Informatics Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Individual control of sensitive health information is a matter of great concern to patients, practitioners, insurers and policymakers. Federal and state law generally supports consent approaches that allow patients to share all or none of their health data. However, research demonstrates that patients prefer more detailed control of their personal data sharing. In particular, little is known about data sharing preferences of patients with behavioral health conditions (BHCs). This study will explore the technical feasibility of supporting patient-driven, consent-based data access through a preliminary analysis of data collected from the My Data Choices e-consent tool. Through these findings, this research seeks to inform stakeholders about the clinical, ethical, policy, and regulatory implications of broader consent choices.
ContributorsKaing, Tina C. (Author) / Grando, Maria Adela (Thesis director) / Murcko, Anita (Committee member) / College of Health Solutions (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-12
Description
Integrating behavioral and physical health is the key to value-based care. Little is known about data sharing preferences and consent practices for individuals with behavioral health conditions. This study focuses on identifying behavioral health provider perceptions about patient data sharing practices, preferences and perceived impact on care resulting from enhanced patient control of record types during consent for data sharing.
ContributorsHiestand, Megan (Author) / Grando, Adela (Thesis director) / Murcko, Anita (Committee member) / Sharp, Richard (Committee member) / Biomedical Informatics Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Background: Pulmonary embolism is a deadly condition that is often diagnosed using a technique known as computed tomography pulmonary angiography (CTPA). CTPA reports are free-text, narrative-style forms of documentation conferring radiologist findings—both primary (regarding pulmonary embolism) and incidental. This project seeks to combine simple natural language processing (NLP) techniques, such as regular expressions and rules, to build upon and
further process output from a machine learning based named entity recognition (NER) tool for the purposes of (1) linking references to radiological images with the corresponding clinical findings and (2) extracting primary and incidental findings.
Methods: The project’s system utilized a regular expression to extract image references. All CTPA reports were first processed with NER software to obtain the text and spans of clinical findings. A heuristic was used to determine the appropriate clinical finding that should be linked with a particular image reference. Another regular expression was used to extract primary findings from NER output; the remaining findings were considered incidental. Performance was
assessed against a gold standard, which was based upon a manually annotated version of the CTPA reports used in this project.
Results: Extraction of image references achieved a 100% accuracy. Linkages between these references and exact gold standard spans of the clinical findings achieved a precision of 0.24, a recall of 0.22, and an F1 score of 0.23. Linkages with partial spans of clinical findings as determined by the gold standard achieved a precision of 0.71, a recall of 0.67, and an F1 score of 0.69. Primary and incidental finding extraction achieved a precision of 0.67, a recall of 0.80, and
an F1 score of 0.73.
Discussion: Various elements reduced system performance such as the difficulty of exactly matching the spans of clinical findings from NER output with those found in the gold standard. The heuristic linking clinical findings and image references was especially sensitive to NER false positives and false negatives due to its assumption that the appropriate clinical finding was that which was immediately prior to the image reference. Although the system did not perform as well as hoped, lessons were learned such as the need for clear research methodology and proper gold standard creation; without a proper gold standard, problem scope and system performance cannot be properly assessed. Improvements to the system include creating a more robust heuristic, sifting NER false positives, and training the NER tool used on a dataset of CTPA reports.
further process output from a machine learning based named entity recognition (NER) tool for the purposes of (1) linking references to radiological images with the corresponding clinical findings and (2) extracting primary and incidental findings.
Methods: The project’s system utilized a regular expression to extract image references. All CTPA reports were first processed with NER software to obtain the text and spans of clinical findings. A heuristic was used to determine the appropriate clinical finding that should be linked with a particular image reference. Another regular expression was used to extract primary findings from NER output; the remaining findings were considered incidental. Performance was
assessed against a gold standard, which was based upon a manually annotated version of the CTPA reports used in this project.
Results: Extraction of image references achieved a 100% accuracy. Linkages between these references and exact gold standard spans of the clinical findings achieved a precision of 0.24, a recall of 0.22, and an F1 score of 0.23. Linkages with partial spans of clinical findings as determined by the gold standard achieved a precision of 0.71, a recall of 0.67, and an F1 score of 0.69. Primary and incidental finding extraction achieved a precision of 0.67, a recall of 0.80, and
an F1 score of 0.73.
Discussion: Various elements reduced system performance such as the difficulty of exactly matching the spans of clinical findings from NER output with those found in the gold standard. The heuristic linking clinical findings and image references was especially sensitive to NER false positives and false negatives due to its assumption that the appropriate clinical finding was that which was immediately prior to the image reference. Although the system did not perform as well as hoped, lessons were learned such as the need for clear research methodology and proper gold standard creation; without a proper gold standard, problem scope and system performance cannot be properly assessed. Improvements to the system include creating a more robust heuristic, sifting NER false positives, and training the NER tool used on a dataset of CTPA reports.
ContributorsBorlongan, Matthew Bilog (Author) / Devarakonda, Murthy (Thesis director) / Murcko, Anita (Committee member) / College of Health Solutions (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05