College of Health Professions
Permanent URI for this collectionhttps://hdl.handle.net/10877/17051
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Browsing College of Health Professions by Department "Health Informatics and Information Management"
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Item Adoption and Utilization of Electronic Health Record Systems by Long-Term Care Facilities in Texas(American Health Information Management Association, 2012-05) Wang, Tiankai; Biedermann, SueLong-term care (LTC) is an important sector in the healthcare industry; however, the adoption of electronic health record (EHR) systems in LTC facilities lags behind that in other sectors of healthcare. This study examines the adoption and utilization of EHRs in LTC facilities in Texas and identifies the barriers preventing implementation of EHRs. A survey instrument was mailed to all Texas LTC facilities between October 2010 and March 2011. The survey found that in Texas, 39.5 percent of LTC facilities have fully or partially implemented EHR systems and 15 percent of LTC facilities have no plans to adopt EHRs yet. There is significant variation in the use of EHR functionalities across the LTC facilities in Texas. In the LTC facilities, the administrative functions of EHRs have been more widely adopted and are more widely utilized than the clinical functions of EHRs. Among the clinical functions adopted, the resident assessment, physician orders, care management plan, and census management are the leading functions used by the LTC facilities in Texas. Lack of capital resources is still the greatest barrier to EHR adoption and implementation. Policy makers, vendors, LTC administrators, educators, and researchers should make more effort to improve EHR adoption in LTC facilities.Item Big Data Analytics in Healthcare: Investigating the Diffusion of Innovation(American Health Information Management Association, 2019-06) Dolezel, Diane; McLeod, AlexanderThe shortage of data scientists has restricted the implementation of big data analytics in healthcare facilities. This survey study explores big data tool and technology usage, examines the gap between the supply and the demand for data scientists through Diffusion of Innovations theory, proposes engaging academics to accelerate knowledge diffusion, and recommends adoption of curriculum-building models. For this study, data were collected through a national survey of healthcare managers. Results provide practical data on big data tool and technology skills utilized in the workplace. This information is valuable for healthcare organizations, academics, and industry leaders who collaborate to implement the necessary infrastructure for content delivery and for experiential learning. It informs academics working to reengineer their curriculum to focus on big data analytics. The paper presents numerous resources that provide guidance for building knowledge. Future research directions are discussed.Item Cyber-Analytics: Identifying Discriminants of Data Breaches(American Health Information Management Association, 2019-06) Dolezel, Diane; McLeod, AlexanderIn this study, the relationship between data breach characteristics and the number of individuals affected by these violations was considered. Data were acquired from the Department of Health and Human Services breach reporting database and analyzed using SPSS. Regression analyses revealed that the hacking/IT incident breach type and network server breach location were the most significant predictors of the number of individuals affected; however, they were not predictive when combined. Moreover, network server location and unauthorized access/disclosure breach type were predictive when combined. Additional analyses of variance revealed that covered entity type and business associate presence were significant predictors, while the geographic region of a breach occurrence was insignificant. The results of this study revealed several associations between healthcare breach characteristics and the number of individuals affected, suggesting that more individuals are affected in hacking/IT incidents and network server breaches independently and that network server breach location and unauthorized access/disclosure breach type were predictive in combination.Item Deep Vision for Breast Cancer Classification and Segmentation(Multidisciplinary Digital Publishing Institute, 2021-10-27) Fulton, Lawrence V.; McLeod, Alexander; Dolezel, Diane; Bastian, Nathaniel; Fulton, Christopher P.(1) Background: Female breast cancer diagnoses odds have increased from 11:1 in 1975 to 8:1 today. Mammography false positive rates (FPR) are associated with overdiagnoses and overtreatment, while false negative rates (FNR) increase morbidity and mortality. (2) Methods: Deep vision supervised learning classifies 299 × 299 pixel de-noised mammography images as negative or non-negative using models built on 55,890 pre-processed training images and applied to 15,364 unseen test images. A small image representation from the fitted training model is returned to evaluate the portion of the loss function gradient with respect to the image that maximizes the classification probability. This gradient is then re-mapped back to the original images, highlighting the areas of the original image that are most influential for classification (perhaps masses or boundary areas). (3) Results: initial classification results were 97% accurate, 99% specific, and 83% sensitive. Gradient techniques for unsupervised region of interest mapping identified areas most associated with the classification results clearly on positive mammograms and might be used to support clinician analysis. (4) Conclusions: deep vision techniques hold promise for addressing the overdiagnoses and treatment, underdiagnoses, and automated region of interest identification on mammography.Item Enhance the Accuracy of Medication Histories for the Elderly by Using an Electronic Medication Checklist(American Health Information Management Association, 2012-09) Wang, Tiankai; Biedermann, SueMedication errors may result in serious safety issues for patients. Medication error issues are more prevalent among elderly patients, who take more medications and have prescriptions that change frequently. The challenge of obtaining accurate medication histories for the elderly at the time of hospital admission creates the potential for medication errors starting at admission.A study at a central Texas hospital was conducted to assess whether an electronic medication checklist can enhance the accuracy of medication histories for the elderly. The empirical outcome demonstrated that medication errors were significantly reduced by using an electronic medication checklist at the time of admission. The findings of this study suggest that implementing electronic health record systems with decision support for identifying inaccurate doses and frequencies of prescribed medicines will increase the accuracy of patients' medication histories.Item Examining Predictors of Myocardial Infarction(Multidisciplinary Digital Publishing Institute, 10/27/2021) Dolezel, Diane; McLeod, Alexander; Fulton, Lawrence V.Cardiovascular diseases are the leading cause of death in the United States. This study analyzed predictors of myocardial infarction (MI) for those aged 35 and older based on demographic, socioeconomic, geographic, behavioral, and risk factors, as well as access to healthcare variables using the Center for Disease (CDC) Control Behavioral Risk Factor Surveillance System (BRFSS) survey for the year 2019. Multiple quasibinomial models were generated on an 80% training set hierarchically and then used to forecast the 20% test set. The final training model proved somewhat capable of prediction with a weighted F1-Score = 0.898. A complete model based on statistically significant variables using the entirety of the dataset was compared to the same model built on the training set. Models demonstrated coefficient stability. Similar to previous studies, age, gender, marital status, veteran status, income, home ownership, employment status, and education level were important demographic and socioeconomic predictors. The only geographic variable that remained in the model was associated with the West North Central Census Division (in-creased risk). Statistically important behavioral and risk factors as well as comorbidities included health status, smoking, alcohol consumption frequency, cholesterol, blood pressure, diabetes, stroke, chronic obstructive pulmonary disorder (COPD), kidney disease, and arthritis. Three access to healthcare variables proved statistically significant: lack of a primary care provider (Odds Ratio, OR = 0.853, p < 0.001), cost considerations prevented some care (OR = 1.232, p < 0.001), and lack of an annual checkup (OR = 0.807, p < 0.001). The directionality of these odds ratios is congruent with a marginal effects model and implies that those without MI are more likely not to have a primary provider or annual checkup, but those with MI are more likely to have missed care due to the cost of that care. Cost of healthcare for MI patients is associated with not receiving care after accounting for all other variables.Item Health Information Technology Knowledge and Skills Needed by HIT Employers(Thieme Publishing, 2012-01) Fenton, Susan H.; Joost, E.; Gongora-Ferraez, M. J.Objective: To evaluate the health information technology (HIT) workforce knowledge and skills needed by HIT employers. Methods: Statewide face-to-face and online focus groups of identified HIT employer groups in Austin, Brownsville, College Station, Dallas, El Paso, Houston, Lubbock, San Antonio, and webinars for rural health and nursing informatics. Results: HIT employers reported needing an HIT workforce with diverse knowledge and skills ranging from basic to advanced, while covering information technology, privacy and security, clinical practice, needs assessment, contract negotiation, and many other areas. Consistent themes were that employees needed to be able to learn on the job and must possess the ability to think critically and problem solve. Many employers wanted persons with technical skills, yet also the knowledge and understanding of healthcare operations. Conclusion: The HIT employer focus groups provided valuable insight into employee skills needed in this fast-growing field. Additionally, this information will be utilized to develop a statewide HIT workforce needs assessment survey.