Browsing by Author "Patel, Jay"

Now showing 1 - 10 of 12
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    A Randomized Control Trial of Ravulizumab for Treatment of Patients With COVID-19 Infection and Kidney Injury
    (Elsevier, 2022) Memon, Aliza A.; Ahmed, Hasban; Li, Yi; Wongboonsin, Janewit; Hundert, Joshua; Benoit, Stefanie; Chaudhari, Advika; Sher, Jawad; Ghimire, Pratima; Hopkins, Rebecca; Patel, Jay; Stegman, Melinda; Lim, Kenneth; Azzi, Jamil; Siedlecki, Andrew M.; Medicine, School of Medicine
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    Assessing Information Congruence of Documented Cardiovascular Disease between Electronic Dental and Medical Records
    (2018) Patel, Jay; Mowery, Danielle; Krishnan, Anand; Thyvalikakath, Thankam
    Dentists are more often treating patients with Cardiovascular Diseases (CVD) in their clinics; therefore, dentists may need to alter treatment plans in the presence of CVD. However, it’s unclear to what extent patient-reported CVD information is accurately captured in Electronic Dental Records (EDRs). In this pilot study, we aimed to measure the reliability of patient-reported CVD conditions in EDRs. We assessed information congruence by comparing patients’ self-reported dental histories to their original diagnosis assigned by their medical providers in the Electronic Medical Record (EMR). To enable this comparison, we encoded patients CVD information from the free-text data of EDRs into a structured format using natural language processing (NLP). Overall, our NLP approach achieved promising performance extracting patients’ CVD-related information. We observed disagreement between self-reported EDR data and physician-diagnosed EMR data.
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    Best Practices for Health Informatician Involvement in Interprofessional Health Care Teams
    (Thieme, 2018-01) Holden, Richard J.; Binkheder, Samar; Patel, Jay; Viernes, Sara Helene P.; BioHealth Informatics, School of Informatics and Computing
    Academic and nonacademic health informatics (HI) professionals (informaticians) serve on interprofessional health care teams with other professionals, such as physicians, nurses, pharmacists, dentists, and nutritionists. Presently, we argue for investing greater attention to the role health informaticians play on interprofessional teams and the best practices to support this role.
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    Depressive Disorder Subtypes as Predictors of Incident Obesity in US Adults: Moderation by Race/Ethnicity
    (Oxford, 2017-05-01) Polanka, Brittanny M.; Vrany, Elizabeth A.; Patel, Jay; Stewart, Jesse C.; Psychology, School of Science
    We compared the relative importance of atypical major depressive disorder (MDD), nonatypical MDD, and dysthymic disorder in predicting 3-year obesity incidence and change in body mass index and determined whether race/ethnicity moderated these relationships. We examined data from 17,787 initially nonobese adults in the National Epidemiologic Survey on Alcohol and Related Conditions waves 1 (2001-2002) and 2 (2004-2005) who were representative of the US population. Lifetime subtypes of depressive disorders were determined using a structured interview, and obesity outcomes were computed from self-reported height and weight. Atypical MDD (odds ratio (OR) = 1.68, 95% confidence interval (CI): 1.43, 1.97; P < 0.001) and dysthymic disorder (OR = 1.66, 95% CI: 1.29, 2.12; P < 0.001) were stronger predictors of incident obesity than were nonatypical MDD (OR = 1.11, 95% CI: 1.01, 1.22; P = 0.027) and no history of depressive disorder. Atypical MDD (B = 0.41 (standard error, 0.15); P = 0.007) was a stronger predictor of increases in body mass index than were dysthymic disorder (B = -0.31 (standard error, 0.21); P = 0.142), nonatypical MDD (B = 0.007 (standard error, 0.06); P = 0.911), and no history of depressive disorder. Race/ethnicity was a moderator; atypical MDD was a stronger predictor of incident obesity in Hispanics/Latinos (OR = 1.97, 95% CI: 1.73, 2.24; P < 0.001) than in non-Hispanic whites (OR = 1.54, 95% CI: 1.25, 1.91; P < 0.001) and blacks (OR = 1.72, 95% CI: 1.31, 2.26; P < 0.001). US adults with atypical MDD are at particularly high risk of weight gain and obesity, and Hispanics/Latinos may be especially vulnerable to the obesogenic consequences of depressions.
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    Differences in medication usage of dental patients by age, gender, race/ethnicity and insurance status
    (IOS, 2021) Siddiqui, Zasim; Wang, Yue; Patel, Jay; Thyvalikakath, Thankam; Cariology, Operative Dentistry and Dental Public Health, School of Dentistry
    BACKGROUND: Limited studies have investigated the medication profile of young adult dental patients despite the high prevalence of prescription opioid abuse in this population. OBJECTIVE: This study investigated the extent and differences in medication usage of dental patients older than 18 years by age, race/ethnicity, gender, insurance status and mechanism of action in an academic dental clinic setting. METHODS: Using an automated approach, medication names in the electronic dental record were retrieved and classified according to the National Drug Code directory. Descriptive statistics, multivariable ANOVA and Post hoc tests were performed to detect differences in the number of medications by patient demographics. RESULTS: Of the 11,220 adult patients, 53 percent reported taking at least one medication with significant differences in medication usage by demographics. Hydroxymethylglutaryl-coenzyme A reductase inhibitors (21–36%), and angiotensin-converting enzyme inhibitors (19–23%) ranked the top two medication classes among patients 55 years and older. Opioid agonists (7–14%), and Selective Serotonin Reuptake Inhibitors (SSRIs) (5–12%) ranked the top two medication classes among patients aged 18–54 years. CONCLUSIONS: The results underscore the importance of dental providers to review medical and medication histories of patients regardless of their age to avoid adverse events and to determine patient’s risk for opioid abuse.
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    An Evaluation of Activity Trackers for Monitoring Parkinson's Disease Patient Outcomes
    (2016) Jones, Josette F.; Wu, Huanmei; Patel, Jay; Kasthurirathne, Suranga N.; Binkhedar, Samar; Thai, Nicole; Mukherjee, Sunanda
    Parkinson's disease (PD) is the second most common neurodegenerative disease in America. PD results in adverse outcomes including motor impairments and non-motor impairments such as cognition and sleep. Medication has a limited impact on treating PD and slowing down the progression of the disease. Anecdotal reports and some research show that intensive activity has been beneficial not only to slow down the progression of PD, but also may reverse the onset of more severe PD symptoms.
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    Extraction and Evaluation of Medication Data from Electronic Dental Records
    (IOS Press, 2017) Wang, Yue; Siddiqui, Zasim; Krishnan, Anand; Patel, Jay; Thyvalikakath, Thankam; Cariology, Operative Dentistry and Dental Public Health, School of Dentistry
    With an increase in the geriatric population, dental care professionals are presented with older patients who are managing their comorbidities using multiple medications. In this study, we developed a system to extract medication information from electronic dental records (EDRs) and provided patient distribution by the number of medications.
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    Extraction and Evaluation of Medication Data from Electronic Dental Records
    (IOS Press, 2017) Wang, Yue; Siddiqui, Zasim; Krishnan, Anand; Patel, Jay; Thyvalikakath, Thankam; Cariology, Operative Dentistry and Dental Public Health, School of Dentistry
    With an increase in the geriatric population, dental care professionals are presented with older patients who are managing their comorbidities using multiple medications. In this study, we developed a system to extract medication information from electronic dental records (EDRs) and provided patient distribution by the number of medications.
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    Identifying Patients' Smoking Status from Electronic Dental Records Data
    (IOS Press, 2017) Patel, Jay; Siddiqui, Zasim; Krishnan, Anand; Thyvalikakath, Thankam; Cariology, Operative Dentistry and Dental Public Health, School of Dentistry
    Smoking is a significant risk factor for initiation and progression of oral diseases. A patient's current smoking status and tobacco dependency can aid clinical decision making and treatment planning. The free-text nature of this data limits accessibility causing obstacles during the time of care and research utility. No studies exist on extracting patient's smoking status automatically from the Electronic Dental Record. This study reports the development and evaluation of an NLP system for this purpose.
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    Identifying Patients' Smoking Status from Electronic Dental Records Data
    (IOS Press, 2017) Patel, Jay; Siddiqui, Zasim; Krishnan, Anand; Thyvalikakath, Thankam; Cariology, Operative Dentistry and Dental Public Health, School of Dentistry
    Smoking is a significant risk factor for initiation and progression of oral diseases. A patient's current smoking status and tobacco dependency can aid clinical decision making and treatment planning. The free-text nature of this data limits accessibility causing obstacles during the time of care and research utility. No studies exist on extracting patient's smoking status automatically from the Electronic Dental Record. This study reports the development and evaluation of an NLP system for this purpose.